| Entries |
| Document | Title | Date |
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| 20080243750 | Human Artificial Intelligence Software Application for Machine & Computer Based Program Function - A method of creating human artificial intelligence in machines and computer software is presented here, as well as methods to simulate human reasoning, thought and behavior. A new human artificial intelligence software application for machines & computer based program function, which generally comprises computer based software code and programming as well as processes and methods of application, which receives movie sequences from the environment, uses an image processor to generate an initial encapsulated tree, searches for the current pathway in memory and find the best pathway matches, determines the best long-term future pathways, locates an optimal pathway, stores current pathway in optimal pathway, follows the future instructions of optimal pathway, and universalizes data in memory. The present invention further provide users with a software application that will serve as the main intelligence of one or a multitude of computer based programs, software applications, machines or compilation of machinery. | 10-02-2008 |
| 20080275838 | CONFLICTING RULE RESOLUTION SYSTEM - A method for identifying conflicting and duplicate rules in a decision support system is provided. The method includes establishing a first subsystem including a protocol of existing rules, each existing rule includes an input feature. The method also includes creating a new rule that includes an input feature, and comparing terminology in the input feature of the new rule against terminology in the input feature of each existing rule of the protocol using a second subsystem and determining whether the new rule and at least one existing rule from the protocol are similar. | 11-06-2008 |
| 20080294590 | Reluctant Episodic Memory (REM) to Store Experiences of Everyday Interaction With Objects - A method and system for storing episodic sequences (events and actions). The system learns episodic sequencing by observing real-world events and actions or by receiving fact data from a database storing common sense facts. The episodic sequences are classified into events and actions, processed to indicate correlations and causality between the events and actions, and generated into linked graphs. The linked graphs may then be used to draw inferences, recognize patterns, and make decisions. | 11-27-2008 |
| 20080313126 | METHOD FOR A DISTRIBUTED CONTROL SYSTEM - In an arrangement, functions and/or structures in a distributed control system ( | 12-18-2008 |
| 20090006306 | Creating A Session Log For Studying Usability Of One Or More Computing Devices Used For Social Networking - Methods, systems, and products are disclosed for creating a session log for studying usability of one or more computing devices used for social networking that include: receiving, by a usability engine from at least one usability expert, usability observations observed by the usability expert during a usability session for studying interaction support provided by one or more computing devices to a plurality of users interacting within a social network through the computing devices; recording, by the usability engine, the usability observations in a session log; detecting, by an event listener on at least one of the computing devices, an event generated by the computing device as a result of an interaction among the plurality of users within the social network; notifying, by the event listener, the usability engine of the event; and recording, by the usability engine, a description of the event in the session log. | 01-01-2009 |
| 20090012928 | System And Method For Generating An Amalgamated Database - A method for creating an amalgamated bioinformatics database from at least a first database and a second database is presented. Concepts are identified in a first field from the records of the first database. A second field from the records of the second database which has data related to the first field is also identified. A first set of concepts is identified by traversing a mediating database using terms associated with the first field and a second set of concepts is also identified by traversing the mediating database using terms associated with the second field. Either the first set of concepts or the second set of concepts, or both, is identified using non-trivial terminological mapping. The set of related concepts in the first set of concepts and the second set of concepts is identified and a record is generated in the amalgamated bioinformatics database. | 01-08-2009 |
| 20090049002 | SYSTEM AND METHOD FOR SELECTING A TRAINING SAMPLE FROM A SAMPLE TEST - Described are a system and method for selecting a training sample from a sample set. The method comprises determining proximities between all data samples in a set of the data samples, forming edges between the data samples as a function of the proximities, computing weights for the edges as a function of the proximities, selecting a plurality of the data samples as a function of the weights to form a subset of the data samples, and storing the subset of the data samples. | 02-19-2009 |
| 20090063391 | Updating an Engine Using a Description Language - Functionality is described for sending updated engine logic to a user device. The engine logic is expressed in a description language, such as the extensible markup language (XML). The user device uses the updated engine logic to update a parse tree. The user device then uses the parse tree to process various events. By virtue of the formation of the engine logic in a description language, a network-accessible service can disseminate the engine in an efficient manner. In one illustrative application, the user device can use the parse tree to process electronic messages (e.g., Email messages) that have been received by the user device | 03-05-2009 |
| 20090077002 | KNOWLEDGE BASED SYNCHRONIZATION OF SUBSETS OF DATA WITH NO MOVE CONDITION - An efficient way is provided to represent and exchange knowledge and/or partial knowledge across nodes when synchronizing between any two nodes. A first node sends a second node its knowledge and/or partial knowledge, including objects and versions of those objects. The second node compares its knowledge and/or partial knowledge with the knowledge and/or partial knowledge of the first node, and then sends the first node any latest versions of objects of which the first node is unaware. In addition, the second node sends its knowledge and/or partial knowledge to the first node. The first node then performs a similar object-by-object version comparison to determine any conflicts due to independent evolution of objects and any changes that should be sent to the second node in order to bring the objects of the second node up to date with the knowledge and/or partial knowledge of the first node. | 03-19-2009 |
| 20090089239 | SYSTEM AND METHOD FOR BUILDING A RULEBASE - A method for building a rulebase includes receiving a plurality of rulebase components. The method also includes merging the rulebase components to create a consolidated rulebase. | 04-02-2009 |
| 20090106184 | LOCATING DENSE AND ISOLATED SUB-GRAPHS - Methods and apparatus for locating a dense and isolated sub-graph from a weighted graph having multiple nodes and multiple weighted edges are described. Each node in the weighted graph represents an object. Each weighted edge in the weighted graph connects two nodes and represents the relationship between the two objects represented by the two corresponding nodes. To located the sub-graph, first, an auxiliary weighted graph is constructed using the weighted graph and three coefficients: α, β, and γ, where α, β, and γ are greater than 0, α influences the number of nodes inside the sub-graph, β influences the sum of the weights associated with the edges connecting a node inside the sub-graph and a node outside the sub-graph, and γ influences the sum of the weights associated with the edges connecting two nodes both inside the sub-graph, and by adding a source node s and a sink node t. Next, the auxiliary weighted graph is partitioned into two parts using the s-t minimum cut algorithm. The sub-graph is the part associated with the sink node t in its original form, with the original undirected edges and unmodified edge weights and excluding the sink node t and all the new edges added during the construction of the auxiliary weighted graph. | 04-23-2009 |
| 20090240651 | Systems and Methods for a Predictive Notification Engine - Certain embodiments of the present invention provide a system for predictive notification including a notification engine adapted to receive a sequence of data values for a parameter from a medical device. The notification engine is adapted to determine a prediction based at least in part on the sequence of data values. The notification engine is adapted to generate a notification based on the prediction. | 09-24-2009 |
| 20090276391 | CREATION OF NEURO-FUZZY EXPERT SYSTEM FROM ONLINE ANALYTICAL PROCESSING (OLAP) TOOLS - A method for automatic generation of a Neuro-Fuzzy Expert System (Fuzzy Logic Expert System implemented as a Neural Network) from data. The method comprising a Data Interface allowing description of location, type, and structure of the Data. The Interface also allows designation of input attributes and output attributes in the Data Structure; automatic Neuro-Fuzzy Expert System generation driven by the Data; Training of the Expert System's Neural Network on the Data and the presentation of results which include new knowledge embedded in the parameters and structure of the trained Neuro-Fuzzy Expert System to a user. | 11-05-2009 |
| 20090299949 | LIMITING RULE BASE MODIFICATION - Various embodiments herein include one or more of systems, methods, data structures, and software operable to limit how rules, or components thereof, may be modified. Some embodiments include receiving a rule definition in a system, the rule definition including one or more rule components, each component including a reference to one or more values from which an inference is made when the rule is applied. Such embodiments further include associating one or more rule components with one or more tag definitions that limit how the one or more associated rule components are modifiable by one or more rule administrators. The rule definition and the associations of tag definitions to the rule components may then be stored in a data store. | 12-03-2009 |
| 20090327206 | FORECASTING BY BLENDING ALGORITHMS TO OPTIMIZE NEAR TERM AND LONG TERM PREDICTIONS - Described is time-weighted blending of the results of time series algorithms in a manner that changes their relative weights based on the prediction time. The prediction values from each algorithm are mathematically blended into a forecast result corresponding to the desired time of prediction. In this manner, an ARTXP algorithm that provides accurate near term predictions is given more weight than an ARIMA for near term predictions, and less relative weight for long term predictions. An example exponential function to compute the relative weights is described; the function corresponds to a curve having a control variable for the slope and the start of the curve, and constant coefficients, with the weights based (in part) on the prediction time. A user-provided parameter may also affect the relative weights used in the blending result. | 12-31-2009 |
| 20100023475 | METHOD AND SYSTEM FOR CREATING A PREDICTIVE MODEL FOR TARGETING WEBPAGE TO A SURFER - A system and method for creating a predictive model to select an object from a group of objects that can be associated with a requested web page, wherein a configuration of the requested web page defines a subgroup of one or more selected objects from the group of objects. Exemplary embodiments of the present invention seek to provide novel solutions for determining which content object, taken from a group of content objects, will be best suited for presentation in association with a link on a web page that has been requested by a certain surfer. Each web page can include one or more links to be associated with content objects from the group. | 01-28-2010 |
| 20100042578 | Computational system and method for memory modification - Systems and methods are described relating to accepting an indication of at least one memory-related condition and presenting an indication of at least one artificial sensory experience and at least one memory-dampening agent at least partially based on the accepting at least one indication of a health-related condition. | 02-18-2010 |
| 20100057665 | METHOD AND SYSTEM FOR ENHANCING COMPUTER OBJECT RULES AND CATALOGS - A method, a machine-readable storage medium and a system are provided for enhancing computer rules in a computer application. In an embodiment, a rule is accessed from a set of computer rules provided by a computer application. The rule includes a number of fields, e.g., an attribute field and an enhancement type field. In response to receiving an input attribute and an input enhancement type, the rule is updated in the set of computer rules. The updated rule is implemented and operation of the updated rule in the computer application is altered based on the inputs. | 03-04-2010 |
| 20100057666 | METHOD AND SYSTEM FOR ENHANCING AND MERGING COMPUTER OBJECT RULES - A method, a machine-readable storage medium and a system are provided for revising content in a computer rule set. The revisions may be made by an issuer of content. In an embodiment, it is determined whether a difference exists between content data in a production table corresponding to a computer rule set and enhanced content data in an enhanced data table. If a difference is determined to exist, the content data is read from the production table and the enhanced content data is read from the enhanced data table. The enhancement data is identified as that assigned to the first issuer. Whether the rule enhanced in the computer rule set is allowed to be revised is confirmed. Based on the results of the determining and confirming, the enhanced data from the enhanced data table is incorporated into the production data table to provide a revised computer rule set. | 03-04-2010 |
| 20100057667 | DETECTION RULE-GENERATING FACILITY - An apparatus for generating event detection rules in a multiple-component computer system in accordance with embodiments of the invention may include a configuration information-extracting section for acquiring system configuration information from a multiple-component computer system. The system configuration information may include related information that describes relationships among system components. The apparatus may further include a history information-collecting section for collecting history information from the multiple-component computer system, such as log information and/or failure information output from a component upon a system failure. A candidate event-identifying section may identify candidate events that may be selected by a user to generate a detection rule based on the system configuration information and the history information. Finally, a candidate event-presenting section may present the candidate events to a user for selection. | 03-04-2010 |
| 20100070457 | Efficient Data Layout Techniques for Fast Machine Learning-Based Document Ranking - A computer readable medium stores a program for optimization for a search, and has sets of instructions for receiving a first decision tree. The first decision tree includes several nodes, and each node is for comparing a feature value to a threshold value. The instructions are for weighting the nodes within the first decision tree, determining the weighted frequency of a first feature within the first decision tree, and determining the weighted frequency of a second feature within the first decision tree. The instructions order the features based on the determined weighted frequencies, and store the ordering such that values of features having higher weighted frequencies are retrieved more often than values of features having lower weighted frequencies within the first decision tree. | 03-18-2010 |
| 20100070458 | RULE CREATION METHOD AND RULE CREATING APPARATUS - An information processing apparatus obtains, from an F-CMDB for managing CIs regarding resources and their attribute values, CIs with the type and attribute of the resource for which a rule is to be created for use at the time of comparison between CIs. From the F-CMDB for managing CIs of SRC and CIs of DST, and relations between SRC and DST together, the information processing apparatus also obtains CI pairs with SRC including any CI previously obtained and also having a relation corresponding to the determination objective of the rule. Then, the information processing apparatus subjects CIs of SRC with the same classification as that defined in a CI of DST to grouping. Then, the information processing apparatus stores a group of CIs of SRC obtained through grouping in a rule DB as a rule for the determination objective. | 03-18-2010 |
| 20100121813 | METHOD OF COMPARING DATA SEQUENCES - A method according to the present invention enables the similarity between sequences of symbols to be determined using rules generated from a dictionary-based compression scheme according to the content of the columns from databases. Pairs of symbols can replaced by rules that do not comprise a repeated combination of two symbols and where each rule occurs more than once in the sequence of symbols. The similarity of each set of rules can then be expressed numerically. | 05-13-2010 |
| 20100153330 | Proactive Information Technology Infrastructure Management - Disclosed herein is a computer implemented method and system for analyzing load responsive behavior of infrastructure components in an electronic environment for proactive management of the infrastructure components. Transaction data on multiple application transactions is collected. Load patterns are identified from the collected transaction data for generating load profiles. Data on infrastructure behavior in response to the application transactions is collected. Infrastructure behavior patterns are identified from the infrastructure behavior data for generating behavior profiles. The generated load profiles and the generated behavior profiles are correlated to create a load responsive behavior model. The created load responsive behavior model predicts behavior of the infrastructure components for different load patterns. A live data stream from current application transactions is analyzed using the load responsive behavior model to determine current load responsive behavior. Deviations of the current load responsive behavior from the predicted behavior are detected using the load responsive behavior model. | 06-17-2010 |
| 20100161547 | Personalized Web Feed Views - A system for generation of personalized Web feed views in accordance with pre-defined profile parameters, is presented. The system including a user definition interface for receiving at least one user parameter and sending the parameter to a content provider and a feed view personalization unit operable to receive the user parameter and customize feed content in accordance with the at least one user parameter for displaying to the user. | 06-24-2010 |
| 20100191699 | DATA PROCESSING IN A DISTRIBUTED COMPUTING ENVIRONMENT - A computerized system configured to provide a data cell graph for a distributed data set comprised of different data formats. The system comprises a plurality of data repositories, each data repository configured to retain a portion of the distributed data set translated into a uniform semantic language and a plurality of processing cells, each processing cell configured to translate a portion of the distributed data set into the uniform semantic language, wherein the processing cells are further configured to perform at least one of applying rules to classify data against semantic knowledge models and/or adding inferred facts to and/or transforming the structure of the data found in the translated data in the data repository. The processing cells are configured in a computerized data cell graph so as to progressively create a unified semantic knowledge model for the distributed data set. | 07-29-2010 |
| 20100280989 | ONTOLOGY CREATION BY REFERENCE TO A KNOWLEDGE CORPUS - A computer-implemented method and computer readable media for creating an ontology for a domain by reference to a knowledge corpus comprising linked documents and a category hierarchy wherein each document can be contained in one or more categories and wherein categories can contain one or more other categories. In some embodiments, the method comprises: searching the corpus to identify documents with text that matches a seed domain description; identifying further documents within the corpus that are semantically similar to the identified documents; identifying a subgraph of the category hierarchy that includes the categories assigned to the extracted documents and the further documents; reducing the subgraph to form the ontology by requiring that documents therein be indicative of a second domain description, the second domain description being at least as broad as the seed domain description. | 11-04-2010 |
| 20110004582 | METHOD OF CONSTRUCTING THE INTELLIGENT COMPUTER SYSTEMS BASED ON INFORMATION REASONING - A method of constructing the intelligent computer systems based on information reasoning, the method comprising the steps of: obtaining the problem from the users and analyzing the corresponding user demands; choosing the data relating to the user demands in databases and collecting the external data for solving the problems; preprocessing the data and generating the data tables; computing the field of probability on the basis of data tables; computing the degree of credibility of the information reasoning rule according to the new information theory; outputting the information reasoning rule “if A, then B” and its degree of credibility; storing the results of the discovered information reasoning rules. The intelligent computer systems constructed by this patent can extract information from the large amount of data automatically. The intelligent systems can decide whether A and B are positively related or negatively related to each other according to the degree of credibility of the information reasoning rule “if A, then B”, moreover, the degree of credibility shows the sufficient degree of the evidences in the reasoning. Since the present patent can help the users to obtain valuable information from the large amount of data, this method can be widely used to construct the intelligent systems based on the large amount of data. | 01-06-2011 |
| 20110047123 | SYSTEM AND METHOD FOR BUILDING AND MERGING A RULEBASE WITH OBJECT ORIENTED SOFTWARE - A method for building a rulebase includes receiving a plurality of rulebase components. The method also includes merging the rulebase components to create a consolidated rulebase. | 02-24-2011 |
| 20110167032 | MOVEMENT OF AN AGENT THAT UTILIZES A COMPILED SET OF CANONICAL RULES - A method includes obtaining, at a first execution environment of a first device, an as-needed rule set. The as-needed rule set is a subset of context-specific rules filtered from a total potential rule set based at least on a hardware characteristic of a second execution environment. The as-needed rule set is associated with an agent. The agent and the as-needed rule set are encoded into a transferable form. The encoded agent and the encoded as-needed rule set are sent from the first execution environment to the second execution environment. | 07-07-2011 |
| 20110202495 | ADJUSTABLE ALERT RULES FOR MEDICAL PERSONNEL - A method, a system, and a computer-readable medium are provided for adjusting an alert rule used to indicate a status of a patient. A first user interface window is presented. The first user interface window includes a plurality of values of physiological characteristics of a patient. An indicator of a selection of a physiological characteristic presented in the first user interface window is received. A second user interface window is presented. The second user interface window includes a first user interface control configured to allow a user to adjust a first alert value for a first condition priority associated with the selected physiological characteristic. The adjusted first alert value is received and stored as part of an adjusted alert rule. A future alert is generated based on the adjusted alert rule. | 08-18-2011 |
| 20110208689 | COMMUNITY-DRIVEN MAP CREATION AND ACCESS - Techniques for creating and enabling access to a community-augmented map are provided. The techniques include uploading user-generated content about one or more locations on a map, processing the user-generated content about one or more locations on the map and storing the user-generated content about one or more locations on the map in an intelligent knowledgebase, applying one or more domain concepts from the intelligent knowledgebase to the user-generated content to infer one or more derivatives in connection with one or more locations in the map, and retrieving information of the one or more locations on the map from the intelligent knowledgebase to provide the map information as augmented metadata on the map. | 08-25-2011 |
| 20110213749 | METHOD, DEVICE AND SYSTEM FOR THE FUSION OF INFORMATION ORIGINATING FROM SEVERAL SENSORS - The invention relates to a method, device and system for fusion of information originating from several sensors. The invention includes a mechanism for fusion of belief functions. To apply this mechanism, various information, knowledge and operations are modelled within the framework of the theory of belief functions: information provided by the sensors, knowledge regarding the propensity of the sensors to be in a given operating state, and merge operators for each operating state considered. | 09-01-2011 |
| 20110270797 | System and Method to Define, Validate and Extract Data for Predictive Models - The present invention provides a System and Method to Define, Validate and Extract Data for Predictive Models. A system of sensors is deployed in an environment, with additional sensors for ambient data whose output as a form of metadata can characterize performance conditions including background ambient conditions. A format or sequence of processes is the basis for a math model to establish a logical weight to data for predictive modeling and event reporting. The present invention provides a computer or other sensor interface system with a primary sensor or sensors, network connection, and supplementary sensors to measure the conditions in which the primary data is captured. A software process allows for user inputs of data in order to establish the methods and rules for normal function. | 11-03-2011 |
| 20120023062 | ROBUST INFORMATION FUSION METHODS FOR DECISION MAKING FOR MULTISOURCE DATA - Methods and systems are provided for developing decision information relating to a single system based on data received from a plurality of sensors. The method includes receiving first data from a first sensor that defines first information of a first type that is related to a system, receiving second data from a second sensor that defines second information of a second type that is related to said system, wherein the first type is different from the second type, generating a first decision model, a second decision model, and a third decision model, determining whether data is available from only the first sensor, only the second sensor, or both the first and second sensors, and selecting based on the determination of availability an additional model to apply the available data, wherein the additional model is selected from a plurality of additional decision models including the third decision model. | 01-26-2012 |
| 20120089555 | BDD Variable Reordering Using Parallel Permutation - One embodiment accesses a binary decision diagram (BDD) representing a function having n variables, where n≧2, wherein: the BDD comprises n layers corresponding to the n variables, respectively; and the BDD has a first variable order where each variable i is at layer i for 1≦i≦n; and reorders the n variables of the BDD according to a second variable order denoted as π(i), where each variable i is at layer π(i) for 1≦i≦n, by iteratively and alternatingly swapping one or more first disjoint pairs of consecutive layers during each odd iteration and swapping one or more second disjoint pairs of consecutive layers during each even iteration, until the second variable order is achieved, wherein during each iteration, two consecutive layers are swapped only if a current order of two variables at the two consecutive layers differs from an order of the two variables specified by the second variable order. | 04-12-2012 |
| 20120089556 | Optimum Layer-Swapping Schedules for BDDs with Four Variables - One embodiment accesses a binary decision diagram (BDD) representing a function having 4 variables, variables | 04-12-2012 |
| 20120089557 | Determining Optimum Variable Orders for BDDs Using Pair-Wise Variable Grouping - One embodiment accesses a binary decision diagram (BDD) representing a function having n variables, where n≧2, wherein the BDD comprises n layers corresponding to the n variables, respectively; separates the n variables into | 04-12-2012 |
| 20120089558 | Determining Optimum Variable Orders for BDDs Using Recursion - One embodiment accesses a binary decision diagram (BDD) representing a function having n variables; constructs one group of one ordered set of the n variables; recursively constructs one or more new groups of one or more ordered sets of one or more variables, replacing existing groups of one or more ordered sets of one or more variables, until each existing group comprises one or more ordered sets of k variables or less, where 1≦k| 04-12-2012 | |
| 20120089559 | Parallel Window Algorithm - One embodiment accesses a binary decision diagram (BDD) representing a function having n variables, where n≧2, wherein the BDD comprises it layers corresponding to the n variables, respectively; and reorders the n variables of the BDD by iteratively and alternating reordering a plurality of disjoint sets of k consecutive layers in parallel, where 1| 04-12-2012 | |
| 20120089560 | Window Algorithm Using Maximal Parallelization - One embodiment accesses a binary decision diagram (BDD) representing a function having n variables, where n≧2, wherein the BDD comprises n layers corresponding to the n variables, respectively; and reorders the n variables of the BDD by iteratively and alternating reordering k consecutive layers, where 1| 04-12-2012 | |
| 20120089561 | Parallel Sifting Algorithm - One embodiment accesses a binary decision diagram (BDD) representing a function having n variables; and reorders the n variables of the BDD by iteratively moving k variables of the n variables to their locally optimum layers, until a size of the BDD has reached a desired threshold, wherein each iteration comprises: selects from the n layers k layers that currently have the k largest sizes among the n layers, wherein the k variables are currently positioned at the k layers; iteratively and concurrently moves the k variables to different layers of the BDD until each of the k variables has been at all the n layers to determine a locally optimum layer for each of the k variables, wherein the locally optimum layer of a variable during each iteration is one of the n layers that currently yields a smallest size among the n layers with the variable at each of the n layers; and concurrently moves the k variables to their respective locally optimum layers. | 04-12-2012 |
| 20120158640 | METHOD AND SYSTEM FOR CREATING A DYNAMIC SYSTEMS BASED HYBRID MODEL FOR REASONING SYSTEMS - A method for creating a dynamic systems based hybrid model for reasoning systems is described. The method receives, at a server, a plurality of expert identified deal attributes. The method presents a conjoint analysis questionnaire for input by one or more respondents. The conjoint analysis questionnaire includes questions based on the plurality of expert identified deal attributes. The method receives responses of the one or more respondents to the conjoint analysis questionnaire. The method then defines an expert reasoning model based on the responses of the one or more respondents to the conjoint analysis questionnaire. The method accesses historical deal information of one or more deals, the historical deal information including one or more deals, each deal including a plurality of expert identified deal attributes and a part-worth associated with each of the deal attributes. Finally, the method validates the expert reasoning model based on the historical deal information. | 06-21-2012 |
| 20120197836 | PORTABLE DATA MANAGEMENT - Embodiments for methods, systems, and computer program products for creating and managing a portable data rule using an electronic computing device are presented including: causing the electronic computing device to create a rule definition including, defining an expression by a user, where the expression defines a logic of a rule, causing the electronic computing device to parse the expression into a logical variable associated with the expression, causing the electronic computing device to identify the logical variable, and causing the electronic computing device to store the rule definition, where the rule definition includes the expression and the logical variable. In some embodiments, the causing the electronic computing device to identify the logical variable includes: causing the electronic computing device to return a name of the logical variable; and causing the electronic computing device to return an expected type of the logical variable. | 08-02-2012 |
| 20120203732 | BEHAVIOR PATTERN EXTRACTION SYSTEM, APPARATUS, METHOD AND RECORDING MEDIUM STORING PROGRAM - There is provided a behavior pattern extraction system which can extract user's behavior pattern with high accuracy. The behavior pattern extraction system includes: a location information acquiring section measuring location points which each indicate a location of a user; a staying point extraction section setting staying points and staying records based on an range in which location points which are each measured in a first period are concentrated, wherein the staying points each indicate a location where the user has stayed temporarily; a representative staying point extraction section setting a representative staying point and a representative staying record based on an range in which the staying points which are set in a second period which is longer than the first period are concentrated, wherein the representative staying point indicates a location where the user has repeatedly visited, and the representative staying record indicates an error range of the location of the representative staying point; and a behavior pattern record section recording the representative staying point and the representative staying record in a storage area as behavior pattern information of the user. | 08-09-2012 |
| 20120278274 | SYSTEM FOR PROVIDING INFORMATION AND INFORMATION EXPERTS TO A PLURALITY OF USERS - A method to provide an information item and information expert to a user includes storing a first information item, task data, and a first expert identifier in a database. The task data includes a plurality of tasks and at least one attribute associated with each of the tasks. The first expert identifier identifies a first expert associated with the first information item and/or the first task. A task information update is created by associating the first information item with the first task in response to determining that it is related to the at least one attribute associated with the first task, and by providing the first expert identifier with the task information update in response to determining that it is associate with at least one of the first information item and the first task. Users that are associated with the first task are then provided the task information update. | 11-01-2012 |
| 20120278275 | GENERATING A PREDICTIVE MODEL FROM MULTIPLE DATA SOURCES - Techniques are disclosed for generating an ensemble model from multiple data sources. In one embodiment, the ensemble model is generated using a global validation sample, a global holdout sample and base models generated from the multiple data sources. An accuracy value may be determined for each base model, on the basis of the global validation dataset. The ensemble model may be generated from a subset of the base models, where the subset is selected on the basis of the determined accuracy values. | 11-01-2012 |
| 20130024417 | METHOD, SYSTEM AND COMPUTER PROGRAM PRODUCT FOR AUTOMATIC GENERATION OF BAYESIAN NETWORKS FROM SYSTEM RELIABILITY MODELS - A method, apparatus and computer program product for the conversion of at least one reliability model of a technical system to a Bayesian network model for assisting in the system's failure diagnostics, has the steps of creating a structure of a Bayesian network using information from at least one reliability model of the technical system, creating parameters of the Bayesian network using information from the reliability model of the technical system, the Bayesian network model having a plurality of observation nodes, obtaining information about the plurality of observation nodes from a list of observations that augments information contained in the reliability model of the technical system, and inserting the observation nodes into the created structure of the Bayesian network. | 01-24-2013 |
| 20130080381 | Combining Medical Binary Decision Diagrams for Size Optimization - In particular embodiments, a method includes accessing a first binary decision diagram (BDD) representing a data stream from a first sensor and a second BDD representing a data stream from a second sensor, constructing a third BDD by performing an OR operation between the first and second BDDs, determining sizes of the first, second, and third BDDs, and if the third BDD is smaller than the sum of the first and second BDDs, then storing the third BDD, else storing the first and second BDDs. | 03-28-2013 |
| 20130080382 | Compression Threshold Analysis of Binary Decision Diagrams - In particular embodiments, a method includes receiving data sets, constructing a first binary decision diagram (BDD) representing the data sets, iteratively adding data from the data sets to the first BDD until a compression rate of the first BDD reaches a threshold compression rate, constructing a second BDD representing data from the data sets received after the compression rate of the first BDD equals a threshold compression rate, and iteratively adding data from the data sets to the second BDD. | 03-28-2013 |
| 20130173527 | Life Cycle Management Of Rule Sets - Life cycle management of rule sets, each rule set including rules for managing the operation of a computing system, including: identifying, by a life cycle management module, a rule life cycle state for each rule in the rule set, wherein the rule life cycle state specifies the current deployment status of the rule; identifying, by the life cycle management module, a linkage set for each rule in the rule set, wherein the linkage set identifies versions of the rule that are in a different rule life cycle state; and updating, by the life cycle management module, the rule set, including: updating the rule life cycle state for one or more rules in the rule set; and updating the linkage set for one or more rules in the rule set. | 07-04-2013 |
| 20130232104 | DUPLICATION IN DECISION TREES - A packet classification system, apparatus, and corresponding apparatus are provided for enabling packet classification. A processor of a security appliance coupled to a network uses a classifier table having a plurality of rules, the plurality of rules having at least one field, to build a decision tree structure for packet classification. Duplication in the decision tree may be identified, producing a wider, shallower decision tree that may result in shorter search times with reduced memory requirements for storing the decision tree. A number of operations needed to identify duplication in the decision tree may be reduced, thereby increasing speed and efficiency of a compiler building the decision tree. | 09-05-2013 |
| 20130246332 | METHODS AND SYSTEMS FOR IMPLEMENTING A COMPOSITIONAL RECOMMENDER FRAMEWORK - A compositional recommender framework using modular recommendation functions is described. Each modular recommendation function can use a discrete technology, such as using clustering, a database lookup, or other means. A first recommendation function can recommend to a user items, such as books to check out, automobiles to purchase, people to date, etc. Another modular recommendation function can be daisy chained with the first to recommend items that are similar or related to the first recommended items, such as users who have also checked out the same recommended book, trailers that can be towed by the recommended automobiles, or vacations booked by people that were recommended as people to date. The modular recommendation functions can be used to build customized recommendation engines for different industries. | 09-19-2013 |
| 20130246333 | SYSTEM TO CREATE AND USE TEST PLANS USABLE IN VALIDATING A REAL WORLD MODEL IN SOFTWARE OF A SAFETY INSTRUMENTED SYSTEM ARCHITECTURE FOR SAFETY INSTRUMENTED SYSTEMS IN A FACILITY - A system to computer generate, manage, analyze, or combinations thereof, a real world model in software of a safety instrumented system (SIS) architecture for SIS in a facility, and generate test plans, wherein the SIS architecture for SIS in a facility comprises at least one instrumented protective function (IPF) and wherein the test plans support process safety lifecycle management. | 09-19-2013 |
| 20130254153 | TECHNIQUES FOR EVALUATION, BUILDING AND/OR RETRAINING OF A CLASSIFICATION MODEL - Techniques for evaluation and/or retraining of a classification model built using labeled training data. In some aspects, a classification model having a first set of weights is retrained by using unlabeled input to reweight the labeled training data to have a second set of weights, and by retraining the classification model using the labeled training data weighted according to the second set of weights. In some aspects, a classification model is evaluated by building a similarity model that represents similarities between unlabeled input and the labeled training data and using the similarity model to evaluate the labeled training data to identify a subset of the plurality of items of labeled training data that is more similar to the unlabeled input than a remainder of the labeled training data. | 09-26-2013 |
| 20130282648 | DETERMINISTIC FINITE AUTOMATON MINIMIZATION - Deterministic finite automaton (DFA) minimization includes representing a DFA as a data structure including a plurality of states, incoming transitions for each state, and outgoing transitions for each state. A state of the plurality of states is selected as a selected state. The incoming transitions are analyzed for the selected state. A computer determines whether source states of the incoming transitions for the selected state include a pair of equivalent states. The pair of equivalent states is merged based on determining that two of the source states of the incoming transitions for the selected state form the pair of equivalent states. | 10-24-2013 |
| 20130282649 | DETERMINISTIC FINITE AUTOMATION MINIMIZATION - Deterministic finite automaton (DFA) minimization includes representing a DFA as a data structure including a plurality of states, incoming transitions for each state, and outgoing transitions for each state. A state of the plurality of states is selected as a selected state. The incoming transitions are analyzed for the selected state. A computer determines whether source states of the incoming transitions for the selected state include a pair of equivalent states. The pair of equivalent states is merged based on determining that two of the source states of the incoming transitions for the selected state form the pair of equivalent states. | 10-24-2013 |
| 20130318028 | DECISION SERVICE MANAGER - The disclosure generally describes computer-implemented methods, software, and systems for modeling and deploying decision services. One computer-implemented method includes creating a connection between a decision service manager and a managed system, establishing a signature of a decision service, developing, using at least one computer, the decision service based upon the established signature of the decision service, performing a deployment readiness check, transferring generated code implementing the decision service to the managed system upon a determination that the deployment readiness check was successful, inserting the generated code into the managed system, and retrieving a deployment status from the managed system. | 11-28-2013 |
| 20130318029 | DISTRIBUTED ORDER ORCHESTRATION SYSTEM WITH EXTENSIBLE FLEX FIELD SUPPORT - A distributed order orchestration system publishes one or more newly generated artifacts that are generated as a result of generating one or more extensible flex fields to a rule dictionary. The distributed order orchestration system then imports the one or more newly generated artifacts within the rule dictionary as one or more facts. The distributed order orchestration system then creates one or more rules for the rule dictionary that references the one or more facts. | 11-28-2013 |
| 20140019404 | METHODS FOR THE CONSTRUCTION AND MAINTENANCE OF A COMPUTERIZED KNOWLEDGE REPRESENTATION SYSTEM - Methods for constructing and maintaining knowledge representation systems are disclosed herein. The knowledge representation system is initially organized and populated using knowledge engineers. After the initial organization, scientific domain experts digest and structure source texts for direct entry into the knowledge representation system using templates created by the knowledge engineers. These templates constrain both the form and content of the digested information, allowing it to be entered directly into the knowledge representation system. Although knowledge engineers are available to evaluate and dispose of those instances when the digested information cannot be entered in the form required by the templates, their role is much reduced from conventional knowledge representation system construction methods. The methods disclosed herein permit the construction and maintenance of a much larger knowledge representation system than could be constructed and maintained using known methods. | 01-16-2014 |
| 20140108329 | LOGIC MODEL FOR MEDIA CUSTOMIZATION - A computing device receives a plurality of media files. Further, the computing device generates a hierarchical logic model for media playback. The hierarchical logic model organizes the plurality of media files for playback into a hierarchy according to a predetermined set of conditions. In addition, a set of code is provided to a media player for media playback based upon the logic model. | 04-17-2014 |
| 20140122410 | RECONFIGURABLE MODEL FOR AUTO-CLASSIFICATION SYSTEM AND METHOD - A reconfigurable automatic document-classification system and method provides classification metrics to a user and enables the user to reconfigure the classification model. The user can refine the classification model by adding or removing exemplars, creating, editing or deleting rules, or performing other such adjustments to the classification model. This technology enhances the overall transparency and defensibility of the auto-classification process. | 05-01-2014 |
| 20140136469 | LOGIC MODEL FOR MEDIA CUSTOMIZATION WITH ITEM ASSOCIATION - A computing device receives a plurality of media files. Further, the computing device associates an item with a media file from the plurality of media files according to an association. The item is displayed during display of the media file. The association has a predetermined playback time during playback of the media file at which item data is displayed in addition to the display of the media file. In addition, the computing device generates a hierarchical logic model for media playback. The hierarchical logic model organizes the plurality of media files for playback into a hierarchy according to a predetermined set of conditions. A set of code is provided to a media player for media playback based upon the logic model and the association between the item and the media file. | 05-15-2014 |
| 20140172774 | METHOD AND DEVICE FOR NAMED-ENTITY RECOGNITION - The present application discloses a method and a device for generating a recognizing model for recognizing named entities, and a method and a device for recognizing named entities. The method for recognizing named entities comprising: obtaining a first characteristic information set of a text to be trained; recognizing the first characteristic information set based on the first recognizing model to obtain a second characteristic information set which comprises M named entities obtained by recognizing the first characteristic information set through the first recognizing model, wherein M is an integer larger than or equal to 0; and performing error-correction on the M named entities in the second characteristic information set based on the error driving model to obtain K named entities, wherein K is an integer lager than or equal to 0 but less than or equal to M. | 06-19-2014 |
| 20140188781 | Methods and Systems of Using Boosted Decision Stumps and Joint Feature Selection and Culling Algorithms for the Efficient Classification of Mobile Device Behaviors - Methods and systems for classifying mobile device behavior include configuring a server use a large corpus of mobile device behaviors to generate a full classifier model that includes a finite state machine suitable for conversion into boosted decision stumps and/or which describes all or many of the features relevant to determining whether a mobile device behavior is benign or contributing to the mobile device's degradation over time. A mobile device may receive the full classifier model and use the model to generate a full set of boosted decision stumps from which a more focused or lean classifier model is generated by culling the full set to a subset suitable for efficiently determining whether mobile device behavior are benign. Boosted decision stumps may be culled by selecting all boosted decision stumps that depend upon a limited set of test conditions. | 07-03-2014 |
| 20140222751 | CONSTRUCTION OF TREE-SHAPED BAYSIAN NETWORK - Embodiments relate to constructing a tree-shaped Bayesian network from variables associated with conditional dependencies in a given data set, the constructing being performed by a plurality of processors in parallel. An aspect includes assigning a plurality of variables as nodes to a respective plurality of processors. Another aspect includes operating the plurality of processors in a parallel manner to determine a correlation for each pair of nodes. Another aspect includes M variables that are randomly selected as primary nodes defining (M+1) sub-trees. Another aspect includes in each sub-tree the plurality of processors are operated in a parallel manner to determine a correlation for the remaining nodes with each of the primary nodes and to allocate each remaining node to one of the (M+1) sub-trees. | 08-07-2014 |
| 20140250052 | ANALYZING SOCIAL BEHAVIOR - A relational event history is determined based on a data set, the relational event history including a set of relational events that occurred in time among a set of actors. Data is populated in a probability model based on the relational event history, where the probability model is formulated as a series of conditional probabilities that correspond to a set of sequential decisions by an actor for each relational event. The set of sequential decisions includes a decision to send a communication, and one or more decisions as to recipients. For a relational event in the relational event history, one or more possible sequences in which the actor decided to include the recipients of the communication are determined. A baseline communications behavior for the relational event history is determined, and departures from the baseline communications behavior within the relational event history are determined. | 09-04-2014 |
| 20140317044 | Method And Device for Real-Time Knowledge Processing Based on an Ontology With Temporal Extensions - Embodiments are directed towards a method and a computer server for receiving assertions, wherein an assertion can have a functional property such that for a given subject and a given property the object has a single value at any time, maintaining a knowledge base that includes (1) a history table that stores previously received assertions, and (2) a snapshot table that stores currently valid assertions, maintaining a snapshot cache in memory that stores a subset of the assertions in the snapshot table, initiating a processing cycle, selecting an assertion for processing, generating an assertion tuple that corresponds to the selected assertion, determining that the property of the selected assertion is functional, writing a retraction tuple to the history table, writing the assertion tuple to the snapshot table; and writing the assertion tuple to the history table. | 10-23-2014 |
| 20160171372 | Method And Device for Real-Time Knowledge Processing Based on an Ontology With Temporal Extensions | 06-16-2016 |
