Patent application number | Description | Published |
20080242420 | Adaptive Matchmaking for Games - Matchmaking processes at online game services often result in players having to wait unacceptably long times to receive a match or immediately receiving a poorly matched session. By using a matchmaking process which dynamically adapts a good balance is achieved between the quality of proposed matches (for example, in terms of how balanced, interesting and fun those matches are likely to be) and the waiting time for potential matches. A matchmaking threshold is specified. When a player seeks a match a waiting time is observed, for example, as to how long that player waits until starting a game or dropping out. Information about such waiting times is used to dynamically update the matchmaking threshold. The update is made on the basis of a relationship between information about the observed waiting time and a target waiting time. Further control may be achieved by using separate matchmaking thresholds and target waiting times for different game categories. | 10-02-2008 |
20090043593 | Event Prediction - There are many situations in which it is desired to predict outcomes of events. In an example, an event prediction system is described which receives variables for a proposed event. The system accesses learnt statistics describing belief about weights associated with the variables and uses the weights to determine probability information that the proposed event will have a specified outcome. The process involves combining the accessed statistics and mapping them into a number representing the probability. In another example, a machine learning process using assumed density filtering is used to learn the statistics from data about observed events. The event prediction system may be used as part of any suitable type of system such as an internet advertising system, an email filtering system, or a fraud detection system. | 02-12-2009 |
20090093287 | Determining Relative Player Skills and Draw Margins - A process for determining relative player skills and draw margins is described. Information about an outcome of a game between at least a first player opposing a second player is received. Also, for each player, skill statistics are received associated with a distribution representing belief about skill of that player. Draw margin statistics are received associated with a distribution representing belief about ability of that player to force a draw. An update process is performed to update the statistics on the basis of the received information about the game outcome. In an embodiment a Bayesian inference process is used during the update process which may take past and future player achievement into account. | 04-09-2009 |
20100100416 | Recommender System - A recommender system may be used to predict a user behavior that a user will give in relation to an item. In an embodiment such predictions are used to enable items to be recommended to users. For example, products may be recommended to customers, potential friends may be recommended to users of a social networking tool, organizations may be recommended to automated users or other items may be recommended to users. In an embodiment a memory stores a data structure specifying a bi-linear collaborative filtering model of user behaviors. In the embodiment an automated inference process may be applied to the data structure in order to predict a user behavior given information about a user and information about an item. For example, the user information comprises user features as well as a unique user identifier. | 04-22-2010 |
20100262568 | Scalable Clustering - A scalable clustering system is described. In an embodiment the clustering system is operable for extremely large scale applications where millions of items having tens of millions of features are clustered. In an embodiment the clustering system uses a probabilistic cluster model which models uncertainty in the data set where the data set may be for example, advertisements which are subscribed to keywords, text documents containing text keywords, images having associated features or other items. In an embodiment the clustering system is used to generate additional features for associating with a given item. For example, additional keywords are suggested which an advertiser may like to subscribe to. The additional features that are generated have associated probability values which may be used to rank those features in some embodiments. User feedback about the generated features is received and used to revise the feature generation process in some examples. | 10-14-2010 |
20110066577 | Machine Learning Using Relational Databases - Machine learning using relational databases is described. In an embodiment a model of a probabilistic relational database is formed by augmenting relation schemas of a relational database with probabilistic attributes. In an example, the model comprises constraints introduced by linking the probabilistic attributes using factor statements. For example, a compiler translates the model into a factor graph data structure which may be passed to an inference engine to carry out machine learning. For example, this enables machine learning to be integrated with the data and it is not necessary to pre-process or reformat large scale data sets for a particular problem domain. In an embodiment a machine learning system for estimating skills of players in an online gaming environment is provided. In another example, a machine learning system for data mining of medical data is provided. In some examples, missing attribute values are filled using machine learning results. | 03-17-2011 |
20110131163 | Managing a Portfolio of Experts - Managing a portfolio of experts is described where the experts may be for example, automated experts or human experts. In an embodiment a selection engine selects an expert from a portfolio of experts and assigns the expert to a specified task. For example, the selection engine has a Bayesian machine learning system which is iteratively updated each time an experts performance on a task is observed. For example, sparsely active binary task and expert feature vectors are input to the selection engine which maps those feature vectors to a multi-dimensional trait space using a mapping learnt by the machine learning system. In examples, an inner product of the mapped vectors gives an estimate of a probability distribution over expert performance. In an embodiment the experts are automated problem solvers and the task is a hard combinatorial problem such as a constraint satisfaction problem or combinatorial auction. | 06-02-2011 |
20110184778 | Event Prediction in Dynamic Environments - Event prediction in dynamic environments is described. In an embodiment a prediction engine may use the learnt information to predict events in order to control a system such as for internet advertising, email filtering, fraud detection or other applications. In an example one or more variables exists for pre-specified features describing or associated with events and each variable is considered to have an associated weight and time stamp. For example, belief about each weight is represented using a probability distribution and a dynamics process is used to modify the probability distribution in a manner dependent on the time stamp for that weight. For example, the uncertainty about the associated variable's influence on prediction of future events is increased. Examples of different schedules for applying the dynamics process are given. | 07-28-2011 |
20110313832 | PRICING IN SOCIAL ADVERTISING - Online recommendations are tracked through a forwarding service. The forwarding service can provide such statistics to an ad service, which can provide incentives to the recommending user and a consuming user. Example incentives may include an accumulation of points by the recommending user, a discount to the consuming user if a purchase is made in response to the recommendation, etc. To determine how much of an incentive each participant in the recommendation flow receives, a graph is created to model the recommendation flow and incentives are allocated using a cooperative game description based on this graph that associates each participant with a power index that represents that participants share of the incentive. | 12-22-2011 |
20110313833 | RECONSTRUCTING THE ONLINE FLOW OF RECOMMENDATIONS - Online recommendations are tracked through a forwarding service. For example, a user may send an email to a friend recommending a product specified at a web site identified by a URI embedded in the email. Before sending the email, the user submits the URI to a forwarding service, which returns a new URI mapped to the original URI and to the recommending user. The recommending user can then recommend the web site by forwarding the new URI to the friend. If the friend selects the recommended URI to review the web site, the forwarding service records the decision to review the web site and directs the friend to the recommended web site. The forwarding service maintains a database of recommendations made by the recommending user, recommendation consumed by the friend, etc. Incentives can be provided to the recommending user and the friend to encourage recommendations. | 12-22-2011 |
20120089446 | Publishing Commercial Information in a Social Network - A publishing engine captures commercial information associated with a first user and automatically notifies other users in the first user's social network of this commercial information. The first user authorizes an e-commerce system to access his or her social network and to publish commercial information about the first user's commercial activity (e.g., a purchase or other commercial transaction) to users in the social network. By this automated notification, the notified users in the first user's social network can learn that the first user has completed a commercial transaction pertaining to a particular product or service. If a notified user is interested in a similar product or service, he or she can contact the first user to inquire about the first user's experience and information with the product or service. | 04-12-2012 |
20120089581 | Informing Search Results Based on Commercial Transaction Publications - A publishing engine captures capturing commercial events and other information (collectively, “commercial information”) associated with a first user and automatically notifies other users in the social network of the first user of this commercial information. The publishing engine also notifies one or more search engines of these events and information. Based on this commercial information, the search engine can augment search results of the members of the social network to include historical notifications relating to commercial transactions for similar products and/or services by others in their social network. In this manner, for example, the search engine can provide results directing the searcher to other users in their social network who have purchased such products and/or services. | 04-12-2012 |
20120101965 | TOPIC MODELS - Machine learning techniques may be used to train computing devices to understand a variety of documents (e.g., text files, web pages, articles, spreadsheets, etc.). Machine learning techniques may be used to address the issue that computing devices may lack the human intellect used to understand such documents, such as their semantic meaning. Accordingly, a topic model may be trained by sequentially processing documents and/or their features (e.g., document author, geographical location of author, creation date, social network information of author, and/or document metadata). Additionally, as provided herein, the topic model may be used to predict probabilities that words, features, documents, and/or document corpora, for example, are indicative of particular topics. | 04-26-2012 |
20120150771 | Knowledge Corroboration - Knowledge corroboration is described. In an embodiment many judges provide answers to many questions so that at least one answer is provided to each question and at least some of the questions have answers from more than one judge. In an example a probabilistic learning system takes features describing the judges or the questions or both and uses those features to learn an expertise of each judge. For example, the probabilistic learning system has a graphical assessment component which aggregates the answers in a manner which takes into account the learnt expertise in order to determine enhanced answers. In an example the enhanced answers are used for knowledge base clean-up or web-page classification and the learnt expertise is used to select judges for future questions. In an example the probabilistic learning system has a logical component that propagates answers according to logical relations between the questions. | 06-14-2012 |
20130024448 | RANKING SEARCH RESULTS USING FEATURE SCORE DISTRIBUTIONS - Document features or document ranking values can be associated with a distribution of values. Feature values, feature value coefficients, and/or document ranking values can be generated based on sampled values from the distribution of values. This can allow the relative ranking of a document to vary. As additional information is obtained regarding the document, leading to greater certainty about the appropriate ranking of the document, the width or variation generated by the distribution can be reduced to provide more stable ranking values | 01-24-2013 |
20130103692 | Predicting User Responses - Predicting user responses to items is useful in many application domains, such as personalized information retrieval and recommendation systems. In an embodiment a contacts service identifies contacts of a target user and predictions are elicited from the contacts about the target user's response to an item. In various examples, the predictions are combined taking into account weights of the contacts to produce a prediction of the target user's response. For example, the response may be one or more of: a numerical rating, a word or phrase describing the targets user's opinion of the item and a word or phrase stating a reason that the target user holds the opinion. In examples, accuracy of the predictions is calculated after observing the target user's actual response. The accuracy may be used to calculate and display scores and rankings of the contact's prediction abilities and to update the weights of the contacts. | 04-25-2013 |
20130346844 | CHECKING AND/OR COMPLETION FOR DATA GRIDS - Checking and/or completing for data grids is described such as for grids having rows and columns of cells at least some of which contain data values such as numbers or categories. In various embodiments predictive probability distributions are obtained from an inference engine for one or more of the cells and the predictive probability distributions are used for various tasks such as to suggest values to complete blank cells, highlight cells having outlying values, identify potential errors, suggest corrections to potential errors, identify similarities between cells, identify differences between cells, cluster rows of the data grid, and other tasks. In various embodiments a graphical user interface displays a data grid and provides facilities for completing, error checking/correcting, and analyzing data in the data grid. | 12-26-2013 |
20140101090 | MODELING DATA GENERATING PROCESS - There is provided a method and system for modeling a data generating process. The method includes generating a dyadic Bayesian model including a pair of probabilistic functions representing a prior distribution and a sampling distribution, and modeling a data generating process based on the dyadic Bayesian model using observed data. | 04-10-2014 |
20140156571 | TOPIC MODELS - Machine learning techniques may be used to train computing devices to understand a variety of documents (e.g., text files, web pages, articles, spreadsheets, etc.). Machine learning techniques may be used to address the issue that computing devices may lack the human intellect used to understand such documents, such as their semantic meaning. Accordingly, a topic model may be trained by sequentially processing documents and/or their features (e.g., document author, geographical location of author, creation date, social network information of author, and/or document metadata). Additionally, as provided herein, the topic model may be used to predict probabilities that words, features, documents, and/or document corpora, for example, are indicative of particular topics. | 06-05-2014 |
Patent application number | Description | Published |
20090143784 | Tibial Aiming Device For The Double Channel Technique | 06-04-2009 |
20100082045 | FLIPP TACK PUSHER - A device for pushing an anchor through a bore in a bone is provided with an elongated shaft, an anchor carrying assembly disposed at a distal end of the shaft for carrying an anchor, and a plunger disposed in the elongated shaft. The plunger is movable relative to the elongated shaft. First, threads are attached to the anchor. Then, the anchor is positioned in the anchor fastener, and the elongated shaft is placed next to the bore in the bone. Next, the plunger is inserted into the elongated shaft, and a force is exerted to on the plunger to move it in direction of the distal end of the elongated shaft such that a distal end of the plunger comes into contact with the anchor and pushes the anchor through the bore in the bone. | 04-01-2010 |
20100204731 | Suture Holding System - A suture holding system including a suture and a block having first, second and third regions for receiving the suture, having proximal and distal ends, is provided. The suture is received in the first and second regions of the block, defining a first suture portion, and is then received in the third region before passing between the block and the first suture portion, defining a second suture portion. In this configuration, pulling on the distal end of the suture selectively locks the suture to block, whereas pulling on the proximal end of the suture allows the suture to advance freely in that direction. Suture holding system may also include a second block, being rotated 180 degrees with respect to the first block. A delivery device for implanting the suture holding system in soft tissue and methods for repairing a tear in soft tissue are also provided. | 08-12-2010 |
20130006303 | Flipp Tack Pusher - A device and method for pushing an anchor through a bore in a bone is provided with an elongated shaft, an anchor carrying assembly disposed at a distal end of the shaft for carrying an anchor, and a plunger disposed in the elongated shaft. The plunger is movable relative to the elongated shaft. First, threads are attached to the anchor. Then, the anchor is positioned in the anchor fastener, and the elongated shaft is placed next to the bore in the bone. Next, the plunger is inserted into the elongated shaft, and a force is exerted to on the plunger to move it in direction of the distal end of the elongated shaft such that a distal end of the plunger comes into contact with the anchor and pushes the anchor through the bore in the bone. Then, the threads attached to the anchor are pulled to position the anchor. | 01-03-2013 |
20130096613 | Suture Holder Delivery System - A suture holder delivery system including a housing having a distal end and a proximal end, a first driver mechanism and a second driver mechanism, each movable in a longitudinal direction with respect to the housing, a first delivery needle and a second delivery needle, the first delivery needle connected at a proximal end to the first driver mechanism and the second delivery needle connected at a proximal end to the second driver mechanism, the first driver mechanism and said second driver mechanism each having fully retracted and fully extended positions and a toggle assembly operable to fix at least one of the first driver mechanism and second driver mechanism in at least one longitudinal position. The delivery system may alternatively or additionally include a locking mechanism operable to prevent the second driver mechanism from being moved in a distal direction until the first driver mechanism is longitudinally advanced to the extended position. | 04-18-2013 |
20130103085 | Suture Anchor Kit - A suture anchor kit including first and second suture anchors, each having two eyelets, and first and second sutures, each having a free end and a fixed end, where the first suture is received in a first of the two eyelets of the first suture anchor and a first of the two eyelets of the second suture anchor and where the second suture is received in a second of said two eyelets of the first suture anchor and a second of the two eyelets of the second suture anchor, the fixed end of the first suture being connected to the free end of the second suture via a first knot and the fixed end of the second suture being connected to the free end of the first suture via a second knot is provided. The kit may also include a delivery device including a housing, a first driver mechanism and a second driver mechanism, each movable in a longitudinal direction with respect to the housing, the first suture anchor being in communication with said the driver mechanism and the second suture anchor being in communication with the second driver mechanism.. | 04-25-2013 |