Patent application number | Description | Published |
20080215299 | Asynchronous Hidden Markov Model Method and System - A system, method and program storage device implementing a method for modeling a data generating process, wherein the modeling comprises observing a data sequence comprising irregularly sampled data, obtaining an observation sequence based on the observed data sequence, assigning a time index sequence to the data sequence, obtaining a hidden state sequence of the data sequence, and decoding the data sequence based on a combination of the time index sequence and the hidden state sequence to model the data sequence. The method further comprises assigning a probability distribution over time stamp values of the observation sequence, wherein the decoding comprises using a Hidden Markov Model. The method further comprises using an expectation maximization methodology to learn the Hidden Markov Model. | 09-04-2008 |
20090049021 | SYSTEM AND METHOD FOR STORING TEXT ANNOTATIONS WITH ASSOCIATED TYPE INFORMATION IN A STRUCTURED DATA STORE - A text annotation structured storage system stores text annotations with associated type information in a structured data store. The present system persists or stores annotations in a structured data store in an indexable and queryable format. Exemplary structured data stores comprise XML databases and relational databases. The system exploits type information in a type system to develop corresponding schemas in a structured data model. The system comprises techniques for mapping annotations to an XML data model and a relational data model. The system captures various features of the type system, such as complex types and inheritance, in the schema for the persistent store. In particular, the repository provides support for path navigation over the hierarchical type system starting at any type. | 02-19-2009 |
20090192987 | SEARCHING NAVIGATIONAL PAGES IN AN INTRANET - Exemplary embodiments of the present invention relate to a method for searching navigational pages within an intranet environment. The method comprises identifying a plurality of navigational pages, performing a page-level analysis upon each identified navigational page in order to determine if a navigational page can be categorized as a candidate navigational page, performing a cross-page analysis upon each determined candidate navigational page in order to generate a final set of navigational pages, associating each final navigational page with a predetermined semantic classification group, generating term variants for each navigational page, building a navigational index for each semantic classification grouping, and filtering user queries in association with a user profile of a user that is posing a query. | 07-30-2009 |
20090198646 | SYSTEMS, METHODS AND COMPUTER PROGRAM PRODUCTS FOR AN ALGEBRAIC APPROACH TO RULE-BASED INFORMATION EXTRACTION - Systems, methods and computer program products for an algebraic approach to rule-based information extraction. Exemplary embodiments include a method for rule-based information extraction, the method including specifying an annotator using algebraic operators, wherein each algebraic operator describes annotations identification from text documents. | 08-06-2009 |
20120226639 | Systems and Methods for Processing Machine Learning Algorithms in a MapReduce Environment - Systems and methods for processing Machine Learning (ML) algorithms in a MapReduce environment are described. In one embodiment of a method, the method includes receiving a ML algorithm to be executed in the MapReduce environment. The method further includes parsing the ML algorithm into a plurality of statement blocks in a sequence, wherein each statement block comprises a plurality of basic operations (hops). The method also includes automatically determining an execution plan for each statement block, wherein at least one of the execution plans comprises one or more low-level operations (lops). The method further includes implementing the execution plans in the sequence of the plurality of the statement blocks. | 09-06-2012 |
20140129211 | SVO-BASED TAXONOMY-DRIVEN TEXT ANALYTICS - Organizing textual data into statement clusters. Sentences are extracted from textual data and parsed. A verb usage pattern is identified and an SVO triplet is determined. The SVO triplet is compared to a taxonomy associated with the domain of the data and a sentiment is derived. A statement cluster is constructed comprising a higher level SVO triplet sensitive to the taxonomy and verb usage pattern, as well as the derived sentiment. Accordingly, the statement clusters may be organized by grouping. | 05-08-2014 |
20140129213 | SVO-BASED TAXONOMY-DRIVEN TEXT ANALYTICS - Organizing textual data into statement clusters. Sentences are extracted from textual data and parsed. A verb usage pattern is identified and an SVO triplet is determined. The SVO triplet is compared to a taxonomy associated with the domain of the data and a sentiment is derived. A statement cluster is constructed comprising a higher level SVO triplet sensitive to the taxonomy and verb usage pattern, as well as the derived sentiment. Accordingly, the statement clusters may be organized by grouping. | 05-08-2014 |
20150051900 | UNSUPERVISED LEARNING OF DEEP PATTERNS FOR SEMANTIC PARSING - Using exemplary sentences, usage patterns and thematic roles ascribed in VerbNet to generate “deep pattern trees” for the exemplary sentences. Then, when an arbitrary natural language subject sentence is input, these deep pattern trees can be matched to the natural language subject sentence in order to assign thematic roles to at least some of the “grammatical portions” of the natural language subject sentence. | 02-19-2015 |