Patent application number | Description | Published |
20110055811 | Discovery, Analysis, and Visualization of Dependencies - Product data pertaining to a plurality of products is gathered from a plurality of sources. Dependency information for the plurality of products is extracted from the product data. The dependency information is analyzed to determine dependencies for each product of the plurality of products. The dependencies for each product of the plurality of products are displayed to a user. | 03-03-2011 |
20110191762 | MINING DEPENDENCIES FROM DISK IMAGES - Methods and arrangements for automatically finding the dependency of a software product on other software products or components. From an install image or directory, a signature is found by deriving the same from a directory structure of the software. Further, a directory tree structure is built and an approximate sub-tree matching algorithm is applied to find commonalties across software products. | 08-04-2011 |
20110235909 | ANALYZING DOCUMENTS USING STORED TEMPLATES - A method, a system and a computer program product for analyzing a document are disclosed. In response to receiving the document, the document is partitioned into a plurality of segments using a set of pre-defined attributes. The plurality of segments of the document is mapped with corresponding segments of at least one template selected from a set of stored templates. A first template from the set of stored templates is selected and a group of segments in the first template is identified by computing at least one of a structural similarity and a textual similarity associated with the group of segments compared with the plurality of segments of the document. A subset of segments from the group of segments is aligned with corresponding segments from the plurality of segments of the document. A set of scores is computed using a set of pre-defined criteria, in response to the mapping. The document is analyzed based on the computed set of scores. | 09-29-2011 |
20120185415 | SYSTEM AND METHOD FOR DOMAIN ADAPTION WITH PARTIAL OBSERVATION - System, method and computer program product provides a novel domain adaption/transfer learning approach applied to the problem of classifying abbreviated documents, e.g., short text messages, instant messages, tweets. The proposed method uses a large number of multi-labeled examples (source domain) to improve the learning on the partial observations (target domain). Specifically, a hidden, higher-level abstraction space is learned that is meaningful for the multi-labeled examples in the source domain. This is done by simultaneously minimizing the document reconstruction error and the error in a classification model learned in the hidden space using known labels from the source domain. The partial observations in the target space are then mapped to the same hidden space, and classified into the label space determined by the source domain. Exemplary results provided for a Twitter dataset demonstrate that the method identifies meaningful hidden topics and provides useful classifications of specific tweets. | 07-19-2012 |
20120323939 | MINING DEPENDENCIES FROM DISK IMAGES - Methods and arrangements for automatically finding the dependency of a software product on other software products or components. From an install image or directory, a signature is found by deriving the same from a directory structure of the software. Further, a directory tree structure is built and an approximate sub-tree matching algorithm is applied to find commonalities across software products. | 12-20-2012 |
20130013539 | SYSTEM AND METHOD FOR DOMAIN ADAPTION WITH PARTIAL OBSERVATION - System, method and computer program product provides a novel domain adaption/transfer learning approach applied to the problem of classifying abbreviated documents, e.g., short text messages, instant messages, tweets. The proposed method uses a large number of multi-labeled examples (source domain) to improve the learning on the partial observations (target domain). Specifically, a hidden, higher-level abstraction space is learned that is meaningful for the multi-labeled examples in the source domain. This is done by simultaneously minimizing the document reconstruction error and the error in a classification model learned in the hidden space using known labels from the source domain. The partial observations in the target space are then mapped to the same hidden space, and classified into the label space determined by the source domain. Exemplary results provided for a Twitter dataset demonstrate that the method identifies meaningful hidden topics and provides useful classifications of specific tweets. | 01-10-2013 |
Patent application number | Description | Published |
20120123956 | SYSTEMS AND METHODS FOR MATCHING CANDIDATES WITH POSITIONS BASED ON HISTORICAL ASSIGNMENT DATA - Systems and associated methods for matching candidates with positions through an automated scoring and ranking process utilizing a scoring function based on previous assignments. The ranking of candidates includes identifying the position requirements, mining relevant candidate information, prioritizing mined information based upon past assignments, and ranking candidates based on how well they match the position requirements. The systems and methods are applicable for use in different environments, including online job portals, recruiting services, and by company human resource departments. | 05-17-2012 |
20120323812 | MATCHING CANDIDATES WITH POSITIONS BASED ON HISTORICAL ASSIGNMENT DATA - Systems and associated methods for matching candidates with positions through an automated scoring and ranking process utilizing a scoring function based on previous assignments. The ranking of candidates includes identifying the position requirements, mining relevant candidate information, prioritizing mined information based upon past assignments, and ranking candidates based on how well they match the position requirements. The systems and methods are applicable for use in different environments, including online job portals, recruiting services, and by company human resource departments. | 12-20-2012 |
20130219165 | SYSTEM AND METHOD FOR PROCESSING FEEDBACK ENTRIES RECEIVED FROM SOFTWARE - A method and system for processing feedback entries received from software provided by a vendor to an end user machine. The end user machine includes the software, a feedback module, and a database. The feedback module: generates an encryption E | 08-22-2013 |
20130232342 | SYSTEM FOR PROCESSING FEEDBACK ENTRIES RECEIVED FROM SOFTWARE - A system for processing feedback entries received from software provided by a vendor to an end user machine. The end user machine includes the software, a feedback module, and a database. The feedback module: establishes a secret key k(0) and a secret key n(0; generates an identification tag FE(0); generates a secret key s(0); generates an encryption E | 09-05-2013 |