American International Group, Inc.

Telcordia Technologies, Inc.

Other

Tti Inventions C LLC

Devasis Bassu

Alvin Chou

Siddhartha R Dalal

Michael Castelli

Ashwath Aithal

Liangkai Zhang

Promiti Dutta

Ashish Jain

Clifford Behrens

Shoshana Loeb

Dennis Egan

Hiralal Agrawal

Thimios Panagos

Stephan Braig

Yoann Poirier

Stan Moyer

Rabih Zbib

Clifford A Behrens

Disclosed is a system and method to automatically identify property-related risks through the use of computer vision, sensors, and/or building information models (BIMs). The ability to automatically identify a variety of hazards helps mitigate the associated risks, and thus reduces the number of accidents or fatalities that would otherwise occur. In some embodiments, a 'risk map' can be generated by mapping the identified risks for a given property.

Systems and methods for dynamic real-time analysis from multi-modal data fusion for contextual risk identification

Performing information extraction from an electronic document is disclosed. A method comprises: receiving a semi-structured input document; retrieving an entity model that provides one or more domain variable definitions for one or more domain variables, wherein the entity model and the input document correspond to a common domain; determining that the input document includes an entity that satisfies a first domain variable definition corresponding to a first domain variable; retrieving a relational model that provides, for the first domain variable, one or more relational definitions comprising spatial restrictions for one or more values corresponding to the first domain variable; extracting one or more data elements from the input document that satisfy the one or more relational definitions; and generating an information graph having a structured data format, wherein the one or more data elements extracted from the input document correspond to the first domain variable in the structured data format.

Systems and methods for information extraction from text documents with spatial context

The invention disclosed here is aimed at enabling a trusted third party to manage user opt-ins which would enable growth of personalized information services, that is, enabling trusted business relationships between three types of entities&#x2014;an end-user, an information source/provider, and an application service provider/developer&#x2014;so that they can have a controlled, secure and private exchange of sensitive and/or confidential information. The inventive system has modes of operation recommended based on various conditions, enabling a secure exchange of private information between personal information repository owners and application services providers to enable deliver of personalized services. One mode is Durable Subscription Management, which is used when per transaction approval is not needed, that is, when an end-user has given permission to access data for a given or predefined period of time. A second mode is Per-Transaction Subscription Management Without Logs and a third mode is Per-Transaction Subscription Management With Logs.

System and method establishing trusted relationships to enable secure exchange of private information

The present invention concerns methods and apparatus for implementing a model-based paradigm for use in developing systems of software solutions. In a method of the present invention, a developer defines templates for use in creating software architecture elements which comprise a software solution or a system of software solutions. The template definitions comprise specifications of template attributes. The developer specifies relationships and dependencies among the templates using a computer programmed to receive the template definitions.

Methods and apparatus for implementing model-based software solution development and integrated change management

Indexing, searching, and retrieving the content of speech documents (including but not limited to recorded books, audio broadcasts, recorded conversations) is accomplished by finding and retrieving speech documents that are related to a query term at a conceptual level, even if the speech documents does not contain the spoken (or textual) query terms. Concept-based cross-media information retrieval is used. A term-phoneme/document matrix is constructed from a training set of documents. Documents are then added to the matrix constructed from the training data. Singular Value Decomposition is used to compute a vector space from the term-phoneme/document matrix. The result is a lower-dimensional numerical space where term-phoneme and document vectors are related conceptually as nearest neighbors. A query engine computes a cosine value between the query vector and all other vectors in the space and returns a list of those term-phonemes and/or documents with the highest cosine value.

Concept based cross media indexing and retrieval of speech documents

The use of latent semantic indexing (LSI) for information retrieval and text mining operations is adapted to work on large heterogeneous data sets by first partitioning the data set into a number of smaller partitions having similar concept domains. A similarity graph network is generated in order to expose links between concept domains which are then exploited in determing which domains to query as well as in expanding the query vector. LSI is performed on those partitioned data sets most likely to contain information related to the user query or text mining operation. In this manner LSI can be applied to datasets that heretofore presented scalability problems. Additionally, the computation of the singular value decomposition of the term-by-document matrix can be accomplished at various distributed computers increasing the robustness of the retrieval and text mining system while decreasing search times.

Information retrieval and text mining using distributed latent semantic indexing

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Bedminster, NJ, United States of America

Devasis Bassu