Thomson Reuters Global Resources

Refinitiv US Organization LLC

Other

Columbia University

Thomson Reuters Global Resources Unlimited Company

Camelot UK Bidco Limited

Hassan Malik

Mans Olof-Ors

Ian MacGillivray

Christy Hatch

John Ronald Kender

Jason E Rollins

Andrej Bugrim

Enav Weinreb

Shai Hertz

Ellen Rotenberg

Tim Miller

Mans A Olof-Ors

Colin Williams

Mark Gordon

Systems and techniques for exploring relationships among entities are disclosed. The systems and techniques provide an entity-based information analysis and content aggregation platform that uses heterogeneous data sources to construct and maintain an ecosystem around tangible and logical entities. Entities are represented as vertices in a directed graph, and edges are generated using entity co-occurrences in unstructured documents and supervised information from structured data sources. Significance scores for the edges are computed using a method that combines supervised, unsupervised and temporal factors into a single score. Important entity attributes from the structured content and the entity neighborhood in the graph are automatically summarized as the entity fingerprint. Entities may be compared to one another based on similarity of their entity fingerprints. An interactive user interface is also disclosed that provides exploratory access to the graph and supports decision support processes.

Entity fingerprints

Systems and techniques for determining significance between entities are disclosed. The systems and techniques identify a first entity having an association with a second entity, apply a plurality of association criteria to the association, weight each of the criteria based on defined weight values, and compute a significance score for the first entity with respect to the second entity based on a sum of a plurality of weighted criteria values. The systems and techniques utilize information from disparate sources to create a uniquely powerful signal. The systems and techniques can be used to identify the significance of relationships (e.g., associations) among various entities including, but not limited to, organizations, people, products, industries, geographies, commodities, financial indicators, economic indicators, events, topics, subject codes, unique identifiers, social tags, industry terms, general term/s, metadata elements, classification codes, and combinations thereof.

Association significance

Systems and method for making intelligent business development and licensing decisions are disclosed. The present invention generally relates to an analytical tool that combines multiple data and content sets based on user selected factors and presents the data in the form of manipulatable visualizations to facilitate decision making to address a specific business problem. More specifically, this invention relates to providing a single portal for access to a decision support system that enables the visualization of data from multiple content and data sets to facilitate decision making related to opportunities analysis, asset acquisition, and intellectual property licensing.

Methods and systems for business development and licensing and competitive intelligence

A multi-component software system facility matches unpublished academic manuscripts with a list or set of recommended potential 'best fit' publications, e.g., journals, e.g., those publications determined most likely to accept the manuscript for publication. Upon selecting from a set of recommended publications a user may electronically upload or submit or transmit the unpublished article or work or manuscript to a target publication review and editing system. The present invention provides a client or web-based interface to effectively integrate word processor and bibliographic management software and other resources, including third-party authority databases.

Systems, methods, and software for manuscript recommendations and submissions

Systems and techniques for improving the training of machine learning classifiers are disclosed. A classifier is trained using a set of validated documents that are accurately associated with a set of class labels. A subset of non-validated documents is also identified and is used to further train and improve accuracy of the classifier.

Automatic data cleaning for machine learning classifiers

Apparatus, systems, and methods can operate to provide efficient data clustering, data classification, and data compression. A method comprises training set of training instances can be processed to select a subset of size-1 patterns, initialize a weight of each size-1 pattern, include the size-1 patterns in classes in a model associated with the training set, and then include a set of top-k size-2 patterns in a way that provides an effective balance between local, class, and global significance patterns. A method comprises processing a dataset to compute an overall significance value of each size-2 pattern in each instance in the dataset, sort the size-2 patterns, and select the top-k size-2 patterns to be represented in clusters, which can be refined into a clustered hierarchy. A method comprises creating an uncompressed bitmap, reordering the bitmap, and compressing the bitmap. Additional apparatus, systems, and methods are disclosed.

Data classification and hierarchical clustering

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Monmouth Junction, NJ, United States of America

Hassan Malik