Abstract: 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.

Abstract: 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.

Abstract: A multi-component software system facility matches unpublished academic manuscripts with a list or set of recommended potential “best fit” publications, e.g., journals, e.g., those publications determined most likely to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 Upon selecting from a set of recommended publications a user may electronically upload or submit or transmit the unpublished article or work or manuscript to a target publication review and editing system.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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Systems and techniques are disclosed for representing information included in unstructured text documents into a structured format. The systems and techniques identify events and information associated with the events in unstructured documents, classify the identified events and information, and represent the identified events and information in a structured format based on a computed classification score. The systems and techniques may also assign a confidence score to identified events, compare the confidence score associated with events to a confidence score associated with a trained confidence model, and represent the identified events and information associated with the events in a structured format based on the comparison.

Abstract: 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.

Abstract: 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.

Abstract: 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.