Abstract: The present disclosure is directed towards systems and methods for evaluating and classifying data, which comprises receiving a first signal associated with a set of user defined categories and a second signal associated with a first set of one or more data items to be analyzed. The set of categories are presented on an interface and each of the data items are to be analyzed are presented on a tile overlay on the interface. A first swipe identification signal identifying a first category to apply to a first data item and a second swipe identification signal identifying a second category to apply to a second data item are received. Based upon the swipe identification signals, a first record associating the first data item with the first category and a second record associating the second data item with the second category are generated and stored in a memory.

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 relationships and association significance between entities are disclosed. The systems and techniques automatically identify supply chain relationships between companies based on unstructured text corpora. The system combines Machine Learning models to identify sentences mentioning supply chain between two companies (evidence), and an aggregation layer to take into account the evidence found and assign a confidence score to the relationship between companies.

Abstract: According to some embodiments, systems, methods, computer program code, and means are provided to receive a broadcast request and a message from a first mobile device where the first mobile device is associated with a first user, compare information in the message to information in a preferences database to match the message with at least a first recipient of the message, and to transmit the message to a second mobile device associated with at least the first recipient.

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 relationships and association significance between entities are disclosed. The systems and techniques automatically identify supply chain relationships between companies based on unstructured text corpora. The system combines Machine Learning models to identify sentences mentioning supply chain between two companies (evidence), and an aggregation layer to take into account the evidence found and assign a confidence score to the relationship between companies.

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: The present invention provides a digital communications system for receiving and integrating multiple service communication feeds into an overall composite deliverable by way of an enhanced and interactive user interface. The system receives peer identification and scoring communications signals from multiple services and based on known handshake configurations links peer identification data to dimensions used to generate an integrated peer identification score and list. A graphical user interface allows users to modify the dimension aggregator function to obtain customizable sets of results based on services communications feeds.

Abstract: According to some embodiments, systems, methods, computer program code, and means are provided to receive a broadcast request and a message from a first mobile device where the first mobile device is associated with a first user, compare information in the message to information in a preferences database to match the message with at least a first recipient of the message, and to transmit the message to a second mobile device associated with at least the first recipient.

Abstract: Systems and techniques for determining relationships and association significance between entities are disclosed. The systems and techniques automatically identify supply chain relationships between companies based on unstructured text corpora. The system combines Machine Learning models to identify sentences mentioning supply chain between two companies (evidence), and an aggregation layer to take into account the evidence found and assign a confidence score to the relationship between companies.

Abstract: According to some embodiments, systems, methods, computer program code, and means are provided to receive a broadcast request and a message from a first mobile device where the first mobile device is associated with a first user, compare information in the message to information in a preferences database to match the message with at least a first recipient of the message, and to transmit the message to a second mobile device associated with at least the first recipient.

Abstract: According to some embodiments, systems, methods, apparatus, computer program code and means are provided to encode data in a text message and to send the text message to a mobile device associated with a user.

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: Exemplary embodiments of the present disclosure relate to systems and methods for providing information about a sector and geographic focus of a company and enables user to identify the top product/brands of a company. Trademark records can be leveraged and combined with other sources of data, which can be presented to a user in an integrated graphical user interface, to facilitate combinatorial business intelligence for one or more companies. Analytical data associated with trademark records corresponding to the company included in the search can be generated to provide a ranked list of trademarked names/brands for the company and a combined or integrated view can be generated in a graphical user interface that includes the ranked list of the trademarked names/brands for the company and also includes the recent news or other information related to the trademark names/brands.

Abstract: Systems and techniques for determining relationships and association significance between entities are disclosed. The systems and techniques automatically identify supply chain relationships between companies based on unstructured text corpora. The system combines Machine Learning models to identify sentences mentioning supply chain between two companies (evidence), and an aggregation layer to take into account the evidence found and assign a confidence score to the relationship between companies.

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 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.

Abstract: The disclosure relates to entity disambiguation in an interactive fashion based upon attributes. Once disambiguated, a manner in which to review a future article based upon an initial set of attributes and an additional set of attributes and, when needed, generate a warning flag based upon the review is also described. The warning flag may result in a change in the relationship between the entity and an organization such as a bank that is considering engaging in a business relationship with a candidate client, and that may subsequently abandon that plan, or a bank that had previously extended credit to the entity, and that subsequently may be less inclined as a result of the information retrieved by the present invention. A previously accepted entity may also be flagged for credit or anti-money laundering consideration if and when the applicant's situation (e.g., financial situation, involvement in anti-money laundering) changes.

Abstract: The present disclosure is directed towards systems and methods for evaluating and classifying data, which comprises receiving a first signal associated with a set of user defined categories and a second signal associated with a first set of one or more data items to be analyzed. The set of categories are presented on an interface and each of the data items are to be analyzed are presented on a tile overlay on the interface. A first swipe identification signal identifying a first category to apply to a first data item and a second swipe identification signal identifying a second category to apply to a second data item are received. Based upon the swipe identification signals, a first record associating the first data item with the first category and a second record associating the second data item with the second category are generated and stored in a memory.

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.