Abstract: A method and system for analyzing a corpus of data artifacts is disclosed. The method comprises obtaining, by a computer, a semantic representation of the data artifacts, where the semantic representation indicates (1) entities identified in the data artifacts, and (2) semantic relationships among the entities as indicated by the data artifacts. The method further comprises clustering the data artifacts into clusters of semantically related data artifacts based on the semantic representation and inferring additional semantic relationships between pairs of the entities. The inferring comprises applying, on a cluster-by-cluster basis, a multi-tiered network of inference engines to a portion of the semantic representation corresponding to the cluster, where the multi-tiered network of inference engines includes a domain-independent inference tier and a domain-specific inference tier.

Abstract: Methods, systems and computer program products are provided to determine an individual's risk of being targeted by a cyberattack based on quantifying their online presence. In some embodiments, online information pertaining to an individual, accessible through the clear web (e.g., Internet) or the dark web, is identified and used to calculate a digital vulnerability (DV) score. The DV score is used to determine the susceptibility of an individual of being targeted for a cyberattack or cybercrime based upon their online presence, and may be computed based upon personally identifying information (PII) features present on clear web and deep/dark web resources.

Abstract: Computer implemented methods and systems directed to a technological improvement in electronic data compression and transmission between two computer systems using semantic analysis are disclosed. The method includes the step of compressing, at a first computer, a plurality of queued artifacts based on one or more network decision variables. The compression includes prioritizing the queued artifacts. The compression further includes determining a first set of artifacts in a set of queued artifacts to transmit and a second set of artifacts in a set of queued artifacts to only send links. The compression further includes replacing unnecessary content in the set of queued artifacts with one or more identifiers. The method further includes the step of transmitting, from the first computer, one or more batches of the compressed data over a network to a second computer.

Abstract: A method and system for analyzing a corpus of data artifacts is disclosed. The method comprises obtaining, by a computer, a semantic representation of the data artifacts, where the semantic representation indicates (1) entities identified in the data artifacts, and (2) semantic relationships among the entities as indicated by the data artifacts. The method further comprises clustering the data artifacts into clusters of semantically related data artifacts based on the semantic representation and inferring additional semantic relationships between pairs of the entities. The inferring comprises applying, on a cluster-by-cluster basis, a multi-tiered network of inference engines to a portion of the semantic representation corresponding to the cluster, where the multi-tiered network of inference engines includes a domain-independent inference tier and a domain-specific inference tier.

Abstract: A method and system for harmonizing and mediating ontologies to search across large data sources is disclosed. The method comprises receiving a query targeting a first ontology. The method further comprises translating the query into one or more translated queries, each translated query targeting a respective ontology different from the first ontology. For each of the queries, issuing the query to a respective database organized according to the respective ontology of the query, and receiving a respective result set for the query, wherein the respective result set corresponds to the respective ontology of the query. The method further comprises translating the respective result set into a translated result set corresponding to the first ontology, aggregating the result sets into an aggregated result set corresponding to the first ontology, and returning the aggregated results set corresponding to the first ontology.

Abstract: Methods and systems for searching over large (i.e., Internet scale) data to discover relevant information artifacts based on similar content and/or relationships are disclosed. Improvements over simple keyword and phrase based searching over internet scale data are shown. Search engines providing accurate and contextually relevant search results are disclosed. Users are enabled to identify related documents and information artifacts and quickly, ascertain, via visualization, which of these documents are original, which are derived (or copied) from a source document or information artifact, and which subset is independently generated (i.e., an original document or information artifact).

Abstract: A method and system for harmonizing and mediating ontologies to search across large data sources is disclosed. The method comprises receiving a query targeting a first ontology. The method further comprises translating the query into one or more translated queries, each translated query targeting a respective ontology different from the first ontology. For each of the queries, issuing the query to a respective database organized according to the respective ontology of the query, and receiving a respective result set for the query, wherein the respective result set corresponds to the respective ontology of the query. The method further comprises translating the respective result set into a translated result set corresponding to the first ontology, aggregating the result sets into an aggregated result set corresponding to the first ontology, and returning the aggregated results set corresponding to the first ontology.

Abstract: A method and system for analyzing a corpus of data artifacts is disclosed. The method comprises obtaining, by a computer, a semantic representation of the data artifacts, where the semantic representation indicates (1) entities identified in the data artifacts, and (2) semantic relationships among the entities as indicated by the data artifacts. The method further comprises clustering the data artifacts into clusters of semantically related data artifacts based on the semantic representation and inferring additional semantic relationships between pairs of the entities. The inferring comprises applying, on a cluster-by-cluster basis, a multi-tiered network of inference engines to a portion of the semantic representation corresponding to the cluster, where the multi-tiered network of inference engines includes a domain-independent inference tier and a domain-specific inference tier.

Abstract: A method and system for analyzing a corpus of data artifacts is disclosed. The method comprises obtaining, by a computer, a semantic representation of the data artifacts, where the semantic representation indicates (1) entities identified in the data artifacts, and (2) semantic relationships among the entities as indicated by the data artifacts. The method further comprises clustering the data artifacts into clusters of semantically related data artifacts based on the semantic representation and inferring additional semantic relationships between pairs of the entities. The inferring comprises applying, on a cluster-by-cluster basis, a multi-tiered network of inference engines to a portion of the semantic representation corresponding to the cluster, where the multi-tiered network of inference engines includes a domain-independent inference tier and a domain-specific inference tier.

Abstract: Methods and systems for searching over a large corpus of data to discover relevant information artifacts based on similar content and/or relationships are disclosed. Improvements over simple keyword and phrase based searching over Internet scale data are shown. A search query may be modified or relaxed based on the search terms and a contextual relationship therebetween. The search results may be ranked based on both a data ranking corresponding to the data entries in the corpus and a query ranking corresponding to the search query and/or the modified or relaxed search query. In this manner, the accuracy and relevance of the search results is improved.

Abstract: Methods and systems for searching over large (i.e., Internet scale) data to discover relevant information artifacts based on similar content and/or relationships are disclosed. Improvements over simple keyword and phrase based searching over internet scale data are shown. Search engines providing accurate and contextually relevant search results are disclosed. Users are enabled to identify related documents and information artifacts and quickly, ascertain, via visualization, which of these documents are original, which are derived (or copied) from a source document or information artifact, and which subset is independently generated (i.e., an original document or information artifact).

Abstract: Methods and systems for searching over large (i.e., Internet scale) data to discover relevant information artifacts based on similar content and/or relationships are disclosed. Improvements over simple keyword and phrase based searching over internet scale data are shown. Search engines providing accurate and contextually relevant search results are disclosed. Users are enabled to identify related documents and information artifacts and quickly, ascertain, via visualization, which of these documents are original, which are derived (or copied) from a source document or information artifact, and which subset is independently generated (i.e., an original document or information artifact).

Abstract: Methods and systems for searching over large (i.e., Internet scale) data to discover relevant information artifacts based on similar content and/or relationships are disclosed. Improvements over simple keyword and phrase based searching over internet scale data are shown. Search engines providing accurate and contextually relevant search results are disclosed. Users are enabled to identify related documents and information artifacts and quickly, ascertain, via visualization, which of these documents are original, which are derived (or copied) from a source document or information artifact, and which subset is independently generated (i.e., an original document or information artifact).