Abstract: The present invention relates to a computer-based system for identifying supply chain risks and generating supply chain graphs representing an interconnected network of entities. An industrial graph database application is configured to account for direct and indirect (transitive) supplier risk and importance, based on a weighted set of measures: criticality, replaceability, centrality and distance. A graph-based model serves as an interactive and visual supply chain risk and importance explorer. A supply network is induced from textual data by applying text mining techniques to news stories and used to populate the supply chain/graph database.

Abstract: A neural paraphrase generator receives a sequence of tuples comprising a source sequence of words, each tuple comprising word data element and structured tag element representing a linguistic attribute about the word data element. An RNN encoder receives a sequence of vectors representing a source sequence of words, and RNN decoder predicts a probability of a target sequence of words representing a target output sentence based on a recurrent state in the decoder. An input composition component includes a word embedding matrix and a tag embedding matrix, and receives and transforms the input sequence of tuples into a sequence of vectors by 1) mapping word data elements to word embedding matrix to generate word vectors, 2) mapping structured tag elements to tag embedding matrix to generate tag vectors, and 3) concatenating word vectors and tag vectors.

Abstract: A neural paraphrase generator receives a sequence of tuples comprising a source sequence of words, each tuple comprising word data element and structured tag element representing a linguistic attribute about the word data element. An RNN encoder receives a sequence of vectors representing a source sequence of words, and RNN decoder predicts a probability of a target sequence of words representing a target output sentence based on a recurrent state in the decoder. An input composition component includes a word embedding matrix and a tag embedding matrix, and receives and transforms the input sequence of tuples into a sequence of vectors by 1) mapping word data elements to word embedding matrix to generate word vectors, 2) mapping structured tag elements to tag embedding matrix to generate tag vectors, and 3) concatenating word vectors and tag vectors.

Abstract: The present invention relates to a computer-based system for identifying supply chain risks and generating supply chain graphs representing an interconnected network of entities. An industrial graph database application is configured to account for direct and indirect (transitive) supplier risk and importance, based on a weighted set of measures: criticality, replaceability, centrality and distance. A graph-based model serves as an interactive and visual supply chain risk and importance explorer. A supply network is induced from textual data by applying text mining techniques to news stories and used to populate the supply chain/graph database.

Abstract: Exemplary systems for processing a corpus of documents, such as legal contracts or agreements, are disclosed. The systems include a phrase discovery engine which derives statistics and phrase equivalence classes, groups of phrase equivalence classes, and uberphrases (clauses) bounded by phrases. These can be used to determine origins of phrases or clauses within given legal contract or to suggest alternative phrases and clauses.

Abstract: The present invention relates to a computer-based system for generating a risk register relating to a named entity. The system comprises a computing device, a risk database accessible by the computing device and having stored therein a set of risk types based on an induced taxonomy of risk types previously derived at least in part upon operation of a machine learning module, an input adapted to receive a set of source data, the set of source data being in electronic form and representing textual content comprising potential risk phrases, a entity-risk relation classifier adapted to identify and extract entity-risk relations from the set of source data, a risk tagger adapted to identify in the set of source data a set of risk candidates (ri) based on the set of risk types, a entity tagger adapted to identify mentions of entity names (ci) in the set of source data, and a risk register aggregator adapted to generate a first risk register based on the set of tuples associated with a first entity.

Abstract: Systems and methods for utilizing filters to reduce an incoming stream of textual messages to a smaller subset of potentially relevant textual messages, and using trained machine learning models to analyze and classify the content of such textual messages. Analyzed messages that belong to a relevant class as determined by the machine learning model are stored in a database, giving users the ability to determine and analyze trends from the subset of messages, such as adverse side effects caused by pharmaceuticals or the efficacy of pharmaceuticals. Relationships between the side effects caused by different pharmaceuticals can be used to predict potential candidates for drug repositioning.

Abstract: Exemplary systems for processing a corpus of documents, such as legal contracts or agreements, are disclosed. The systems include a phrase discovery engine which derives statistics and phrase equivalence classes, groups of phrase equivalence classes, and uberphrases (clauses) bounded by phrases. These can be used to determine origins of phrases or clauses within given legal contract or to suggest alternative phrases and clauses.

Abstract: Exemplary systems for processing a corpus of documents, such as legal contracts or agreements, are disclosed. The systems include a phrase discovery engine which derives statistics and phrase equivalence classes, groups of phrase equivalence classes, and uberphrases (clauses) bounded by phrases. These can be used to determine origins of phrases or clauses within given legal contract or to suggest alternative phrases and clauses.

Abstract: A computer implemented method for mining risks includes providing a set of risk-indicating patterns on a computing device; querying a corpus using the computing device to identify a set of potential risks by using a risk-identification-algorithm based, at least in part, on the set of risk-indicating patterns associated with the corpus; comparing the set of potential risks with the risk-indicating patterns to obtain a set of prerequisite risks; generating a signal representative of the set of prerequisite risks; storing the signal representative of the set of prerequisite risks in an electronic memory; and aggregating potential risks linked to an entity to an entity risk profile (ERP). A computing device or system for mining risks includes an electronic memory; and a risk-identification-algorithm based, at least in part, on the set of risk-indicating patterns associated with a corpus stored in the electronic memory.

Abstract: A computer implemented method for mining risks includes providing a set of risk-indicating patterns on a computing device; querying a corpus using the computing device to identify a set of potential risks by using a risk-identification-algorithm based, at least in part, on the set of risk-indicating patterns associated with the corpus; comparing the set of potential risks with the risk-indicating patterns to obtain a set of prerequisite risks; generating a signal representative of the set of prerequisite risks; storing the signal representative of the set of prerequisite risks in an electronic memory; aggregating potential risks linked to an entity to an entity risk profile (ERP); and predicting a movement in a security associated with an entity.

Abstract: Exemplary systems for processing a corpus of documents, such as legal contracts or agreements, are disclosed. The systems include a phrase discovery engine which derives statistics and phrase equivalence classes, groups of phrase equivalence classes, and uberphrases (clauses) bounded by phrases. These can be used to determine origins of phrases or clauses within given legal contract or to suggest alternative phrases and clauses.