Abstract: Some embodiments are directed to systems for authoring predictive models. An embodiment includes a computer system implementing a development environment for generating predictive models. The predictive model authoring tool is configured to perform a modeling operation based on one or more user inputs provided to interface controls of the predictive model authoring tool, determine a modeling context for the modeling operation, log the one or more user inputs, generate a predictive model based on one or more model parameters defined during the modeling operation, link the predictive model to an asset, such that one or more sets of data received from the asset are provided to the predictive model during execution of the predictive model, cause the predictive model to be executed such that the predictive model receives data from the asset, and provide the modeling context, the one or more user inputs, and the one or more model parameters.

Abstract: According to one embodiment, a method for text analysis is provided. The method includes recognizing a concept. Recognizing a concept includes receiving a stream of text including a plurality of entities, and extracting at least one concept from the plurality of entities. The method also includes disambiguating the at least one extracted concept. Disambiguating the at least one extracted concept includes receiving the at least one extracted concept, and generating at least one disambiguated concept corresponding to the at least one extracted concept.

Abstract: A system and method for searching for and finding data across industrial time-series data is disclosed. A computer system receives a search query from a client system. The computer system accesses a database including a plurality of stored time-series data sets. For each stored time-series data set, the computer system determines whether the stored time-series data set includes one or more sections that match the received search query. In accordance with a determination that two or more of stored time-series data sets include at least one section that matches the received search query, the computer system determines whether the matching sections in each stored time-series data set have overlapping time periods. In accordance with a determination that the matching sections in each time-series data set have overlapping time periods, the computer system identifies a particular event that occurred during the overlapping time periods.

Abstract: Some embodiments are directed to systems for authoring predictive models. An embodiment includes a computer system implementing a development environment for generating predictive models. The predictive model authoring tool is configured to perform a modeling operation based on one or more user inputs provided to interface controls of the predictive model authoring tool, determine a modeling context for the modeling operation, log the one or more user inputs, generate a predictive model based on one or more model parameters defined during the modeling operation, link the predictive model to an asset, such that one or more sets of data received from the asset are provided to the predictive model during execution of the predictive model, cause the predictive model to be executed such that the predictive model receives data from the asset, and provide the modeling context, the one or more user inputs, and the one or more model parameters.

Abstract: According to one embodiment, a method for text analysis is provided. The method includes recognizing a concept. Recognizing a concept includes receiving a stream of text including a plurality of entities, and extracting at least one concept from the plurality of entities. The method also includes disambiguating the at least one extracted concept. Disambiguating the at least one extracted concept includes receiving the at least one extracted concept, and generating at least one disambiguated concept corresponding to the at least one extracted concept.

Abstract: A system for extracting ontological information from a body of text includes an input module configured to receive a verb phrase. The system also includes a parsing module configured to parse one or more sentences from the body of text into parse tree format to generate a set of parsed sentences. The system further includes a named-entity-recognition module configured to identify a subset of parsed sentences from the set of parsed sentences, identify a subset of noun phrases from the subset of parsed sentences, classify a first noun phrase in subset of noun phrases as an entity, and classify a second noun phrase in subset of noun phrases as a property. The system also includes a concept-extraction module configured to identify and output a conceptual relationship between the first entity and the first property based at least partially on grammatical relationship of the first entity and the first property.

Abstract: A system and method for searching for and finding data across industrial time-series data is disclosed. A computer system receives a search query from a client system. The computer system accesses a database including a plurality of stored time-series data sets. For each stored time-series data set, the computer system determines whether the stored time-series data set includes one or more sections that match the received search query. In accordance with a determination that two or more of stored time-series data sets include at least one section that matches the received search query, the computer system determines whether the matching sections in each stored time-series data set have overlapping time periods. In accordance with a determination that the matching sections in each time-series data set have overlapping time periods, the computer system identifies a particular event that occurred during the overlapping time periods.

Abstract: Disclosed and described systems, methods, and apparatus provide facilitate detection, processing, and relevancy analysis of clinical data. An example data event processing system includes a data event processor configured to receive a data event and to trigger, based on receipt of the data event, processing of the data event with respect to a clinical scenario. The example system includes a data relevancy processor configured to process the data event by applying natural language processing and machine learning to the data event based on the clinical scenario and to determine relevancy of the data event with respect to the clinical scenario based on a combination of domain knowledge and user knowledge. The example system includes an interface configured to output the data event and an indication of the relevancy of the data event with respect to the clinical scenario.

Abstract: Systems, methods and computer program products to automate the process of ontology updates in radiology software are provided. In one aspect, the present disclosure analyzes the textual data describing the radiology exams and identifies terms that are not defined in the existing ontology. It then extracts various types of statistical patterns, such as neighboring concepts, from the textual data, and infers which concepts the unrecognized terms belong to. Finally it presents rank-ordered ontology updating suggestions to the user for final confirmation. The system, methods, and computer program products of the present disclosure are an effective way in updating ontologies, requiring the users to have little, or no prior experience in ontology management or understanding of the underlying ontology structure.

Abstract: A system for extracting ontological information from a body of text is disclosed. The system parses one or more sentences from the body of text into parse tree format to generate a set of parsed sentences. The system further performs named-entity-recognition by identifying a subset of parsed sentences from the set of parsed sentences. A subset of noun phrases from the subset of parsed sentences are identified and the noun phrases are examined to classify the noun phrases as an entity or as a property. The system also identifies and outputs a conceptual relationship between the entity and the property based at least partially on grammatical relationship of the entity and the property.

Abstract: The present disclosure relates to the use of both semantic analysis and statistical text mining to process data records, improving the completeness and accuracy of records so processed. By way of example, a data record may be iteratively processed by text mining using seeds derived from a semantic template and by validating the results based on semantic reasoning based on the semantic template.

Abstract: A system for extracting ontological information from a body of text includes an input module configured to receive a verb phrase. The system also includes a parsing module configured to parse one or more sentences from the body of text into parse tree format to generate a set of parsed sentences. The system further includes a named-entity-recognition module configured to identify a subset of parsed sentences from the set of parsed sentences, identify a subset of noun phrases from the subset of parsed sentences, classify a first noun phrase in subset of noun phrases as an entity, and classify a second noun phrase in subset of noun phrases as a property. The system also includes a concept-extraction module configured to identify and output a conceptual relationship between the first entity and the first property based at least partially on grammatical relationship of the first entity and the first property.