Abstract: Concepts may be associated with each other based on information provided by data sources. Entities may be associated based on the information provided by the data sources and characteristics of the entities. A concept graph may be generated based on the concepts such that each edge in the concept graph corresponds to a relationship between two or more associated concepts. A data graph may be generated based on the concept graph and the entities such that each node in the data graph corresponds to a concept or an entity and the edges in the data graph correspond to relationships between two or more concepts and such that other relationships between two or more associated concepts are absent from the concept graph. In response to a query, traversing the data graph to determine entities that are related to the query and providing a report that includes those entities.

Abstract: Embodiments are directed to managing data using network computers. A data graph may be provided based on knowledge graphs and information provided by data sources. Concepts and entities may be provided based on the data graph. Scoring models may be determined based on the concepts and the entities. Thematic scores for the entities may be generated based on the scoring models and the data graph such that the thematic scores include values that quantify each relationship between the concepts and the entities and such that an entity with a higher thematic score value for a concept has a relationship strength value that exceeds another relationship strength value for another entity with a lower thematic score value for the concept. A report that includes the thematic scores, the entities, and the concepts may be provided.

Abstract: Concepts may be associated with each other based on information provided by data sources. Entities may be associated based on the information provided by the data sources and characteristics of the entities. A concept graph may be generated based on the concepts such that each edge in the concept graph corresponds to a relationship between two or more associated concepts. A data graph may be generated based on the concept graph and the entities such that each node in the data graph corresponds to a concept or an entity and the edges in the data graph correspond to relationships between two or more concepts and such that other relationships between two or more associated concepts are absent from the concept graph. In response to a query, traversing the data graph to determine entities that are related to the query and providing a report that includes those entities.

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: Embodiments are directed towards managing data. A data engine provides a data model that may include a plurality of concepts and a plurality of relations between the concepts. The data engine associates a propagation weight with each relation based on characteristics of the concepts. A feature engine associates an initial impetus value with a pivot concept. The feature engine employs the pivot concept as a start point to recursively traverse the data model. The feature engine allocates a portion of the impetus value to concepts that may be on a direct path of the traversal based on the propagation weight associated with each relation of the concepts. The feature engine may identify feature concepts based on a value of a portion of the impetus value that exceeds a threshold.

Abstract: A data model is traversed to determine concept characteristics associated with concepts that may be associated with entities. Associated documents may be evaluated to identify document characteristics associated with the entities. Entity models may be trained based on the concept characteristics and the document characteristics with each entity model being associated with a confidence value. Results for one or more queries based on the documents and the entity models may be provided. The results may reference the documents that may be associated with the entities. Some entity models may produce results that have a confidence value below a threshold value. Accordingly, the entity models that provide low confidence results may be re-trained.

Abstract: Systems and methods (e.g., utilities) for use in providing automated, lightweight collection of online, open source data which may be content-based to reduce website source bias. In one aspect, a utility is disclosed for use in extracting content of interest from at least one website or other online data source (e.g., where the extracted content can be used in a subsequent search query). In other aspects, utilities are disclosed that are operable to perform various types of analyzes on such extracted content and present graphical representations of such analyzes on a display of a client device.

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: Examples relate to systems for authoring and executing predictive models. A computer system includes a model development context analyzer configured to store a set of derived modeling knowledge generated at least in part from a plurality of modeling operations performed using at least a first predictive model authoring tool. The system is configured to, receive a modeling context indicating at least a modeling operation being performed, determine, from the modeling context, at least one element of an ontology, the ontology defining at least one attribute of a plurality of modeling operations, query the set of derived modeling knowledge using the at least one element of the ontology to identify at least one record of the set of derived modeling knowledge associated with the at least one element of the ontology, identify at least one suggested model parameter associated with the modeling context, and provide the at least one suggested model parameter.

Abstract: Examples relate to systems for authoring and executing predictive models. A computer system includes a model development context analyzer configured to store a set of derived modeling knowledge generated at least in part from a plurality of modeling operations performed using at least a first predictive model authoring tool. The system is configured to, receive a modeling context indicating at least a modeling operation being performed, determine, from the modeling context, at least one element of an ontology, the ontology defining at least one attribute of a plurality of modeling operations, query the set of derived modeling knowledge using the at least one element of the ontology to identify at least one record of the set of derived modeling knowledge associated with the at least one element of the ontology, identify at least one suggested model parameter associated with the modeling context, and provide the at least one suggested model parameter.

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: 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: Systems and methods (e.g., utilities) for use in providing automated, lightweight collection of online, open source data which may be content-based to reduce website source bias. In one aspect, a utility is disclosed for use in extracting content of interest from at least one website or other online data source (e.g., where the extracted content can be used in a subsequent search query). In other aspects, utilities are disclosed that are operable to perform various types of analyzes on such extracted content and present graphical representations of such analyzes on a display of a client device.

Abstract: Embodiments allow blocking and featurization of time-series data gathered from at least one sensor. The input time-series data is divided into blocks with common attributes (features) according to feature models that describe patterns in the data. The blocks may be overlapping or non-overlapping. The resultant feature blocks are annotated with feature information and semantic meaning. The feature blocks can be indexed to facilitate semantic search of the data. Feature blocks may be further analyzed to create semantic blocks that incorporate semantic meaning and features for multiple feature blocks, sensors and/or related time-series data. The semantic blocks can also be indexed to facilitate semantic search of the data.

Abstract: One website mining embodiment is for characterizing first time users of a website, collecting user session data of the users visiting the website and identifying first time visitors, determining features of the first time visitors utilizing the user session data, determining rules utilizing the features of the first time visitors, monitoring actions of the first time visitors on the website, updating the rules utilizing the monitored actions of the first time visitors and recommending web content utilizing the rules to the first time visitor.

Abstract: A method for intent mining is provided. The method includes performing a preliminary search of a constrained source using one or more seed phrases to generate multiple preliminary search results representing different ways of expressing a desired intent. The method also includes identifying each of the plurality of preliminary search results that have expressed the desired intent to generate a plurality of intent results. The method also includes producing multiple action search strings around one or more action verbs in each of the multiple intent results. The method further includes applying each of the multiple action search strings on one or more non-constrained sources to generate multiple action search results.

Abstract: According to some embodiments, an influencer analyzer platform may access a document database storing documents associated with various social and traditional media sources, each document being associated with an author. A first influencer score may be calculated for a selected author based on a first algorithm and the documents in the document database. Similarly, a second influencer score may be calculated for the selected author based on a second algorithm, different than the first algorithm, and the documents in the document database. An overall influencer score may then be calculated based on the first influencer score adjusted by a first weighing value and the second influencer score adjusted by a second weighing value.

Abstract: A method for recommending videos is presented. The method includes generating a cross-usage matrix based upon a data of video sessions for a plurality of videos, generating a temporal matrix based upon release dates of the plurality of videos, generating a cross-temporal matrix based upon the cross-usage matrix and the temporal matrix, computing a global video rank corresponding to each of the plurality of videos based upon the cross-temporal matrix, generating a similarity score corresponding to each pair of videos in the plurality of videos based upon meta-data of the plurality of videos, and generating a local video rank corresponding to each of the plurality of videos relative to another video in the plurality of videos based upon the generated cross-usage matrix, the computed global video rank and the generated similarity score.

Abstract: Systems and methods (e.g., utilities) for use in providing automated, lightweight collection of online, open source data which may be content-based to reduce website source bias. In one aspect, a utility is disclosed for use in extracting content of interest from at least one website or other online data source (e.g., where the extracted content can be used in a subsequent search query). In other aspects, utilities are disclosed that are operable to perform various types of analyses on such extracted content and present graphical representations of such analyses on a display of a client device.

Abstract: Systems and methods (e.g., utilities) for use in providing automated, lightweight collection of online, open source data which may be content-based to reduce website source bias. In one aspect, a utility is disclosed for use in extracting content of interest from at least one website or other online data source (e.g., where the extracted content can be used in a subsequent search query). In other aspects, utilities are disclosed that are operable to perform various types of analyzes on such extracted content and present graphical representations of such analyzes on a display of a client device.