43 results about "Data enrichment" patented technology

The present disclosure relates to performing similarity metric analysis and data enrichment using knowledge sources. A data enrichment service can compare an input data set to reference data sets stored in a knowledge source to identify similarly related data. A similarity metric can be calculated corresponding to the semantic similarity of two or more datasets. The similarity metric can be used to identify datasets based on their metadata attributes and data values enabling easier indexing and high performance retrieval of data values. A input data set can labeled with a category based on the data set having the best match with the input data set. The similarity of an input data set with a data set provided by a knowledge source can be used to query a knowledge source to obtain additional information about the data set. The additional information can be used to provide recommendations to the user.

The present disclosure relates generally to a data enrichment service that automatically profiles data sets and provides visualizations of the profiles using a visual-interactive model within a client application (such as a web browser or mobile app). The visual profiling can be refined through end user interaction with the visualization objects and guide exploratory data visualization and discovery. Additionally, data sampling of heterogeneous data streams can be performed during ingestion to extract statistical attributes from multi-columnar data (e.g., standard deviation, median, mode, correlation coefficient, histogram, etc.). Data sampling can continue in real-time as data sources are updated.

A method for knowledge generation from raw medical records uses XML-based specifications. The method includes content extraction, data aggregation and data enrichment. The method operates on various sources of medical data including financial data, clinical documents and medical images.

Data quality enrichment integration and evaluation system that enables the import of data into a database and the turnkey integration with data enrichment entities. The data imported into the database may be validated using validation rules. Data with particular data quality problems may be sent to a particular bucket for to avoid processing or to obtain processing by a particular data quality enrichment entity. A bucket of data may be sent to be enriched by one or more data enrichment entities. The enrichment results may be compared between entities to enable the selection of a data enrichment entity. The enrichment results may also be drilled down into to provide geographic and other plots that show the quality of original data and quality of data enrichment provided by each data enrichment entity. Evaluation of the enrichment results side by side allows for the selection of a data enrichment entity.

The present invention discloses a method, a system and a computer program product for spend data classification using selected taxonomies. The invention provides refresh classification tool and implementation classification tools for spend data classification. The invention further provides a web mining tool for determining unknown terms in spend data to obtain an enriched spend data for classification.

The present disclosure relates generally to a data enrichment service that extracts, repairs, and enriches datasets, resulting in more precise entity resolution and correlation for purposes of subsequent indexing and clustering. As the data enrichment service can include a visual recommendation engine and language for performing large-scale data preparation, repair, and enrichment of heterogeneous datasets. This enables the user to select and see how the recommended enrichments (e.g., transformations and repairs) will affect the user's data and make adjustments as needed. The data enrichment service can receive feedback from users through a user interface and can filter recommendations based on the user feedback.

A data base system is disclosed for storing meta-data about labeled predominantly non-text items in a collection of labeled predominantly non-text items (lpnt items). The system comprises a storage facility (10), a keyword generation facility (20) and a meta-data enrichment facility (30). The storage facility (10) stores respective meta-data for lpnt items (i) within said collection, said meta-data comprising at least one lpnt item classification (gi) and a lpnt item description (Ti), said classification defining classes. The keyword generation facility (20), which generates keyword data for respective classes, comprises a retrieval module for retrieving terms from lpnt item descriptions of lpnt items associated with said classes. The keyword generation facility (20) further comprises a term relevance determining module for assigning a relevance of said terms for said classes, for selecting terms from said retrieved terms on the basis of their assigned relevance and providing these selected terms as candidate keywords. The system further comprises a metadata enrichment facility (30) for adding a subset (Ki) of the provided candidate keywords (K(c)) as keywords to the meta-data of lpnt items of a class.

Aspects of the disclosure relate to cognitive automation-based engine processing to propagate data across multiple systems via a private network to overcome technical system, resource consumption, and architecture limitations. Data to be propagated can be manually input or extracted from a digital file. The data can be parsed by analyzing for correct syntax, normalized into first through sixth normal forms, segmented into packets for efficient data transmission, validated to ensure that the data satisfies defined formats and input criteria, and distributed into a plurality of data stores coupled to the private network, thereby propagating data without repetitive manual entry. The data may also be enriched by, for example, correcting for any errors or linking with other potentially related data. Based on data enrichment, recommendations of additional target(s) for propagation of data can be identified. Reports may also be generated. The cognitive automation may be performed in real-time to expedite processing.

A data enrichment processing apparatus (100) comprises a processing resource (154) arranged to access, when in use, location data (300) having temporal data associated therewith, and to group a part of the location data according to a predetermined criterion. The processing resource (154) is arranged to support an analysis module (268) capable of inferring temporal access information from the part of the location data grouped, the temporal access information being indicative of ability to access physically a point of interest associated with the part of the location data grouped.