International Business Machines Corporation

April L Webster

Daniel Gruhl

Varun Bhagwan

Clemens Drews

Steven R Welch

Neal Ryan Lewis

John T E Timm

Embodiments of the present invention relate to performing entity recognition on a stream while providing ongoing training or supplementation of an entity dictionary. In one embodiment, a method of and computer program product for stream based named entity recognition is provided. A first portion of a textual input is received. A plurality of patterns is applied to the first portion to determine that a predetermined type is present in the first portion. Approval is requested of the presence of the predetermined type. An indication of approval or disapproval of the predetermined type is received. A dictionary is supplemented according to the indication. A second portion of the textual input is received. The plurality of patterns is applied to the second portion.

Stream based named entity recognition

Embodiments of the present invention disclose a method, computer program product, and system for optimizing data analysis. A set of analytics are received and a plurality of subsets of the set of analytics is generated. An optimization goal(s) is defined. The plurality of subsets of analytics are applied to a set of data. The output of applied analytics are recorded on a data storage device by the computer. Performance values of the computer applying the plurality of subsets of analytics are recorded and displayed. An optimal subset of the plurality of subsets of analytics is calculated, using recorded performance values and outputs of the applied plurality of subsets of analytics, being based on the optimization goal. A set of applied analytics are displayed, where the set of applied analytics includes a number of subsets of analytics of the plurality of analytics that meet the criteria of the optimal subset.

Optimal analytic workflow

Embodiments of the present invention disclose a computer system for optimizing data analysis. A set of analytics are received and a plurality of subsets of the set of analytics is generated. An optimization goal(s) is defined. The plurality of subsets of analytics are applied to a set of data. The output of applied analytics are recorded on a data storage device by the computer. Performance values of the computer applying the plurality of subsets of analytics are recorded and displayed. An optimal subset of the plurality of subsets of analytics is calculated, using recorded performance values and outputs of the applied plurality of subsets of analytics, being based on the optimization goal. A set of applied analytics are displayed, where the set of applied analytics includes a number of subsets of analytics of the plurality of analytics that meet the criteria of the optimal subset.

Embodiments of the present invention disclose a computer program product for optimizing data analysis. A set of analytics are received and a plurality of subsets of the set of analytics is generated. An optimization goal(s) is defined. The plurality of subsets of analytics are applied to a set of data. The output of applied analytics are recorded on a data storage device by the computer. Performance values of the computer applying the plurality of subsets of analytics are recorded and displayed. An optimal subset of the plurality of subsets of analytics is calculated, using recorded performance values and outputs of the applied plurality of subsets of analytics, being based on the optimization goal. A set of applied analytics are displayed, where the set of applied analytics includes a number of subsets of analytics of the plurality of analytics that meet the criteria of the optimal subset.

Embodiments of the present invention disclose a method for optimizing data analysis. A set of analytics are received and a plurality of subsets of the set of analytics is generated. An optimization goal(s) is defined. The plurality of subsets of analytics are applied to a set of data. The output of applied analytics are recorded on a data storage device by the computer. Performance values of the computer applying the plurality of subsets of analytics are recorded and displayed. An optimal subset of the plurality of subsets of analytics is calculated, using recorded performance values and outputs of the applied plurality of subsets of analytics, being based on the optimization goal. A set of applied analytics are displayed, where the set of applied analytics includes a number of subsets of analytics of the plurality of analytics that meet the criteria of the optimal subset.

A race condition in a workflow representation is detected and corrected. First and second contracts are retrieved for respective first and second analytics of the workflow representation, wherein the contracts specify input types and output types of their analytics. Both contracts include information required to execute their respective analytics by a workflow executor. It is determined that the output type of the first analytic matches the input type of the second analytic based on a comparison of the first contract and the second contract, and that the workflow representation does not include a directed edge connecting the first analytic to the second analytic. The inclusion of a directed edge in the workflow representation connecting the first analytic to the second analytic will correct the race condition in the workflow representation.

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Mountain View, CA, United States of America

April L Webster