INFORMATION MATCHING APPARATUS, METHOD OF MATCHING INFORMATION, AND COMPUTER READABLE STORAGE MEDIUM HAVING STORED INFORMATION MATCHING PROGRAM

摘要

The information matching apparatus includes: a training data setting unit that sets supervised data in a machine learning device of supervised learning that learns judgment criteria used for a judgment of identicalness, similarity, and relevance between a plurality of records by matching the records configured by sets of values corresponding to items; a check point setting unit that sets a check point configured by one set of two records used for evaluating the set supervised data; and a learning result evaluation unit, for the set check point, acquires a change between a judgment result using judgment criteria derived as a result of learning based on set first supervised data and a judgment result using judgment criteria derived as a result of learning based on set second supervised data set and evaluates the supervised data based on the acquired change.

主权项

1. An information matching apparatus comprising:
a processor; and a memory, wherein the processor executes: first acquiring a first judgment criteria and a second judgment criteria utilizing a first training data and a second training data, respectively, the first judgment criteria and the second judgment criteria being generated by a machine learning device that learns judgment criteria for name-based aggregation between a plurality of data sets, each of the plurality of data sets including a plurality of records; selecting a plurality of check points, each of the plurality of check points being a pair of two records in different data sets and having a specific result for the name-based aggregation, specific results of the plurality of check points being known in advance, respectively; second acquiring judgment differences between a first judgment result by the first judgment criteria and a second judgment result by the second judgment criteria, for the name-based aggregation judgment to the plurality of check points; and evaluating the second training data based on the judgment differences and an evaluation of the second training data.