International Business Machines Corporation

Bogdan Alexe

Shivakumar Vaithyanathan

Yunyao Li

Lucian Popa

Ioana Roxana Stanoi

Rajasekar Krishnamurthy

Hima Prasad Karanam

Mauricio Antonio Hernandez-Sherrington

Douglas Ronald Burdick

Tyler Shore Baldwin

Described herein are methods, systems and computer program products for entity resolution. Entity resolution, also known as entity matching or record linkage, seeks to identify equivalent data objects between or among datasets. An example method includes creating a deterministic model by defining an entity to be resolved, selecting two datasets for comparison, defining matching predicates for attributes of the datasets to select a set of candidate matches, and defining a precedence rule for the candidate matches to select a subset of the candidate matches. The method includes running the deterministic model on the two datasets. Running the deterministic model includes applying the matching predicates and the precedence rule to data in the datasets that correspond to the attributes. The method also includes applying a cardinality rule to results of the running, and outputting the matching candidates for which the cardinality rule is satisfied.

Entity resolution between datasets

Embodiments of the invention relate to ambiguity detection. In one embodiment, an object and a topical domain associated with the object are obtained. In this embodiment, the object includes at least one term. At least one of a plurality of information sources is analyzed based on the at least one term and the topical domain. A determination is made that object is one of ambiguous and unambiguous based on analyzing at least one of the plurality of information sources.

Knowledge-rich automatic term disambiguation

Growing community of inventors

San Jose, CA, United States of America

Bogdan Alexe