Multi-resolution disambiguation of term occurrences

Authors:
Einat Amitay;Rani Nelken;Wayne Niblack;Ron Sivan;Aya Soffer
Affiliations:
IBM Haifa Research Lab, Mount Carmel, Haifa, Israel;IBM Haifa Research Lab, Mount Carmel, Haifa, Israel;IBM Almaden Research Center;IBM Haifa Research Lab, Mount Carmel, Haifa, Israel;IBM Haifa Research Lab, Mount Carmel, Haifa, Israel
Venue:
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Year:
2003

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Abstract

We describe a system for extracting mentions of terms such as company and product names, in a large and noisy corpus of documents, such as the World Wide Web. Since natural language terms are highly ambiguous, a significant challenge in this task is disambiguating which occurrences of each term are truly related to the right meaning, and which are not. We describe our approach for disambiguation, and show that it achieves very high accuracy with only limited training. This serves as a necessary first step for applications that strive to do analytics on term mentions.