Term Association Analysis for Named Entity Filtering
Abstract
This paper describes the participation of the Universities of Helsinki and Caen in the first round of the TREC Knowledge Base Acceleration track3. The task focused on filtering a stream of documents relevant to a set of entities. Our approach uses word co-occurrence graphs for modelling the named entities. We submitted two runs that achieved an average F-measure superior to the mean of all submitted runs. The best of those runs ranked in the top 5 runs for both the central and relevant F-measures, out of a total of 43 runs submitted by 11 institutions. As our runs were the produce of a first implementation of our approach these preliminary results are very supportive of our idea to use concept graphs for modelling named entity relations.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 2012
- Accession Number
- ADA579408
Entities
People
- Antoine Doucet
- Hannu Toivonen
- Oskar Gross
Organizations
- University of Helsinki