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Tuesday, September 04th, 2012 | Author:

One of my PhD students, Mena Badieh Habib, got a paper accepted at the Semantic Web and Information Extraction (SWAIE) workshop at the EKAW conference on improving NEE in twitter.
Unsupervised Improvement of Named Entity Extraction in Short Informal Context Using Disambiguation Clues
Mena Badieh Habib, Maurice van Keulen
Short context messages (like tweets and SMS’s) are a potentially rich source of continuously and instantly updated information. Shortness and informality of such messages are challenges for Natural Language Processing tasks. Most efforts done in this direction rely on machine learning techniques which are expensive in terms of data collection and training.
In this paper we present an unsupervised Semantic Web-driven approach to improve the extraction process by using clues from the disambiguation process. For extraction we used a simple Knowledge-Base matching technique combined with a clustering-based approach for disambiguation. Experimental results on a self-collected set of tweets (as an example of short context messages) show improvement in extraction results when using unsupervised feedback from the disambiguation process.
The paper will be presented at the EKAW workshop co-located with SWAIE 2012, 8-12 October 2012, Galway City, Ireland [details]

Category: Information Extraction, Neogeography  | Tags: ,  | Comments off