PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

ADVANCING TOPIC ONTOLOGY LEARNING THROUGH TERM EXTRACTION
Blaz Fortuna, Nada Lavrac and Paola Velardi
In: IS 2007, 8-12 October 2007, Ljubljana, Slovenia.

Abstract

This paper presents a novel methodology for topic ontology learning from text documents. The proposed methodology, named OntoTermExtraction is based on OntoGen, a semi-automated tool for topic ontology construction, upgraded by using and an advanced terminology extraction tool in an iterative, semi-automated ontology construction process. This process consists of (a) document clustering to find the nodes in the topic ontology, (b) term extraction from document clusters, (c) populating the term vocabulary and keyword extraction, and (d) choosing the concept names by comparing the best ranked terms with the extracted keywords. The approach is illustrated on a case study analysis of the ILPNet2 publications data

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
Information Retrieval & Textual Information Access
ID Code:3758
Deposited By:Dunja Mladenić
Deposited On:16 February 2008