Home // CONTENT 2019, The Eleventh International Conference on Creative Content Technologies // View article
Authors:
Iana Atanassova
Gan Jin
Ibrahim Soumana
Peter Greenfield
Sylviane Cardey
Keywords: Web content; Information Extraction; Competitive Intelligence; Sentence Classification; Semantic Annotation; Linguistic Model
Abstract:
In a competitive environment and in the current context of rapid technological advances, competitive intelligence is a key strategic need in the private sector and requires the development of Web content tools capable of robust and semantically-driven text classification. In this paper, we present a method for the information extraction and semantic classification of text segments. Our approach to text processing makes use of linguistic clues to populate an ontology of competitive intelligence. We have developed a method for the automatic identification and classification of sentences into predefined semantic classes by using linguistic models and a knowledge-based approach. This method has been tested on a dataset of journal articles in horology and aeronautics, and can be extended to other domains. The tool that we have developed is part of the WebSO+ platform for competitive intelligence. We present the overall methodology for annotation and information extraction, our experimental protocol and the results obtained from the evaluation.
Pages: 32 to 37
Copyright: Copyright (c) IARIA, 2019
Publication date: May 5, 2019
Published in: conference
ISSN: 2308-4162
ISBN: 978-1-61208-707-8
Location: Venice, Italy
Dates: from May 5, 2019 to May 9, 2019