Identifying temporal relations between main events in new articles

Author

Berrazega, Ines ; Faiz, Rim

Author_Institution

LARODEC, Univ. of Tunis - ISG, Tunis, Tunisia

fYear

2013

fDate

27-30 May 2013

Firstpage

1

Lastpage

4

Abstract

With the expansion of the Web 2.0, daily huge amount of data is produced everywhere, namely new articles. These contents need to be exploited in order to extract relevant information and to build knowledge databases. In this concern, processing the temporal dimension of language and extracting temporal information from electronic news articles is becoming a prominent task. In this concern, we propose an approach for identifying inter-sentential temporal relations between main events from news articles. Our approach is based on a complete linguistic analysis of texts and supervised learning models.

Keywords

Internet; information retrieval; Web 2.0; electronic news articles; intersentential temporal relation identification; knowledge databases; linguistic text analysis; supervised learning models; temporal information extraction; temporal language dimension; Accuracy; Data mining; Feature extraction; Natural language processing; Pragmatics; Semantics; Syntactics; Classification; Linguistic Analysis; Machine Learning; Natural Language Processing; Temporal Information Extraction; Temporal Relation Identification; Web 2.0;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Systems and Applications (AICCSA), 2013 ACS International Conference on

Conference_Location

Ifrane

ISSN

2161-5322

Type

conf

DOI

10.1109/AICCSA.2013.6616467

Filename

6616467