Enhancing retrieval and novelty detection for arabic text using sentence level information pattern

Author

AL-Shdaifat, E. ; Al-Kabi, Mohammed N. ; Al-Shawakfa, Emad ; Wahbeh, A.H.

Author_Institution

Software Eng. Dept., Hashemite Univ., Zarqa, Jordan

fYear

2012

fDate

14-16 May 2012

Firstpage

1

Lastpage

4

Abstract

Novelty detection is already used in many Natural Processing Language (NLP) applications, such as information retrieval systems, Web search engines, text summarization, question answering systems...etc. This study aims to detect novel Arabic sentence level information patterns. The Length Adjusted (LA) model is based on sentence level information patterns is used, which depends on the sentence length. Test results show a significant improvement in the performance of novelty detection for Arabic texts in terms of precision at top ranks.

Keywords

information retrieval; natural language processing; search engines; text analysis; Arabic sentence level information patterns; LA; NLP; Web search engines; arabic text; enhancing retrieval; information retrieval systems; length adjusted model; natural processing language; novelty detection; question answering systems; sentence level information pattern; text summarization; Educational institutions; Event detection; Information filtering; Materials; Redundancy; Research and development; Information retrieval; Novelty detection; information patterns;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer, Information and Telecommunication Systems (CITS), 2012 International Conference on

Conference_Location

Amman

Print_ISBN

978-1-4673-1549-4

Type

conf

DOI

10.1109/CITS.2012.6220389

Filename

6220389