Title :
Parsumist: A Persian text summarizer
Author :
Shamsfard, Mehrnoush ; Akhavan, Tara ; Jourabchi, Mona Erfani
Author_Institution :
Comput. Eng. Dept., Shahid Behehti Univ., Tehran, Iran
Abstract :
The rapid growth of online information services causes the problem of information explosion. Automatic text summarization techniques are essential for dealing with this problem. The process of compacting a source document to reduce complexity and length, retaining the most important information is called text summarization. This paper introduces PARSUMIST; a text summarization system for Persian documents. It can generate generic or topic/query-driven extract summaries for single or multiple Persian documents, using a combination of statistical, semantic and heuristic improved methods. In this paper we will first review the related works in this field and especially in Persian text summarization. Then we will present the architecture of PARSUMIST, its components and its features. The last section will evaluate the system and compare it to other existing ones.
Keywords :
natural language processing; text analysis; PARSUMIST; Persian document; Persian text summarizer; automatic text summarization; information explosion; Broadcasting; Communication industry; Computer architecture; Data mining; Explosions; Frequency; Intelligent systems; Machine learning; Mining industry; Text mining; Automatic text summarization; Persian; extraction; lexical chains; multi document summarization;
Conference_Titel :
Natural Language Processing and Knowledge Engineering, 2009. NLP-KE 2009. International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-4538-7
Electronic_ISBN :
978-1-4244-4540-0
DOI :
10.1109/NLPKE.2009.5313844