The identification of important concepts in highly structured technical papers
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
A trainable document summarizer
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
WordNet: a lexical database for English
Communications of the ACM
Automatic text structuring and summarization
Information Processing and Management: an International Journal - Special issue: methods and tools for the automatic construction of hypertext
The decomposition of human-written summary sentences
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
New Methods in Automatic Extracting
Journal of the ACM (JACM)
Using hidden Markov modeling to decompose human-written summaries
Computational Linguistics - Summarization
Lexical cohesion computed by thesaural relations as an indicator of the structure of text
Computational Linguistics
Identifying topics by position
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Centroid-based summarization of multiple documents
Information Processing and Management: an International Journal
Headline generation based on statistical translation
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Using maximum entropy for sentence extraction
AS '02 Proceedings of the ACL-02 Workshop on Automatic Summarization - Volume 4
Hedge Trimmer: a parse-and-trim approach to headline generation
HLT-NAACL-DUC '03 Proceedings of the HLT-NAACL 03 on Text summarization workshop - Volume 5
The automatic creation of literature abstracts
IBM Journal of Research and Development
Machine-made index for technical literature: an experiment
IBM Journal of Research and Development
Topic-based Bengali opinion summarization
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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This paper describes a system that produces extractive summaries of Bengali news documents. The ultimate objective of produced summaries is defined as helping readers to determine whether they would be interested in reading a particular document. To this end, the summary aims to provide a reader with an idea about the theme of a document without revealing the in-depth detail. The approach presented here has four major steps (1) preprocessing (2) extraction of candidate summary sentences (3) ranking the candidate summary sentences (4) summary generation. The proposed approach defines TF*IDF, position and sentence length feature in more effective way that helps in improving the summarization performance. The experimental results show that the proposed text summarization approach outperforms the lead baseline and a more sophisticated baseline that uses TF*IDF and position features both.