Publication Type : Conference Paper
Thematic Areas : Wireless Network and Application
Publisher : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE, Udupi, India.
Source : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE, Udupi, India (2017)
Url : https://ieeexplore.ieee.org/abstract/document/8125917
Keywords : Automatic document summarization, automatic text summarization, Data preprocessing, document context, extractive approach, Graph theory, Hybrid approach, Information Retrieval, learning (artificial intelligence), Machine learning, NAtural language processing, natural language processing tools, Probabilistic logic, scoring system, sentence similarity, Silicon, single document summarization, Speech, text analysis, textual information, Tools, weighted undirected graph.
Campus : Amritapuri
School : Department of Computer Science and Engineering, School of Engineering
Center : Computational Linguistics and Indic Studies, Amrita Center for Wireless Networks and Applications (AmritaWNA)
Department : Computer Science
Year : 2017
Abstract : Automatic text summarization come under the domains of natural language processing, machine learning and information retrieval. As the abundance of textual information grows so does the need for summarising it. Here we consider a method for single document summarization using natural language processing tools and an extractive approach based on sentence similarity and document context. The technique uses a weighted undirected graph based scoring on paragraphs and a word frequency based scoring system on the entire document to obtain summaries. The proposed method is validated through experiments and the results are promising.
Cite this Research Publication : Siji Rani S., Sreejith, K., and Sanker, A., “A hybrid approach for automatic document summarization”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017