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Publication Type : Conference Paper
Thematic Areas : Learning-Technologies
Publisher : Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing, ACM.
Source : Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing, ACM (2014)
Campus : Amritapuri
School : Department of Computer Science and Engineering, School of Engineering
Center : Technologies & Education (AmritaCREATE), Amrita Center For Research in Analytics
Department : Computer Science
Verified : Yes
Year : 2014
Abstract : Information Retrieval (IR) systems such as search engines retrieve a large set of documents, images and videos in response to a user query. Computational methods such as Automatic Text Summarization (ATS) reduce this information load enabling users to find information quickly without reading the original text. The challenges to ATS include both the time complexity and the accuracy of summarization. Our proposed Information Retrieval system consists of three different phases: Retrieval phase, Clustering phase and Summarization phase. In the Clustering phase, we extend the Potential-based Hierarchical Agglomerative (PHA) clustering method to a hybrid PHA-ClusteringGain-K-Means clustering approach. Our studies using the DUC 2002 dataset show an increase in both the efficiency and accuracy of clusters when compared to both the conventional Hierarchical Agglomerative Clustering (HAC) algorithm and PHA.
Cite this Research Publication : G. K. R. Naveen and Prof. Prema Nedungadi, “Query-based Multi-Document Summarization by Clustering of Documents”, in Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing, 2014