doi: 10.7763/IJET.2011.V3.261
Improved Algorithms for Document Classification &Query-based Multi-Document Summarization
Suzanne D’Silva
1
,
Neha Joshi
1
,
Sudha Rao
1
,
Sangeetha Venkatraman
2
,
Seema Shrawne
1
- 1 the Veermata Jijabai Technological Institute, Matunga, Mumbai – 400019, India
- 2 the Veermata Jijabai Technological Institute, Matunga, Mumbai, India
Abstract
With an excess of information in recent times, sound information retrieval is the need of the hour. Document Classification, where a document is classified as being under one of a number of predefined categories, is the foundation of an efficient and effective Information Retrieval system. Once information has been retrieved, the next step is unearthing the relevant and essential information. Query-based Multi- Document Summarization will do just that. In this paper, we analyze the different variants of the k Nearest Neighbors (kNN) Classification Algorithm and from them design the CAST Algorithm for Classification, which, as precision and recall results will show, performs better in most cases. For document summarization, we analyze and improvise on a Hyper graph based algorithm. Further, we design and describe the CAST Algorithm for Summarization and show that it performs well for Query-based Multi-Document Summarization.
Keywords
- Document Classification
- Multi-Document Summarization
- Query-based summary
How to Cite
Suzanne D’Silva, Neha Joshi, Sudha Rao, Sangeetha Venkatraman, and Seema Shrawne, "Improved Algorithms for Document Classification &Query-based Multi-Document Summarization," International Journal of Engineering and Technology, vol. 3, no. 4, pp. 404-409, 2011. https://doi.org/ 10.7763/IJET.2011.V3.261
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).