Using Wikipedia Anchor Text and Weighted Clustering Coefficient to Enhance the Traditional Multi-Document Summarization

From Wikipedia Quality
Revision as of 12:11, 11 January 2020 by Athena (talk | contribs) (Adding infobox)
Jump to: navigation, search


Using Wikipedia Anchor Text and Weighted Clustering Coefficient to Enhance the Traditional Multi-Document Summarization
Authors
Niraj Kumar
Kannan Srinathan
Vasudeva Varma
Publication date
2012
DOI
10.1007/978-3-642-28601-8_33
Links
Original

Using Wikipedia Anchor Text and Weighted Clustering Coefficient to Enhance the Traditional Multi-Document Summarization - scientific work related to Wikipedia quality published in 2012, written by Niraj Kumar, Kannan Srinathan and Vasudeva Varma.

Overview

Similar to the traditional approach, authors consider the task of summarization as selection of top ranked sentences from ranked sentence-clusters. To achieve this goal, authors rank the sentence clusters by using the importance of words calculated by using page rank algorithm on reverse directed word graph of sentences. Next, to rank the sentences in every cluster authors introduce the use of weighted clustering coefficient. Authors use page rank score of words for calculation of weighted clustering coefficient. Finally the most important issue is the presence of a lot of noisy entries in the text, which downgrades the performance of most of the text mining algorithms. To solve this problem, authors introduce the use of Wikipedia anchor text based phrase mapping scheme. Authors experimental results on DUC-2002 and DUC-2004 dataset show that system performs better than unsupervised systems and better than/comparable with novel supervised systems of this area.