A new method to compute the word relevance in news corpus
|A new method to compute the word relevance in news corpus|
|Author(s)||Jinpan L., Liang H., Xin L., Mingmin X., Wei L.|
|Published in||Proceedings - 2010 2nd International Workshop on Intelligent Systems and Applications, ISA 2010|
|Keyword(s)||Component, News corpus, Term co-occurrence, Wikipedia, Word relatedness (Extra: Co-occurrence, Term co-occurrence, Web Corpora, Wikipedia, Intelligent systems, Security of data)|
|Article||BASE, CiteSeerX, Google Scholar|
|Web||Ask, Bing, Google (PDF), Yahoo!|
|Download and mirrors|
|Local copy||Not available|
|Remote mirror(s)||Not available|
|Export and share|
|BibTeX, CSV, RDF, JSON|
|Browse properties · List of conference papers|
A new method to compute the word relevance in news corpus is a 2010 conference paper written in English by Jinpan L., Liang H., Xin L., Mingmin X., Wei L. and published in Proceedings - 2010 2nd International Workshop on Intelligent Systems and Applications, ISA 2010.
In this paper we propose a new method to compute the relevance of term in news corpus. According to the characteristics of news corpus , we first propose that the news corpus should be divided into different channels, second we make use of the feature of news document , we divide the co-occurrence of terms into two cases, on the one hand the co-occurrence in the title of the news, On the other hand the co-occurrence in the news text, we use different methods to compute the co-occurrence. In the end, we introduce the web corpus Wikipedia to overcome some shortcomings of the news corpus
- This section requires expansion. Please, help!
Probably, this publication is cited by others, but there are no articles available for them in WikiPapers.