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  • 标题:Semantic Web Improved with the Weighted IDF Feature
  • 本地全文:下载
  • 作者:Mrs. Jyoti Gautam ; Dr. Ela Kumar
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2015
  • 卷号:6
  • 期号:2
  • DOI:10.14569/IJACSA.2015.060224
  • 出版社:Science and Information Society (SAI)
  • 摘要:The development of search engines is taking at a very fast rate. A lot of algorithms have been tried and tested. But, still the people are not getting precise results. Social networking sites are developing at tremendous rate and their growth has given birth to the new interesting problems. The social networking sites use semantic data to enhance the results. This provides us with a new perspective on how to improve the quality of information retrieval. As we are aware, many techniques of text classification are based on TFIDF algorithm. Term weighting has a significant role in classifying a text document. In this paper, firstly, we are extending the queries by “keyword+tags” instead of keywords only. In addition to this, secondly, we have developed a new ranking algorithm (JEKS algorithm) based on semantic tags from user feedback that uses CiteUlike data. The algorithm enhances the already existing semantic web by using the weighted IDF feature of the TFIDF algorithm. The suggested algorithm provides a better ranking than Google and can be viewed as a semantic web service in the domain of academics.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; Text classification; Semantic Web with weighted idf feature; Expanded query; New Semantic Web Algorithm; Ranking Algorithm
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