SVM Based Ranking Model for Dynamic Adaption to Business Domains

Journal Title: INTERNATIONAL JOURNAL OF COMPUTER TRENDS & TECHNOLOGY - Year 2014, Vol 8, Issue 2

Abstract

Huge information can be obtained from vertical search domains. Often the information is very large in such a way that users need to browse further to get the required piece of information. In this context ranking plays an important role. When ranking is required for every domain, it is tedious task to develop ranking algorithms for every domain explicitly. Therefore it is the need of the hour to have a ranking model that can adapt to various domains implicitly. Recently Geng et al. proposed an algorithm that has a ranking model which can adapt to various domains. This avoids the process of writing various algorithms for different domains. In this paper we built a prototype application that implements the algorithm to provide ranking to the search results of various domains. The experimental results reveal that the algorithm is effective and can be used in the real world applications.

Authors and Affiliations

Sandeep Reddy Daida , G. Manoj Kumar

Keywords

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  • EP ID EP88486
  • DOI -
  • Views 168
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How To Cite

Sandeep Reddy Daida, G. Manoj Kumar (2014). SVM Based Ranking Model for Dynamic Adaption to Business Domains. INTERNATIONAL JOURNAL OF COMPUTER TRENDS & TECHNOLOGY, 8(2), 79-84. https://europub.co.uk/articles/-A-88486