文章基本信息

标题：Learning Ranking Model Adaption in the vector of the Domain- Specific Search
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作者：Deepakkishore Bokam ; R.Sailaja
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2015
卷号：21
期号：3
页码：1116-120
出版社：Seventh Sense Research Group
摘要：Technology and its significance always takes mile stone base for achievement of the goal, but if we consider the approach of the usual methodology involved in the traditional software design, it’s really an amazing and strong base to next level of concept. In this paper we consider the concept of the vertical domain and the mess up for the same in order to search keyword of Meta tag of Meta description. In the model of the domain culture, vertical domain culture provides service to the utmost best level. In this paper, we implemented the concept of the vector model of domain adoption and learning ranking methodology to give the best to the user of the domain and its related, in order to resolve the cross domain issue. In the security mechanism where the ranking is important we have implemented the key word with unique key and map paring of Hadoop big data analytics. In the context it gives the effectiveness, time forward and the most robust and best of the all classical ranking methodology.
关键词：Information retrieval; support vector machines; learning to rank; domain adaptation.