Review on “Adaption of Ranking Model for Domain Specific Search”?

Different new vertical domains are coming everyday so running a sophisticated ranking model Is no longer enviable as the domain are different and building a separate model for each domain is also not favorable because there much time required for labeling the data and training the samples. In this paper we are managing the above problem by regularization based algorithm called as ranking adaptation SVM (RA-SVM), the algorithm is used to adapt existing ranking model of sophisticated search engine to new domain. Here performance is still guaranteed and times taken to label the data training the samples are reduced. The algorithms only requires prediction from existing ranking model and do not require internal structure of it. Adapted ranking model concentrate on specific domain to achieve superior results which are relevant to the search, further it reduces the searching cost also as the most appropriate search results are shown.