User-perceptive image search using complex multiple word based query (An efficient image search process using complex multiple word based query)

Increasingly developed world internet and social multimedia services allow users to view, tag, and comments also upload large amount of data to search the content among this metadata through text based searching is widely preferred by users. To increase the search efficiency of the searchers we enhanced the model of ternary relationship among users, images and tags; to jointly model of tensor factorization, to perform the low-rank approximation. In this paper, we propose a model to considering the user interest, user specified query in user specified topic space and rank the result list the effect of effective personalize tag-based search. This model is tested for complex multiple word based query and it's showing suitable results.