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Paper Details


Pratik Joshi, Imran Pathan, Aamir Khan?

Journal Title:International Journal of Computer Science and Mobile Computing - IJCSMC

Keyword generation for search engine advertising is an important problem for sponsored search or paid placement advertising. A recent strategy in this area is bidding on non-obvious yet relevant words, which are economically more viable. Targeting many such non-obvious words lowers the advertising cost, while delivering the same click volume as expensive words. Generating the right non-obvious yet relevant keywords is a challenging task. The challenge lies in not only finding relevant words, but also in finding many such words. In this paper, we present TermsNet, a novel approach to this problem. This approach leverages search engines to determine relevance between terms and captures their semantic relationships as a directed graph. By observing the neighbours of a term in such a graph, we generate the common as well as the non-obvious keywords related to a term.