Abstract:Term suggestions recommend query terms to a user based on his initial query. Suggesting adequate terms is a challenging issue. Most existing commercial search engines suggest search terms based on the frequency of prior used terms that match the leading alphabets the user types. In this article, we present a novel mechanism to construct semantic term-relation graphs to suggest relevant search terms in the semantic level. We built term-relation graphs based on multipartite networks of existing social media, esp… Show more
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