Search intent discovery by structurization of community QA contents

Abstract

Web search users often suffer from formulating keyword queries although their search intent may be clear. Moreover, it is difficult for search engines to guess search intent from queries only. We propose a new method for discovering search intents and for generating suggested queries of a given input Web search query to address these problems. Precisely, we introduce the process which analyzes and structurizes corresponding Community Question-Answer corpus data: Finding question-answer pairs (QAs) related to a user's query, extracting keywords from QAs related to the user's intent, transforming QAs into a graph, and generating suggested queries using QA graphs. © 2012 Springer-Verlag.