Paper Details

Keyword query empowers ordinary users to search large data. But the ambiguity of keyword query makes itdifficult to effectively answer keyword queries, especially if the query is short and vague. To solve this challengingproblem, we propose an approach that automatically diversifies XML keyword search based on its different contexts inthe XML data. When a short and vague keyword query is provided and XML data to be searched, we first derive keywordsearch candidates of the query by a simple feature selection model. Then, we design an effective XML keyword searchdiversification model to measure the quality of each candidate. After that, two efficient algorithms are used toincrementally compute top-k qualified query candidates as the diversified search intentions. Two selection criteria aretargeted: the k selected query candidates are most relevant to the given query and they have to cover maximal number ofdistinct results. At last, a comparative analysis of the existing system and proposed system demonstrates the effectivenessand efficiency of our algorithms and diversification model.

Kirti Agarwal, Mihir Joshi, Shreenivas Latad, “Keyword query search using context based diversification in xml data with performance analysis”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 3, Issue 13, pp. -, January 2016.