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Keyword search is the most popular querying technique on semistructured data.Keyword queries are simple and con- venient. However, as a consequence of theirimprecision, the quality of their answers is poor and the existing algorithmsdo not scale satisfactorily.  In this paper, we introduce the novel concept of cohesive keyword queries fortree data. Intuitively, a cohesiveness relationship on keywords indicates thatthey should form a cohesive whole in a query result. Cohesive keyword queriesallow term nesting and keyword repetition. Although more expressive, they areas simple as flat keyword queries. We provide formal semantics for cohesivekeyword queries rank- ing query results on the proximity of the keywordinstances. We design a stack based algorithm which efficiently evaluatescohesive keyword queries. Our experiments demonstrate that our approachoutperforms in quality previous filtering semantics and our algorithm scalessmoothly on queries of even 20 keywords on large datasets.

Cohesiveness Relationships to Empower Keyword Search on Tree Data on the Web