XIOTR :A Terse Ranking of XIO for XML Keyword Search

Abstract

The emergence of the Web has increased interests in XML data because that XML has flexible structure. Keyword search has attracted a great deal of attention for retrieving XML data because it is a user-friendly mechanism. But Keyword search is hard to directly improve search quality because lots of keyword-matched nodes may not contribute to the results. And in many applications, the goal is to find such related results that best match a set of keywords, the keywords occur location may not be consided. XML includes rich semantic information, these semantics are helpful to information retrieval process. The existing approaches of keyword search usually first generate all possible results composed of relevant tuples and then sort them based on their individual ranks. This paper investigates the compelling problem of how to take advantage of XML semantics to improve keyword search quality. We design an XML keyword search approach, that can derive the keyword query and generate a set of effective structured queries by analyzing the given keyword query and the schemas of XML data sources. Furthermore, we provide a terse algorithm to computing the rank score of the structured queries, then we can sort the results easily. We have implemented our method on real datasets and the experimental results show that our approach achieves both high recall and precise when compared with existing proposals.