A System for Keyword Proximity Search on XML Databases

Keyword proximity search is a user-friendly information discovery technique that has been extensively studied for text documents. In extending this technique to structured databases, recent works [6, 7, 4, 2] provide keyword proximity search on labeled graphs. A keyword proximity search does not require the user to know the structure of the graph, the role of the objects containing the keywords, or the type of the connections between the objects. The user simply submits a list of keywords and the system returns the sub-graph that connect the objects containing the keywords. XML and its labeled graph/tree abstractions are becoming the data model of choice for representing semistructured, self-describing data, and keyword proximity search is well-suited to XML documents as well. We describe a system that provides keyword proximity search on XML data that are modeled as labeled graphs or trees, the edges correspond to the element-subelement relationship and to ID/IDREF links (in the case of graphs). Our work differs from prior systems for proximity search on labeled graphs in that it can take advantage of knowledge of the schema, e.g., the XML Schema [12], to which the XML data con-