A multi-ranker model for adaptive XML searching

The evolution of computing technology suggests that it has become more feasible to offer access to Web information in a ubiquitous way, through various kinds of interaction devices such as PCs, laptops, palmtops, and so on. As XML has become a defacto standard for exchanging Web data, an interesting and practical research problem is the development of models and techniques to satisfy various needs and preferences in searching XML data. In this paper, we employ a list of simple XML tagged keywords as a vehicle for searching XML fragments in a collection of XML documents. In order to deal with the diversified nature of XML documents as well as user preferences, we propose a novel nker Model (MRM), which is able to abstract a spectrum of important XML properties and adapt the features to different XML search needs. The MRM is composed of three ranking levels. The lowest level consists of two categories of similarity and granularity features. At the intermediate level, we define four tail...

• Type: Conference
• Year: 2008
• Where: VLDB
• Authors: Ho Lam Lau, Wilfred Ng
• Keywords: Database, Training Xml Fragments, VLDB 2008, XML Fragments, XML Tagged Keywords