Title :
Bayesian Networks Model for Xml Documents Ranking
Author :
Wang, He-yi ; Yang, Shi-ying
Author_Institution :
Inst. of Syst. Eng., Tianjin Univ.
Abstract :
As more and more data are described, stored, exchanged and represented by XML, the abilities of information retrieval for XML documents become increasingly important. However, the retrieval results to users are quite large. To text-rich XML documents´ retrieval, a structured index method is designed at first, which accounts for the structure and content of each document. Then each XML document is modeled through a Bayesian network to handle both structure and content for the document. This paper also presents the inference process for computing the probability of each document on the given query. Finally documents are ranked according to the probabilities in descent. The experiments indicate that this framework can reduce the workloads and the complications, and also improve the recall and precision
Keywords :
XML; belief networks; inference mechanisms; information retrieval; probability; Bayesian network; Bayesian network model; XML document ranking; inference process; information retrieval; probability; structured index method; text-rich XML document retrieval; Bayesian methods; Computer networks; Content based retrieval; Cybernetics; Data engineering; Design methodology; Finance; Information retrieval; Machine learning; Systems engineering and theory; Web pages; XML; XML document; belief network; document ranking;
Conference_Titel :
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location :
Dalian, China
Print_ISBN :
1-4244-0061-9
DOI :
10.1109/ICMLC.2006.258831