Title :
Information Retrieval using probability and belief theory
Author :
Chowdhary, K.R. ; Bansal, V.S.
Author_Institution :
M.B.M. Eng. Coll., Jodhpur, India
Abstract :
This paper presents two approaches for Information Retrieval (IR) from a collection of documents: Bayesian theory of probability and Dempster-Shafer theory of belief functions. Each method has been supported with essential derivations to prove their suitability for IR. The conclusions of derivations have been applied in illustrative examples. Finally, comparison of both the methods suggests the suitability of each for specific domains.
Keywords :
belief networks; inference mechanisms; information retrieval; probability; Bayesian theory; Dempster-Shafer theory; belief function; belief theory; document retrieval; information retrieval; probability; Animals; Bayesian methods; Computational modeling; Indexes; Information retrieval; Probabilistic logic; Uncertainty; Bayesian; Dempster-Shafer; Document retrieval; Information Retrieval;
Conference_Titel :
Emerging Trends in Networks and Computer Communications (ETNCC), 2011 International Conference on
Conference_Location :
Udaipur
Print_ISBN :
978-1-4577-0239-6
DOI :
10.1109/ETNCC.2011.5958513
