Paper Info
Title
Comparing Boolean and probabilistic information retrieval systems across queries and disciplines
Abstract
Abstract Whether using Boolean queries or ranking documents,using document,and term weights will result in better retrieval performance,has been the subject of considerable discussion among,document,retrieval system users and researchers. We suggest a method that allows one to analytically compare,the two approaches to retrieval and examine,their relative merits. The performance,of information retrieval systems may be determined either by using experimental simulation, or through the application of analytic techniques that directly estimate the retrieval performance, given values for query and database characteristics. Using these performance predicting techniques, sample performance figures are provided for queries using the Boolean and and or, as well as for probabilistic systems assuming statistical term independence,or term dependence. The variation of performance,across sublanguages,(used in different academic,disciplines) and queries is examined. The performance,of models failing to meet statistical and other assumptions is examined.
Year
DOI
Venue
1997
3.0.CO;2-Y" target="_self" class="small-link-text"10.1002/(SICI)1097-4571(199702)48:23.0.CO;2-Y
JASIS
Keywords
Field
DocType
probabilistic information retrieval system,data analysis,databases,information systems,information retrieval,document retrieval,information retrieval system,mathematical formulas,comparative analysis,relevance information retrieval
Data mining,Divergence-from-randomness model,Information retrieval,Ranking,Computer science,Standard Boolean model,Boolean algebra,Relevance (information retrieval),Probabilistic logic,Vector space model,Document retrieval
Journal
Volume
Issue
ISSN
48
2
0002-8231
Citations 
PageRank 
References 
9
0.62
29
Authors
1
Name
Order
Citations
PageRank
Robert M. Losee127636.01