scholarly journals A Linguistically Motivated Probabilistic Model of Information Retrieval

Author(s):  
Djoerd Hiemstra
2000 ◽  
Vol 36 (6) ◽  
pp. 809-840 ◽  
Author(s):  
K Sparck Jones ◽  
S Walker ◽  
S.E Robertson

Author(s):  
KENJI SAITO ◽  
HIROYUKI SHIOYA ◽  
TSUTOMU DA-TE

We improve a document retrieval method based on the so-called maximum entropy principle proposed by Cooper, and show how to implement this system on a Bayesian network. A Bayesian network is a probabilistic model for expressing probabilistic relations among random variables. We show advantages of a document retrieval system on a Bayesian network in comparison with Cooper's system. The original document retrieval system based on the maximum entropy principle has a drawback: a result of retrieval can not be obtained in some cases. In this paper, we resolve this drawback by fuzzification of user retrieval requests.


2017 ◽  
Vol 53 (1) ◽  
pp. 87-105 ◽  
Author(s):  
Fouad Dahak ◽  
Mohand Boughanem ◽  
Amar Balla

2000 ◽  
Vol 36 (6) ◽  
pp. 779-808 ◽  
Author(s):  
K. Sparck Jones ◽  
S. Walker ◽  
S.E. Robertson

2016 ◽  
Vol 8 (3) ◽  
pp. 494-504 ◽  
Author(s):  
Fei Cai ◽  
Honghui Chen

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