Research on Bayesian Network Retrieval Model Based on Query Expansion

2012 ◽  
pp. 291-295
Author(s):  
Shuang Zhao ◽  
Hong-Xia Wu ◽  
Yong-Min Lin
Keyword(s):  
Bayesian Network ◽  
Query Expansion ◽  
Retrieval Model ◽  
Model Based

Research on Bayesian Network Retrieval Model in Electronic Commerce

2012 ◽  
Vol 263-266 ◽  
pp. 2726-2731
Author(s):  
Shuang Zhao ◽  
Yong Min Lin
Keyword(s):  
Information Retrieval ◽  
Bayesian Network ◽  
Electronic Commerce ◽  
Theoretical Basis ◽  
Query Expansion ◽  
Posterior Probability ◽  
Expansion Method ◽  
Analysis Method ◽  
Retrieval Model ◽  
Retrieval Performance

On the analysis about the problem of information retrieval in the Electronic Commerce environment, this paper presents a Bayesian network retrieval model. This model adopts the topology of three layer nodes, and uses co-occurrence analysis method to mine relationships between the terms. A query expansion method according to domain ontology is used to extend the users query. Finally the similarity between the document and the query can be measured by calculating the posterior probability of relevance of the document. Experiments show that the model which will provide a theoretical basis for the problem of information retrieval in the Electronic Commerce environment can effectively improve the retrieval performance.

Probabilistic Model-Based Fault Diagnosis of the Rotor System

2007 ◽  
Author(s):  
Jiye Shao ◽  
Rixin Wang ◽  
Jingbo Gao ◽  
Minqiang Xu
Keyword(s):  
Fault Diagnosis ◽  
Bayesian Network ◽  
Network Model ◽  
Rotating Machinery ◽  
Rotor System ◽  
Bayesian Network Model ◽  
Diagnosis System ◽  
Model Based ◽  
Core Components ◽  
Fault Diagnosis System

The rotor is one of the most core components of the rotating machinery and its working states directly influence the working states of the whole rotating machinery. There exists much uncertainty in the field of fault diagnosis in the rotor system. This paper analyses the familiar faults of the rotor system and the corresponding faulty symptoms, then establishes the rotor’s Bayesian network model based on above information. A fault diagnosis system based on the Bayesian network model is developed. Using this model, the conditional probability of the fault happening is computed when the observation of the rotor is presented. Thus, the fault reason can be determined by these probabilities. The diagnosis system developed is used to diagnose the actual three faults of the rotor of the rotating machinery and the results prove the efficiency of the method proposed.

scholarly journals An information retrieval model based on simple Bayesian networks

2003 ◽  
Vol 18 (2) ◽  
pp. 251-265 ◽  
Author(s):  
Silvia Acid ◽  
Luis M. De Campos ◽  
Juan M. Fernández-Luna ◽  
Juan F. Huete
Keyword(s):  
Information Retrieval ◽  
Bayesian Networks ◽  
Retrieval Model ◽  
Model Based

A Semantic Retrieval Model Based on Domain Ontology of Orchard Disease and Pests

2016 ◽  
Vol 25 (3) ◽  
pp. 460-466 ◽  
Author(s):  
Jiajia Hou ◽  
Hui Han ◽  
Chengjing Qiu ◽  
Dongmei Li
Keyword(s):  
Domain Ontology ◽  
Semantic Retrieval ◽  
Retrieval Model ◽  
Model Based
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