Applying Genetic Algorithms to Information Retrieval Systems Via Relevance Feedback

Author(s):  
Donald H. Kraft ◽  
Frederick E. Petry ◽  
Bill P. Buckles ◽  
Thyagarajan Sadasivan
Author(s):  
Antonio Picariello

Information retrieval can take great advantages and improvements considering users’ feedbacks. Therefore, the user dimension is a relevant component that must be taken into account while planning and implementing real information retrieval systems. In this chapter, we first describe several concepts related to relevance feedback methods, and then propose a novel information retrieval technique which uses the relevance feedback concepts in order to improve accuracy in an ontology-based system. In particular, we combine the Semantic information from a general knowledge base with statistical information using relevance feedback. Several experiments and results are presented using a test set constituted of Web pages.


Author(s):  
Antonio Picariello ◽  
Antonio M. Rinaldi

The user dimension is a crucial component in the information retrieval process and for this reason it must be taken into account in planning and technique implementation in information retrieval systems. In this paper we present a technique based on relevance feedback to improve the accuracy in an ontology based information retrieval system. Our proposed method combines the semantic information in a general knowledge base with statistical information using relevance feedback. Several experiments and results are presented using a test set constituted of Web pages.


10.28945/3163 ◽  
2007 ◽  
Author(s):  
Panagiotis Petratos

In this article a human centered approach for Information Retrieval IR systems is offered. The focus of this article is on human users of IR systems, who are given the opportunity to offer enhanced relevance feedback. A novel approach is offered to capture the back-propagated feedback of human users during IR sessions. According to this approach the IR system is developed to accept human bidirectional relevance feedback, which is utilized to further enhance the IR process with the aim of improving IR effectiveness.


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