Add to ORKGInternational audienceThis paper presents an approach to intelligent information retrieval based on genetic heuristics. Recent search has shown that applying genetic models for query optimisation improve the retrieval effectiveness. We investigate ways to improve this process by combining genetic heuristics and information retrieval techniques. More precisely, we propose to integrate relevance feedback techniques to perform the genetic operators and the speciation heuristic to solve the relevance multimodality problem. Experiments, with AP documents and queries issued from TREC, showed the effectiveness of our approach. Keywords: Informatio
In this paper we compare four selection strategies in evolutionary optimization of information retri...
As the information grows rapidly, searching relevant and up to date information has become a crucial...
In this paper we compare four selection strategies in evolutionary optimization of information retri...
International audienceThis work presents a genetic approach for query optimisation in information re...
International audienceRecent studies suggest that significant improvement in information retrieval p...
International audienceThis paper presents a genetic relevance optimisation process performed in an i...
International audienceThis paper presents a new genetic approach for query optimisation in document ...
This paper presents an adaptive method using genetic algorithm to modify user’s queries, based on r...
The thesis deals with the use of genetic algorithmes to tackle information retrieval issues. More pr...
The thesis deals with the use of genetic algorithmes to tackle information retrieval issues. More pr...
Abstract-The augmentation of digital information on the Web has proliferated informational needs and...
The ability of information retrieval system parameters on the basis of user's relevance feedback for...
The ability of information retrieval system parameters on the basis of user's relevance feedback for...
Abstract—The formulation of user queries is an important part of the information retrieval process. ...
Information retrieval systems are complex in nature due to the interactions of document, query, and ...
In this paper we compare four selection strategies in evolutionary optimization of information retri...
As the information grows rapidly, searching relevant and up to date information has become a crucial...
In this paper we compare four selection strategies in evolutionary optimization of information retri...
International audienceThis work presents a genetic approach for query optimisation in information re...
International audienceRecent studies suggest that significant improvement in information retrieval p...
International audienceThis paper presents a genetic relevance optimisation process performed in an i...
International audienceThis paper presents a new genetic approach for query optimisation in document ...
This paper presents an adaptive method using genetic algorithm to modify user’s queries, based on r...
The thesis deals with the use of genetic algorithmes to tackle information retrieval issues. More pr...
The thesis deals with the use of genetic algorithmes to tackle information retrieval issues. More pr...
Abstract-The augmentation of digital information on the Web has proliferated informational needs and...
The ability of information retrieval system parameters on the basis of user's relevance feedback for...
The ability of information retrieval system parameters on the basis of user's relevance feedback for...
Abstract—The formulation of user queries is an important part of the information retrieval process. ...
Information retrieval systems are complex in nature due to the interactions of document, query, and ...
In this paper we compare four selection strategies in evolutionary optimization of information retri...
As the information grows rapidly, searching relevant and up to date information has become a crucial...
In this paper we compare four selection strategies in evolutionary optimization of information retri...