Bees Swarm Optimization Based Approach for Web Information Retrieval
This paper deals with large scale information retrieval aiming at contributing to web searching. The collections of documents considered are huge and not obvious to tackle with classical approaches. The greater the number of documents belonging to the collection, the more powerful approach required....
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| Veröffentlicht in: | 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Jg. 1; S. 6 - 13 |
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| Format: | Tagungsbericht |
| Sprache: | Englisch |
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IEEE
01.08.2010
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| ISBN: | 9781424484829, 1424484820 |
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| Abstract | This paper deals with large scale information retrieval aiming at contributing to web searching. The collections of documents considered are huge and not obvious to tackle with classical approaches. The greater the number of documents belonging to the collection, the more powerful approach required. A Bees Swarm Optimization algorithm called BSO-IR is designed to explore the prohibitive number of documents to find the information needed by the user. Extensive experiments were performed on CACM and RCV1 collections and more large corpuses in order to show the benefit gained from using such approach instead of the classic one. Performances in terms of solutions quality and runtime are compared between BSO and exact algorithms. Numerical results exhibit the superiority of BSO-IR on previous works in terms of scalability while yielding comparable quality. |
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| AbstractList | This paper deals with large scale information retrieval aiming at contributing to web searching. The collections of documents considered are huge and not obvious to tackle with classical approaches. The greater the number of documents belonging to the collection, the more powerful approach required. A Bees Swarm Optimization algorithm called BSO-IR is designed to explore the prohibitive number of documents to find the information needed by the user. Extensive experiments were performed on CACM and RCV1 collections and more large corpuses in order to show the benefit gained from using such approach instead of the classic one. Performances in terms of solutions quality and runtime are compared between BSO and exact algorithms. Numerical results exhibit the superiority of BSO-IR on previous works in terms of scalability while yielding comparable quality. |
| Author | Drias, Habiba Mosteghanemi, Hadia |
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| SubjectTerms | BSO classic approach Complexity theory evolutionary algorithms Heuristic algorithms Humanities Indexing Information retrieval Metaheuristics Particle swarm optimization Scalability swarm intelligence Time factors Vectors very large collections of documents web information retrieval |
| Title | Bees Swarm Optimization Based Approach for Web Information Retrieval |
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