Research on B Cell Algorithm for Learning to Rank Method Based on Parallel StrategyReportar como inadecuado




Research on B Cell Algorithm for Learning to Rank Method Based on Parallel Strategy - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

For the purposes of information retrieval, users must find highly relevant documents from within a system and often a quite large one comprised of many individual documents based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic–there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions.



Autor: Yuling Tian , Hongxian Zhang

Fuente: http://plos.srce.hr/



DESCARGAR PDF




Documentos relacionados