Research on B Cell Algorithm for Learning to Rank Method Based on Parallel Strategy

Yuling Tian, Hongxian Zhang, Quan Zou
2016 PLoS ONE  
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
more » ... rallel 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.
doi:10.1371/journal.pone.0157994 pmid:27487242 pmcid:PMC4972358 fatcat:nbxpmvhbcrbpbawm6435w2czfq