【摘要】 在信息检索①发展的过程中,研究者们不断尝试着将自然语言处理应用到检索里,希望能够为检索效果提高带来帮助。然而这些尝试的结果大多和研究者们最初的设想相反,自然语言处理在大多数情况下没有改进信息检索效果,甚至反而起了负面作用。即便有一些帮助,也往往是微小的,远远不如自然语言处理所需要的计算消耗那么大。研究者们对这些现象进行了分析,认为:自然语言处理更适合于应用在需要精确结果的任务中,例如问答系统、信息抽取等;自然语言处理需要针对信息检索进行优化才可能发挥积极作用。最新的一些进展(例如在语言模型中加入自然语言处理)在一定程度上印证了这一结论。更多还原

【Abstract】 Natural language processing(NLP) has been used in information retrieval(IR) by researchers,in the hope of improving retrieval effect.But most of the results are in the opposite way hypothesized.In most cases,NLP didn’t yield increases in IR precision but took a negative effect.Even if NLP helped IR under some circumstances,the improvements were much smaller than the processing cost needed by NLP.Researchers perform analysis on these phenomena and come to the conclusion that: IR-related tasks that acquire accurate results,such as question answering(QA) and information extraction(IE),are more suited for the use of NLP.NLP needs to be optimized for IR in order to be effective.Recent research,e.g.adding NLP factors to language model,has more or less confirmed the conclusion.更多还原