An Information-Based Cross-Language Information Retrieval Model
An Information-Based Cross-Language Information Retrieval Model
复制标题
一种基于信息的跨语言信息检索模型
DOI：
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发表时间：
2012
期刊：
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通讯作者：
Éric Gaussier
中科院分区：
文献类型：
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作者：
Bo Li;Éric Gaussier
我们在本文中提出了基于信息的信息检索家族中最近引入的模型的跨语言扩展，即[4]的LL（逻辑逻辑）和SPL（平滑幂律）模型。这些扩展基于(a)对基于信息的族中使用的信息概念的概括，(b)对该族中也使用的随机变量的概括，以及(c)对查询术语及其翻译的直接扩展。然后，在实验评估之前，我们从理论的角度回顾这些扩展。在三个集合和三个语言对上，将这些扩展与现有的CLIR系统进行了实验比较，结果表明，LL模型的跨语言扩展提供了最先进的CLIR系统，总体性能最好。
We present in this paper well-founded cross-language extensions of the recently introduced models in the information-based family for information retrieval, namely the LL (log-logistic) and SPL (smoothed power law) models of [4]. These extensions are based on (a) a generalization of the notion of information used in the information-based family, (b) a generalization of the random variables also used in this family, and (c) the direct expansion of query terms with their translations. We then review these extensions from a theoretical point-of-view, prior to assessing them experimentally. The results of the experimental comparisons between these extensions and existing CLIR systems, on three collections and three language pairs, reveal that the cross-language extension of the LL model provides a state-of-the-art CLIR system, yielding the best performance overall.