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Completely-Arbitrary Passage Retrieval in Language Modeling Approach

机译:语言建模方法中的完全任意段落检索

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Passage retrieval has been expected to be an alternative method to resolve length-normalization problem, since passages have more uniform lengths and topics, than documents. An important issue in the passage retrieval is to determine the type of the passage. Among several different passage types, the arbitrary passage type which dynamically varies according to query has shown the best performance. However, the previous arbitrary passage type is not fully examined, since it still uses the fixed-length restriction such as n consequent words. This paper proposes a new type of passage, namely completely-arbitrary passages by eliminating all possible restrictions of passage on both lengths and starting positions, and by extremely relaxing the type of the original arbitrary passage. The main advantage using completely-arbitrary passages is that the proximity feature of query terms can be well-supported in the passage retrieval, while the non-completely arbitrary passage cannot clearly support. Experimental result extensively shows that the passage retrieval using the completely-arbitrary passage significantly improves the document retrieval, as well as the passage retrieval using previous non-completely arbitrary passages, on six standard TREC test collections, in the context of language modeling approaches.
机译:由于段落比文档具有更统一的长度和主题,因此人们期望将段落检索作为解决长度标准化问题的另一种方法。段落检索中的一个重要问题是确定段落的类型。在几种不同的段落类型中,随查询动态变化的任意段落类型显示了最佳性能。但是,由于先前的任意通过类型仍使用诸如n个后续单词之类的固定长度限制,因此尚未得到充分检查。本文提出了一种新型的通道,即完全任意通道,它消除了通道在长度和起始位置上的所有可能限制,并且通过极大地放松了原始任意通道的类型。使用完全任意段落的主要优点是,在段落检索中可以很好地支持查询词的邻近特征,而不能完全支持非完全任意段落。实验结果广泛表明,在语言建模方法的背景下,使用完全任意段落的段落检索显着改善了文档检索以及使用先前的非完全任意段落的段落检索的六个标准TREC测试集。

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