红外模型的凹凸性

Proceedings of the 21st ACM international conference on Information and knowledge management Pub Date : 2012-10-29 DOI:10.1145/2396761.2398686

S. Clinchant

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引用次数: 2

摘要

我们研究了IR模型中凹凸度的影响，并提出使用广义对数函数n-对数来对文档中的单词进行加权。我们用这个函数扩展了基于信息的信息检索(IR)模型族。我们表明，凹性确实是红外模型的一个重要性质。在红外任务、潜在语义索引和文本分类方面进行了实验。

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Concavity in IR models

We study the impact of concavity in IR models and propose to use a generalized logarithm function, the n-logarithm to weight words in documents. We extend the family of information based Information Retrieval (IR) models with this function. We show that that concavity is indeed an important property of IR models. Experiments conducted for IR tasks, Latent Semantic Indexing and Text Categorization show improvements.

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Proceedings of the 21st ACM international conference on Information and knowledge management

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