Article Recommender for Feed Readers with a Loss Compensation Based on the TF-IDF Weight

机译：具有TF-IDF权重的，具有损失补偿的Feed阅读器的文章推荐者

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摘要

In this paper, we improve the accuracy of item-based collaborative filtering by introducing a loss compensation based on the TF-IDF weight. The proposed scheme is implemented as a part of a feed reader, and is evaluated through the feedback from users.

机译：在本文中，我们通过引入基于TF-IDF权重的损失补偿来提高基于项目的协作过滤的准确性。所提出的方案被实现为提要阅读器的一部分，并通过来自用户的反馈进行评估。

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《2010 First International Conference on Networking and Computing》|2010年|p.298-299|共2页
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作者
Yokota Daichi; Fujita Satoshi;
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原文格式 PDF
正文语种
中图分类计算机网络;
关键词
Collaborative Filtering; Recommendation; TF-IDF;

机译：协同过滤;推荐; TF-IDF;

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Article Recommender for Feed Readers with a Loss Compensation Based on the TF-IDF Weight

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