推荐维基百科页面的段落作为旅游指南

2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA) Pub Date : 2016-11-01 DOI:10.1109/IWCIA.2016.7805749

M. Tokuhisa, Yuuki Ishihara, Shuhei Kimura, Kenta Oku

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引用次数: 2

摘要

本文提出了一种推荐维基百科页面段落作为旅游指南的方法。这种方法可以帮助游客(用户)在旅行中阅读维基百科页面的吸引人的描述。为了对段落进行评级，段落的重要性、非冗余性和新颖性基于Tf-Idf方式进行评估。特别是，新颖性是通过用户的经验来实现的，这些经验是通过定位用户过去访问过的地方的地理标记tweet来估计的。实验结果表明，地理标记推文反映了用户体验，推荐超出了MAP标准的预期。

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Recommending paragraphs of wikipedia pages as a travel guide

This paper proposes a method to recommend paragraphs of Wikipedia pages as a travel guide. This method helps tourists (users) read attractive descriptions of Wikipedia pages during their travel. In order to rate paragraphs, importance, non-redundancy, and novelty of the paragraphs are evaluated based on a Tf-Idf manner. Especially, novelty is done by user's experience estimated from geo-tagged tweets located to places that the user visited in the past. As the results of the experiments, we confirmed the geo-tagged tweets reflected user's experience and the recommendations exceeded the expectation of MAP criteria.

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2016 IEEE 9th International Workshop on Computational Intelligence and Applications (IWCIA)

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