Development of semi-supervised named entity recognition to discover new tourism places

Khurniawan Eko Saputro, S. Kusumawardani, S. Fauziati
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引用次数: 7

Abstract

Tourism information needs are increasing in line with tourism that has been a primary need for some people. This has an impact on the growth of the tourism information provider. The amount of available information sometimes makes tourist confuse to the information that they needed. Currently, the search systems only rely on indexing web pages so that the information obtained by the tourist is still unfavorable because it only shows a web page with keywords that exist on the article. A support system to recognize tourism places on the web pages is required to produce better information presentation. In this study, the recognition system based on Yet Another Two Stage Idea (YATSI) Semi-Supervised Learning with the Naïve Bayes classifier is used to address the problem. Results obtained by classifying candidate entities on a hundred web pages demonstrate 74% precision with 70% recall.
开发半监督命名实体识别,发现新的旅游场所
随着旅游成为一些人的主要需求,旅游信息需求也在增加。这对旅游信息提供者的成长产生了影响。可获得信息的数量有时会使游客对他们需要的信息感到困惑。目前的搜索系统只依赖于索引网页,游客获得的信息仍然是不利的,因为它只显示了一个网页上存在的关键字的文章。需要一个支持系统来识别网页上的旅游地点,以提供更好的信息呈现。在本研究中,基于YATSI半监督学习的识别系统与Naïve贝叶斯分类器被用来解决这个问题。通过对100个网页上的候选实体进行分类得到的结果表明,准确率为74%,召回率为70%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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