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Entity Linking of Artists Names in Japanese Music Articles

机译：日语音乐文章中艺术家姓名的实体链接

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摘要

The opportunity to read music articles and blogs on the Web to get music information is more and more increasing. However, hyperlinks to artist information do not often exist in such articles, and it is a troublesome task for the reader to look it up online. In this paper, in order to make it easy to look up artist information in music articles, we propose a method to extract entities such as artist names in music articles in Japanese, and to perform entity linking which links from artist entities to artist information automatically. The method consists of two phases. First, we extract artist names in music articles. An artist name is a named entity, and it is necessary to distinguish artist names from other named entities, such as personal names of non-artists, place names, organization names, etc. In order to achieve it, we prepare training data of music articles in which artist names are manually tagged, and extract artist names using Support Vector Machine (SVM). Next, we choose a web page of artist information for each extracted artist name. We use Wikipedia as the source of artist information to verify the usefulness of the proposed method, we conducted evaluation experiments using cross-validation. For the experiments, we used 35 Japanese music articles and extracted artist names manually from the articles, and used them for cross-validation. We achieved the recall of 0.2788, precision of 0.7530, and F-measure of 0.4070. We also conducted an experiment to find correct artist information from Wikipedia using edit distance between extracted artist names from ten music articles and Wikipedia titles. We achieved the correct rate of 0.8740 in linking correct Wikipedia articles for artist names.
机译：在网络上阅读音乐文章和博客以获取音乐信息的机会越来越多。但是，在此类文章中通常不存在指向艺术家信息的超链接，并且对于读者来说，在网上查找它是一项麻烦的任务。在本文中，为了使查找音乐文章中的艺术家信息变得容易，我们提出了一种方法，该方法可提取日语音乐文章中的艺术家名称之类的实体，并执行将艺术家实体与艺术家信息自动链接的实体链接。该方法包括两个阶段。首先，我们在音乐文章中提取艺术家的名字。艺术家名称是一个命名实体，有必要将艺术家名称与其他命名实体区分开，例如非艺术家的个人名称，地名，组织名称等。为了实现这一点，我们准备了音乐的训练数据手动标记艺术家名称的文章，并使用支持向量机（SVM）提取艺术家名称。接下来，我们为提取的每个艺术家名称选择一个艺术家信息网页。我们使用维基百科作为艺术家信息的来源，以验证所提出方法的有效性，并使用交叉验证进行了评估实验。对于实验，我们使用了35篇日本音乐文章，并从这些文章中手动提取了艺术家姓名，并将其用于交叉验证。我们实现了0.2788的召回率，0.7530的精度和0.4070的F量度。我们还进行了一项实验，使用从十首音乐文章中提取的艺术家姓名与Wikipedia标题之间的编辑距离，从Wikipedia中查找正确的艺术家信息。在针对艺术家姓名链接正确的Wikipedia文章时，我们的正确率为0.8740。

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