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意见挖掘应用程序的实体发现和分配
Entity Discovery and Assignment for Opinion Mining Applications |
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| 课程网址: |
http://videolectures.net/kdd09_liu_edaoma/
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| 主讲教师: |
Bing Liu
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| 开课单位: |
伊利诺大学
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| 开课时间: |
2009-09-14
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| 课程语种: |
英语
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| 中文简介: |
由于其广泛的应用，意见挖掘近年来成为一个重要的研究课题。还有许多公司提供意见挖掘服务。到目前为止尚未研究的一个问题是每个句子中已经讨论过的实体的分配。让我们以产品的论坛讨论为例，使问题具体化。在典型的讨论帖中，作者可以就多种产品发表意见并进行比较。问题是如何检测每个句子中谈到的产品。如果句子包含产品名称，则需要识别它们。我们将此问题称为实体发现。如果产品名称未在句子中明确提及但由于使用代词和语言惯例而暗示，我们需要推断产品。我们将此问题称为实体分配。这些问题很重要，因为不知道每个句子谈论从句子中挖掘的意见的产品几乎没用。在本文中，我们研究这些问题并提出两种有效的方法来解决这些问题。实体发现基于模式发现，实体分配基于比较句的挖掘。使用大量论坛帖子的实验结果证明了该技术的有效性。我们的系统也已在商业环境中成功通过测试。
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| 课程简介: |
Opinion mining became an important topic of study in recent years due to its wide range of applications. There are also many companies offering opinion mining services. One problem that has not been studied so far is the assignment of entities that have been talked about in each sentence. Let us use forum discussions about products as an example to make the problem concrete. In a typical discussion post, the author may give opinions on multiple products and also compare them. The issue is how to detect what products have been talked about in each sentence. If the sentence contains the product names, they need to be identified. We call this problem entity discovery. If the product names are not explicitly mentioned in the sentence but are implied due to the use of pronouns and language conventions, we need to infer the products. We call this problem entity assignment. These problems are important because without knowing what products each sentence talks about the opinion mined from the sentence is of little use. In this paper, we study these problems and propose two effective methods to solve the problems. Entity discovery is based on pattern discovery and entity assignment is based on mining of comparative sentences. Experimental results using a large number of forum posts demonstrate the effectiveness of the technique. Our system has also been successfully tested in a commercial setting.
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| 关 键 词: |
实体发现; 实体分配; 比较句
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| 课程来源: |
视频讲座网
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| 最后编审: |
2020-07-16：yumf
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| 阅读次数: |
37
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