从评级中提取特征：因子模型的作用

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摘要翻译：
执行有效的基于偏好的数据检索需要关于当前用户以及正在考虑的项目的详细且优先是有意义的结构化信息。一个常见的问题是，项目的表示通常只包含纯粹的技术属性，而不像人类的感知。对于整体项目，如电影或歌曲，尤其如此。人们经常声称，有意义的项目特征可以从协作评级数据中提取，这些数据正在通过社交网络服务获得。然而，只有轶事证据支持这一说法；但是如果是这样的话，提取的信息对于基于偏好的数据检索是非常有价值的。在本文中，我们提出了一种方法来系统地检查这一共同的主张。我们对大量的电影评分进行了初步调查，并提出了初步证据。
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英文标题：
《Extracting Features from Ratings: The Role of Factor Models》
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作者：
Joachim Selke and Wolf-Tilo Balke
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最新提交年份：
2011
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  Performing effective preference-based data retrieval requires detailed and preferentially meaningful structurized information about the current user as well as the items under consideration. A common problem is that representations of items often only consist of mere technical attributes, which do not resemble human perception. This is particularly true for integral items such as movies or songs. It is often claimed that meaningful item features could be extracted from collaborative rating data, which is becoming available through social networking services. However, there is only anecdotal evidence supporting this claim; but if it is true, the extracted information could very valuable for preference-based data retrieval. In this paper, we propose a methodology to systematically check this common claim. We performed a preliminary investigation on a large collection of movie ratings and present initial evidence.
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PDF链接：
https://arxiv.org/pdf/1101.2378

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关键词：Presentation Intelligence Presentatio information Preliminary items 进行 data evidence 协作