An approach to controlling user models and personalization effects in recommender systems
An approach to controlling user models and personalization effects in recommender systems
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推荐系统中控制用户模型和个性化效果的方法
DOI：
10.1145/2449396.2449405
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
A. Tsang
中科院分区：
文献类型：
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作者：
Fedor Bakalov;Marie;B. König;Bahar Sateli;R. Witte;G. Butler;A. Tsang
个性化如今是广泛的计算机系统中的商品。例如，从基于用户先前购买的产品推荐的在线商店到基于用户浏览历史对搜索命中进行排序的网络搜索引擎。这种自适应行为的目的是帮助用户更容易、更快地找到相关内容。然而，这种行为也有一些消极的方面。自适应系统因违反了直接操作系统的可用性原则而受到批评，这些原则包括可控性、可预测性、透明性和不显眼性。在本文中，我们提出了一种方法来控制推荐系统中的自适应行为。它允许用户获得个性化效果的概述，查看用于个性化的用户配置文件，并根据他们的需求和偏好调整配置文件和个性化效果。我们提出了这种方法使用的一个例子，个性化的门户网站的生物化学文献，其用户是生物化学家，生物学家和基因组学家。此外，我们报告的用户研究评估可控个性化的有用性，可用性，用户满意度，透明度和可信度的个性化系统的影响。
Personalization nowadays is a commodity in a broad spectrum of computer systems. Examples range from online shops recommending products identified based on the user's previous purchases to web search engines sorting search hits based on the user browsing history. The aim of such adaptive behavior is to help users to find relevant content easier and faster. However, there are a number of negative aspects of this behavior. Adaptive systems have been criticized for violating the usability principles of direct manipulation systems, namely controllability, predictability, transparency, and unobtrusiveness. In this paper, we propose an approach to controlling adaptive behavior in recommender systems. It allows users to get an overview of personalization effects, view the user profile that is used for personalization, and adjust the profile and personalization effects to their needs and preferences. We present this approach using an example of a personalized portal for biochemical literature, whose users are biochemists, biologists and genomicists. Also, we report on a user study evaluating the impacts of controllable personalization on the usefulness, usability, user satisfaction, transparency, and trustworthiness of personalized systems.