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Recommender systems and market diversity.

机译:推荐系统和市场多样性。

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摘要

The last ten years have seen a large increase in the number of products available. Many believe this increased variety will allow consumers to obtain more ideal products for themselves. One difficulty that arises, however, is how consumers will find such niche products among so many choices. Recommender systems are one solution to this problem. These systems use data on purchases, ratings, and product content to identify which items are best suited to each user. Although a large body of work exists on designing recommender systems, we know much less about how they affect the market and society. This thesis begins a line of research in that direction, asking what effects recommenders have on the products sold through them and the consumers who use them. Part one asks how recommenders affect products: do recommenders increase the diversity of products sold? Two anecdotal views exist. A common view is that recommenders help consumers discover new products and thus increase sales diversity. Others believe that recommenders only reinforce the popularity of already popular products. Modeling the consumer-recommender interaction as a stochastic process, we find that some recommender designs can reduce sales diversity. In turn, consumers may be underserved if there exist better product matches outside of the hits. We also discuss design modifications that limit these popularity effects and promote exploration. Part two asks how recommenders affect consumers: do they create fragmentation among users? Recommenders give consumers a powerful means to focus on their interests and filter out all other content. As a result, critics argue that recommenders will reduce commonality and create fragmentation. Others, however, contend the opposite: recommenders may homogenize users because they share information among those who would otherwise not communicate. These are opposing views for which there is not yet empirical evidence. In an empirical study of a large service provider in the music industry, we find that recommenders are associated with an increase in commonality among users, and so concerns of fragmentation may be misplaced. The thesis thus identifies a debate about recommender systems in each part, products and consumers, and in each case, the reconciliation appears to challenge a popular view.
机译:在过去的十年中,可用产品的数量大大增加。许多人认为,品种的增加将使消费者能够自己获得更多理想的产品。然而,出现的一个困难是,消费者如何在众多选择中找到这种利基产品。推荐系统是解决此问题的一种方法。这些系统使用有关购买,等级和产品内容的数据来确定最适合每个用户的商品。尽管在设计推荐系统方面存在大量工作,但我们对它们如何影响市场和社会的了解还很少。本论文开始朝这个方向进行研究,询问推荐者对通过他们出售的产品和使用它们的消费者有什么影响。第一部分询问了推荐人如何影响产品:推荐人是否增加了所售产品的多样性?存在两个轶事视图。常见的观点是推荐者可以帮助消费者发现新产品,从而增加销售多样性。其他人则认为推荐者只会增强已经很流行的产品的受欢迎程度。将消费者与推荐者的互动建模为随机过程,我们发现一些推荐者设计可以减少销售差异。反过来,如果在热门产品之外还存在更好的产品匹配条件,则可能无法为消费者提供足够的服务。我们还将讨论限制这些受欢迎程度并促进探索的设计修改。第二部分询问推荐者如何影响消费者:它们在用户之间造成碎片吗?推荐为消费者提供了一种强大的手段来专注于他们的兴趣并过滤掉所有其他内容。结果,批评家认为推荐者将减少共性并造成分散性。然而,其他人则相反:推荐者可能使用户同质化,因为他们在原本不会交流的人之间共享信息。这些是没有经验证据的相反观点。在音乐行业中一家大型服务提供商的实证研究中,我们发现推荐者与用户之间的通用性增加相关联,因此可能会错位分散的担忧。因此,本文确定了关于每个部分,产品和消费者中的推荐系统的辩论,并且在每种情况下,和解似乎都对流行的观点提出了挑战。

著录项

  • 作者

    Fleder, Daniel M.;

  • 作者单位

    University of Pennsylvania.;

  • 授予单位 University of Pennsylvania.;
  • 学科 Business Administration Marketing.;Economics General.;Psychology Social.;Statistics.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 142 p.
  • 总页数 142
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 贸易经济;社会心理、社会行为;统计学;经济学;
  • 关键词

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