I-Corps: Diversity-aware News Recommendation

本项目拟探索构建具有多样性意识的新闻推荐服务，以改善人们的新闻阅读体验。研究人员已经开展了几项对照实验和实地试验，以验证理论，并深入了解如何衡量多样性的替代概念，如何模拟用户的多样性偏好，以及如何以一种让用户满意的方式向用户呈现具有挑战性的项目。此外，我们还开发了算法、系统和小部件，可以根据政治观点对政治文章进行分类，生成一个平衡的文章列表，并在用户阅读相关文章时向他们提供多样性增强的推荐。这项工作是第一次尝试形式化多样性一般概念的几个不同实例，并设计针对这些措施进行优化的算法。数字新闻聚合器依靠评级和链接来选择和呈现每天生成的大量新闻和观点项目的子集。输出集中的意见和主题多样性可以提供几个好处。对于个人读者来说，不同的结果可能会更有趣，并随着时间的推移带来更好的学习。一种特殊形式的多样性，即不同群体利益的比例代表制，可以为与其他人讨论提供共同的基础，也可以使人们了解哪些是多数人的观点，哪些是少数人的观点。这个项目提出的服务如果成功，将作为网站和浏览器插件直接提供给消费者。研究人员认为，他们可以提供一种服务，帮助公众提高他们的新闻阅读习惯。多样性感知推荐技术可能适用于新闻阅读以外的其他领域，在这些领域中，选择一组不同的项目是有价值的，例如搜索引擎结果、电子商务产品推荐，以及听众对会议演讲者或公职人员提出的问题进行投票。

This project plans to investigate building a diversity-aware news recommendation service to improve people's news reading experience. Researchers have launched several controlled experiments and field trials to validate theories and gain insights on how to measure alternative notions of diversity, how to model users' diversity preferences, and how to present challenging items to users in a way that is palatable to users. In addition, we have developed algorithms, systems and widgets that classify political articles according to their political opinions, produce a balanced list of articles, and present the diversity-enhanced recommendations to users while they are reading related articles. This work is the first attempt to formalize several different instantiations of the general concept of diversity and to devise algorithms that optimize for these measures.Digital news aggregators rely on ratings and links to select and present subsets of the large quantity of news and opinion items generated each day. Opinion and topic diversity in the output sets can provide several benefits. For individual readers, diverse results may be more interesting and lead to greater learning over time. A particular form of diversity, proportional representation of different group interests, can provide common ground for discussion with other people and also lead to understanding of which are majority and which are minority viewpoints. The service proposed by this project, if successful, will be made available directly to consumers, as a website and browser plug-ins. Researchers believe that they can provide a service that will help the public enhance their news-reading habits. Diversity-aware recommendation techniques are likely to be applicable to other domains beyond news reading where selecting a diverse set of items is valuable, such as search engine results, e-Commerce product recommendations, and audience voting on questions to ask of a conference speaker or public official.