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GroupLens Research is a human–computer interaction research lab in the Department of Computer Science and Engineering at the University of Minnesota, Twin Cities specializing in recommender systems and online communities. GroupLens also works with mobile and ubiquitous technologies, digital libraries, and local geographic information systems. The GroupLens lab was one of the first to study automated recommender systems with the construction of the "GroupLens" recommender, a Usenet article recommendation engine, and MovieLens, a popular movie recommendation site used to study recommendation engines, tagging systems, and user interfaces. The lab has also gained notability for its members' work studying open content communities such as Wikipedia and Cyclopath, a computational "geo-wiki" currently being used in the Twin Cities to help plan the regional cycling system.〔(【引用サイトリンク】 Cycloplan )〕 ==History== In 1992, John Riedl and Paul Resnick attended the CSCW conference together. After they heard keynote speaker Shumpei Kumon talk about his vision for an information economy,〔 〕 they began working on a collaborative filtering system for Usenet news. The system collected ratings from Usenet readers and used those ratings to predict how much other readers would like an article before they read it. This recommendation engine was one of the first automated collaborative filtering systems in which algorithms were used to automatically form predictions based on historical patterns of ratings.〔 〕 The overall system was called the "GroupLens" recommender, and the servers that collected the ratings and performed the computation were called the "Better Bit Bureau". This name was later dropped after a request from the Better Business Bureau. "GroupLens" is now used as a name both for this recommender system, and for the research lab at the University of Minnesota. A feasibility test was done between MIT and the University of Minnesota and a research paper was published including the algorithm, the system design, and the results of the feasibility study, in the CSCW conference of 1994.〔 〕 In 1995, Riedl and Resnick invited Joseph Konstan to join the team. Together, they decided to create a higher-performance implementation of the algorithms to support larger-scale deployments. In summer 1995 the team gathered Bradley Miller, David Maltz, Jon Herlocker, and Mark Claypool for "Hack Week" to create the new implementation, and to plan the next round of experiments.〔 〕 In the Spring of 1996, the first workshop on collaborative filtering was put together by Resnick and Hal Varian at the University of California, Berkeley.〔 (【引用サイトリンク】 Collaborative Filtering )〕 There, researchers from projects around the US that were studying similar systems came together to share ideas and experience. In the Summer of 1996, David Gardiner, a former Ph.D. student of Riedl's, introduced Riedl to Steven Snyder. Snyder had been one of the early employees at Microsoft, but had left Microsoft to come to Minnesota to do a Ph.D. in Psychology. He realized the commercial potential of collaborative filtering, and encouraged the team to found a company in April 1996. By June, Gardiner, Snyder, Miller, Riedl, and Konstan had incorporated their company, and by July they had their first round of funding, from the Hummer-Winblad venture capital company.〔 〕 Net Perceptions went on to be one of the leading companies in personalization during the Internet boom of the late 1990s, and stayed in business until 2004.〔 〕〔 〕 Based on their experience, Riedl and Konstan wrote a book about the lessons learned from deploying recommenders in practice.〔 〕 Recommender systems have since become ubiquitous in the online world, with leading vendors such as Amazon and Netflix deploying highly sophisticated recommender systems.〔 〕 Netflix even offered a $1,000,000 prize for improvements in recommender technology.〔 〕 Meanwhile, research continued at the University of Minnesota. When the EachMovie〔 〕 site closed in 1997, the researchers behind it released the anonymous rating data they had collected, for other researchers to use. The GroupLens Research team, led by Brent Dahlen and Jon Herlocker, used this data set to jumpstart a new movie recommendation site called MovieLens which has been a very visible research platform, including a detailed discussion in a New Yorker article by Malcolm Gladwell,〔 〕 and a report in a full episode of ABC Nightline.〔 〕 Between 1997 and 2002 the group continued its research on collaborative filtering, which became known in the community by the more general term of recommender systems. With Joe Konstan's expertise in user interfaces,〔 〕〔 〕 the team began exploring interface issues in recommenders, such as explanations,〔 〕 and meta-recommendation systems.〔 〕 In 2002, GroupLens expanded into social computing and online communities with the addition of Loren Terveen, who was known for his research of ''social'' recommender systems such as PHOAKS.〔 〕〔 〕 In order to broaden the set of research ideas and tools they used, Riedl, Konstan, and Terveen invited colleagues in social psychology (Robert Kraut and Sara Kiesler, of the Carnegie Mellon Human Computer Interaction Institute), and economic and social analysis (Paul Resnick and Yan Chen of the University of Michigan School of Information) to collaborate. The new, larger team adopted the name CommunityLab, and looked generally at the effects of technological interventions on the performance of online communities. For instance, some of their research explored technology for enriching conversation systems,〔 〕 while other research explored the personal, social, and economic motivations for user ratings.〔 〕〔 〕 In 2008 GroupLens launched Cyclopath,〔(【引用サイトリンク】title=cyclopath.org )〕 a computational geo-wiki for bicyclists within a city.〔 〕〔 . 〕 In 2010, GroupLens won the annual ACM software systems award.〔(【引用サイトリンク】title=Software System Award - Award Winners: List By Year )〕 Brent Hecht joined the GroupLens faculty in 2013, focusing on geographic human-computer interaction. Lana Yarosh joined the GroupLens faculty in 2014; she works with social computing and child-computer interaction. A third professor, Haiyi Zhu, will join in 2015. Haiyi has published research on Facebook and other social networks. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「GroupLens Research」の詳細全文を読む スポンサード リンク
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