What is he best known for?
The fields of study he is best known for:
- The Internet
- Operating system
- Artificial intelligence
John Riedl spends much of his time researching Collaborative filtering, Recommender system, World Wide Web, MovieLens and Information retrieval.
His research on Collaborative filtering focuses in particular on Slope One.
His Recommender system study incorporates themes from Quality, Personalization, Field, User experience design and Algorithm.
His biological study spans a wide range of topics, including User modeling, Internet privacy and Tag system.
His MovieLens study integrates concerns from other disciplines, such as Social navigation and Multimedia.
He combines subjects such as Data mining, Executable, Function, Control and Popularity with his study of Information retrieval.
His most cited work include:
- Item-based collaborative filtering recommendation algorithms (6199 citations)
- GroupLens: an open architecture for collaborative filtering of netnews (4522 citations)
- Evaluating collaborative filtering recommender systems (4481 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Recommender system, World Wide Web, Collaborative filtering, Information retrieval and Quality.
His specific area of interest is Recommender system, where John Riedl studies MovieLens.
His work in the fields of World Wide Web, such as Personalization, overlaps with other areas such as Interface.
Slope One is the focus of his Collaborative filtering research.
His work deals with themes such as Function and Information space, which intersect with Information retrieval.
His Quality research includes themes of Encyclopedia and Knowledge management.
He most often published in these fields:
- Recommender system (36.27%)
- World Wide Web (32.64%)
- Collaborative filtering (22.80%)
What were the highlights of his more recent work (between 2010-2017)?
- Recommender system (36.27%)
- World Wide Web (32.64%)
- Quality (12.95%)
In recent papers he was focusing on the following fields of study:
Recommender system, World Wide Web, Quality, Information retrieval and Public relations are his primary areas of study.
John Riedl is studying Collaborative filtering, which is a component of Recommender system.
His Collaborative filtering research incorporates themes from Variety, Field and Implementation.
He interconnects User interface and Key in the investigation of issues within World Wide Web.
The various areas that John Riedl examines in his Quality study include Software system, Social media, Order and Encyclopedia.
His Folksonomy study in the realm of Information retrieval interacts with subjects such as Set.
Between 2010 and 2017, his most popular works were:
- Collaborative Filtering Recommender Systems (632 citations)
- Recommender systems: from algorithms to user experience (447 citations)
- Building Successful Online Communities: Evidence-Based Social Design (373 citations)
In his most recent research, the most cited papers focused on:
- The Internet
- Operating system
- Artificial intelligence
His scientific interests lie mostly in Quality, Recommender system, Encyclopedia, Public relations and Collaborative filtering.
The Quality study combines topics in areas such as Order and Data science.
The study incorporates disciplines such as Ground truth and Data structure in addition to Recommender system.
His research integrates issues of Peer production and Internet privacy in his study of Encyclopedia.
John Riedl has included themes like Variety, User experience design, Field and Key in his Collaborative filtering study.
His User experience design research integrates issues from Open research, World Wide Web, Algorithm and Relevance.
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