Proceedings ArticleDOI
tagging, communities, vocabulary, evolution
Shilad Sen,Shyong K. Lam,Al Mamunur Rashid,Dan Cosley,Dan Frankowski,Jeremy Osterhouse,F. Maxwell Harper,John Riedl +7 more
- pp 181-190
TLDR
A user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency is presented and evaluated in an emergent tagging system by introducing tagging features into the MovieLens recommender system.Abstract:
A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.read more
Citations
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Journal ArticleDOI
The MovieLens Datasets: History and Context
TL;DR: The history of MovieLens and the MovieLens datasets is documents, including a discussion of lessons learned from running a long-standing, live research platform from the perspective of a research organization, and best practices and limitations of using the Movie Lens datasets in new research are documented.
Proceedings ArticleDOI
Why we tag: motivations for annotation in mobile and online media
Morgan G. Ames,Mor Naaman +1 more
TL;DR: The incentives for annotation in Flickr, a popular web-based photo-sharing system, and ZoneTag, a cameraphone photo capture and annotation tool that uploads images to Flickr are investigated to offer a taxonomy of motivations for annotation along two dimensions (sociality and function).
Proceedings ArticleDOI
Mapping the world's photos
TL;DR: This work uses the spatial distribution of where people take photos to define a relational structure between the photos that are taken at popular places, and finds that visual and temporal features improve the ability to estimate the location of a photo, compared to using just textual features.
Journal ArticleDOI
Collaborative Filtering beyond the User-Item Matrix: A Survey of the State of the Art and Future Challenges
TL;DR: A comprehensive introduction to a large body of research, more than 200 key references, is provided, with the aim of supporting the further development of recommender systems exploiting information beyond the U-I matrix.
Journal ArticleDOI
Recommender systems: from algorithms to user experience
Joseph A. Konstan,John Riedl +1 more
TL;DR: It is argued that evaluating the user experience of a recommender requires a broader set of measures than have been commonly used, and additional measures that have proven effective are suggested.
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