Name
Title | ||
|---|---|---|
Leveraging search and content exploration by exploiting context in folksonomy systems |
Abstract | ||
|---|---|---|
With the advent of Web 2.0 tagging became a popular feature in social media systems. People tag diverse kinds of content, e.g. products at Amazon, music at Last.fm, images at Flickr, etc. In the last years several researchers analyzed the impact of tags on information retrieval. Most works focused on tags only and ignored context information. In this article we present context-aware approaches for learning semantics and improve personalized information retrieval in tagging systems. We investigate how explorative search, initialized by clicking on tags, can be enhanced with automatically produced context information so that search results better fit to the actual information needs of the users. We introduce the SocialHITS algorithm and present an experiment where we compare different algorithms for ranking users, tags, and resources in a contextualized way. We showcase our approaches in the domain of images and present the TagMe! system that enables users to explore and tag Flickr pictures. In TagMe! we further demonstrate how advanced context information can easily be generated: TagMe! allows users to attach tag assignments to a specific area within an image and to categorize tag assignments. In our corresponding evaluation we show that those additional facets of tag assignments gain valuable semantics, which can be applied to improve existing search and ranking algorithms significantly. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1080/13614568.2010.497193 | The New Review of Hypermedia and Multimedia |
Keywords | Field | DocType |
explorative search,leveraging search,tag assignment,content exploration,personalized information retrieval,existing search,actual information need,advanced context information,context information,information retrieval,folksonomy system,flickr picture,search result,personalized learning,personalization,information need,social media | Information system,Learning to rank,World Wide Web,Information needs,Social media,Information retrieval,Ranking,Computer science,Folksonomy,Semantics,Personalization | Journal |
Volume | Issue | ISSN |
16 | 1-2 | 1361-4568 |
Citations | PageRank | References |
1 | 0.34 | 20 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fabian Abel | 1 | 1187 | 62.22 |
| Matteo Baldoni | 2 | 924 | 80.42 |
| Cristina Baroglio | 3 | 645 | 62.62 |
| Nicola Henze | 4 | 946 | 90.27 |
| Ricardo Kawase | 5 | 57 | 6.34 |
| Daniel Krause | 6 | 1 | 0.34 |
| Viviana Patti | 7 | 638 | 61.15 |