DocumentCode :
2510075
Title :
Rated Tags: Adding Rating Capability to Collaborative Tagging
Author :
Kailer, Daniel ; Mandl, P. ; Schill, Alexander
Author_Institution :
Dept. of Comput. Sci. & Math., Munich Univ. of Appl. Sci., Munich, Germany
fYear :
2013
fDate :
Sept. 30 2013-Oct. 2 2013
Firstpage :
249
Lastpage :
255
Abstract :
Collaborative tagging is a popular way to organize content. But sometimes it is also used as a way to express opinions, which is normally done through rating- or text review systems. This paper will demonstrate that there is a gap between rating- and text review systems, that limits the ability of users to find the desired item. A novel concept based on collaborative tagging is presented, which is designed to bridge this gap. This concept, named Rated Tags, uses a hybrid approach to combine tagging-, rating- and review functionality. A key element of Rated Tags is the combination of a traditional user generated tag and a 5-star rating scale. Such a tag is called rated tag. We will discuss the design and the challenges of Rated Tags in detail and demonstrate its application based on a prototype. Furthermore we will show that similar related works suffer from an ambiguity problem, which was avoided in Rated Tags.
Keywords :
collaborative filtering; information retrieval; text analysis; 5-star rating scale; collaborative filtering; collaborative tagging; rated tags; rating functionality; rating review systems; review functionality; text review systems; Bridges; Cameras; Collaboration; Decision making; Headphones; Prototypes; Tagging; collaborative tagging; rated tags; ratings; reviews; social tagging; tags;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud and Green Computing (CGC), 2013 Third International Conference on
Conference_Location :
Karlsruhe
Type :
conf
DOI :
10.1109/CGC.2013.46
Filename :
6686038
Link To Document :
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