6 research outputs found
The Impact of Semantic Context Cues on the User Acceptance of Tag Recommendations: An Online Study
In this paper, we present the results of an online study with the aim to shed
light on the impact that semantic context cues have on the user acceptance of
tag recommendations. Therefore, we conducted a work-integrated social
bookmarking scenario with 17 university employees in order to compare the user
acceptance of a context-aware tag recommendation algorithm called 3Layers with
the user acceptance of a simple popularity-based baseline. In this scenario, we
validated and verified the hypothesis that semantic context cues have a higher
impact on the user acceptance of tag recommendations in a collaborative tagging
setting than in an individual tagging setting. With this paper, we contribute
to the sparse line of research presenting online recommendation studies.Comment: 2 pages, poste
A Temporal Usage Pattern-based Tag Recommendation Approach
While social tagging can benefit Internet users managing their resources, it suffers the problems such as diverse and/or unchecked vocabulary and unwillingness to tag. Use of freely new tags and/or reuse of frequent tags have degraded coherence of corresponding resources of each tag that further frustrates people in retrieving information due to cognitive dissonance. Tag recommender systems can recommend users the most relevant tags to the resource they intend to annotate, and drastically transfer the tagging process from generation to recognition to reduce user’s cognitive effort and time. Prior research on tag recommendation has addressed the time-dependence issues of tags by applying a time decaying measure to determine the recurrence probability of a tag according to its recency instead of its usage pattern. In response, this study intends to propose the temporal usage pattern-based tag recommendation technique to consider the usage patterns and temporal characteristic of tags for making recommendations