dc.contributor.author |
Barnes, Michael |
|
dc.date.accessioned |
2008-11-03T20:31:18Z |
|
dc.date.available |
2008-11-03T20:31:18Z |
|
dc.date.issued |
2007-03 |
|
dc.identifier.uri |
http://hdl.handle.net/1794/7670 |
|
dc.description |
131 p. This paper was completed as part of the final research component in the University of Oregon Applied Information Management Master's Degree Program [see htpp://aim.uoregon.edu]. |
en |
dc.description.abstract |
This study describes how user-generated metadata may be leveraged to enhance findability in web-based social software applications (Morville, 2005). Two interaction design systems, content tagging (Golder & Huberman, 2005) and recommender systems (Resnick & Varian, 1997), are examined to identify strengths and weaknesses along three findability factors: information classification, information retrieval and information discovery. Greater overall findability strength may be found in content tagging systems than in recommender systems. |
en |
dc.relation.ispartofseries |
AIM Capstone 2007;Michael Barnes |
|
dc.subject |
Applied Information Management |
en |
dc.subject |
Social software applications |
en |
dc.subject |
Metadata |
en |
dc.subject |
Information classification |
en |
dc.subject |
Information discovery |
en |
dc.subject |
Recommender systems |
en |
dc.subject |
Content tagging |
en |
dc.subject |
Information retrieval |
en |
dc.subject |
AIM |
en |
dc.subject |
Data |
en |
dc.title |
User-Generated Metadata in Social Software: An Analysis of Findability in Content Tagging and Recommender Systems |
en |
dc.type |
Other |
en |