Details
| Original language | English |
|---|---|
| Title of host publication | HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 56-65 |
| Number of pages | 10 |
| ISBN (print) | 9781450329545 |
| Publication status | Published - 1 Sept 2014 |
| Event | 25th ACM Conference on Hypertext and Social Media, HT 2014 - Santiago, Chile Duration: 1 Sept 2014 → 4 Sept 2014 |
Publication series
| Name | HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media |
|---|
Abstract
Heterogeneous content is an inherent problem for cross-system search, recommendation and personalization. In this paper we investigate differences in topic coverage and the impact of topics in different kinds of Web services. We use entity extraction and categorization to create fingerprints that allow for meaningful comparison. As a basis taxonomy, we use the 23 main categories of Wikipedia Category Graph, which has been assembled over the years by the wisdom of the crowds. Following a proof of concept of our approach, we analyze differences in topic coverage and topic impact. The results show many differences between Web services like Twitter, Flickr and Delicious, which reflect users' behavior and the usage of each system. The paper concludes with a user study that demonstrates the benefits of fingerprints over traditional textual methods for recommendations of heterogeneous resources.
Keywords
- classification, comparison, domain independent, fingerprints, twikime, wikipedia
ASJC Scopus subject areas
- Computer Science(all)
- Computer Graphics and Computer-Aided Design
- Computer Science(all)
- Human-Computer Interaction
- Computer Science(all)
- Software
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HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media. Association for Computing Machinery (ACM), 2014. p. 56-65 (HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Exploiting the Wisdom of the Crowds for Characterizingand Connecting Heterogeneous Resources
AU - Kawase, Ricardo
AU - Siehndel, Patrick
AU - Pereira Nunes, Bernardo
AU - Herder, Eelco
AU - Nejdl, Wolfgang
PY - 2014/9/1
Y1 - 2014/9/1
N2 - Heterogeneous content is an inherent problem for cross-system search, recommendation and personalization. In this paper we investigate differences in topic coverage and the impact of topics in different kinds of Web services. We use entity extraction and categorization to create fingerprints that allow for meaningful comparison. As a basis taxonomy, we use the 23 main categories of Wikipedia Category Graph, which has been assembled over the years by the wisdom of the crowds. Following a proof of concept of our approach, we analyze differences in topic coverage and topic impact. The results show many differences between Web services like Twitter, Flickr and Delicious, which reflect users' behavior and the usage of each system. The paper concludes with a user study that demonstrates the benefits of fingerprints over traditional textual methods for recommendations of heterogeneous resources.
AB - Heterogeneous content is an inherent problem for cross-system search, recommendation and personalization. In this paper we investigate differences in topic coverage and the impact of topics in different kinds of Web services. We use entity extraction and categorization to create fingerprints that allow for meaningful comparison. As a basis taxonomy, we use the 23 main categories of Wikipedia Category Graph, which has been assembled over the years by the wisdom of the crowds. Following a proof of concept of our approach, we analyze differences in topic coverage and topic impact. The results show many differences between Web services like Twitter, Flickr and Delicious, which reflect users' behavior and the usage of each system. The paper concludes with a user study that demonstrates the benefits of fingerprints over traditional textual methods for recommendations of heterogeneous resources.
KW - classification
KW - comparison
KW - domain independent
KW - fingerprints
KW - twikime
KW - wikipedia
UR - http://www.scopus.com/inward/record.url?scp=84907385016&partnerID=8YFLogxK
U2 - 10.1145/2631775.2631797
DO - 10.1145/2631775.2631797
M3 - Conference contribution
AN - SCOPUS:84907385016
SN - 9781450329545
T3 - HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media
SP - 56
EP - 65
BT - HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media
PB - Association for Computing Machinery (ACM)
T2 - 25th ACM Conference on Hypertext and Social Media, HT 2014
Y2 - 1 September 2014 through 4 September 2014
ER -