Contribution of Social Tagging to Clustering Effectiveness Using as Interpretant the User's Community

• Type: Article in International Conference Proceedings Book
• Date: 2020

Authors

Cunha, E (Author) Other; Figueira, A (Author) FCUP

Conference proceedings International

Title: WorldCIST (1)

Pages: 180-190

8th World Conference on Information Systems and Technologies, WorldCIST 2020

7 April 2020 through 10 April 2020

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-00S-3ZE

DOI: 10.1007/978-3-030-45688-7_19

Abstract (EN): In this article we discuss how social tagging can be used to improve the methodology used for clustering evaluation. We analyze the impact of the integration of tags in the clustering process and its effectiveness. Following the semiotic theory, the own nature of tags allows the reflection of which ones should be considered depending on the interpretant (community of users, or tag writer). Using a case with the community of users as the interpretant, our novel clustering algorithm (k-C), which is based on community detection on a network of tags, was compared with the standard k-means algorithm. The results indicate that the k-C algorithm created more effective clusters. © 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11