Abstract
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.
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This work is financed by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia within project: UID/EEA/50014.
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Cunha, E., Figueira, Á. (2020). Contribution of Social Tagging to Clustering Effectiveness Using as Interpretant the User’s Community. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S., Orovic, I., Moreira, F. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing, vol 1159. Springer, Cham. https://doi.org/10.1007/978-3-030-45688-7_19
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DOI: https://doi.org/10.1007/978-3-030-45688-7_19
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