On Tag Recommendation for Expertise Profiling
- 2 February 2015
- conference paper
- conference paper
- Published by Association for Computing Machinery (ACM) in Proceedings of the Eighth ACM International Conference on Web Search and Data Mining
Abstract
Building expertise profiles is a crucial step towards identifying experts in different knowledge areas. However, summarizing the topics of expertise of a given individual is a challenging task, primarily due to the semi-structured and heterogeneous nature of the documentary evidence available for this task. In this paper, we investigate the suitability of tag recommendation as a mechanism to produce effective expertise profiles. In particular, we perform a large-scale user study with academic experts from different knowledge areas to assess the effectiveness of multiple supervised and unsupervised tag recommendation approaches as well as multiple sources of textual evidence. Our analysis reveals that traditional content-based tag recommenders perform well at identifying expertise-oriented tags, with article keywords being a particularly effective source of evidence across profiles in different knowledge areas and with various levels of sparsity. Moreover, by combining multiple recommenders and sources of evidence as learning signals, we further demonstrate the effectiveness of tag recommendation for expertise profiling.Keywords
Funding Information
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (MCT-CNPq 573871/2008-6)
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