Abstract
This work evaluates the combination of multiple evidence for discovering groups of users with similar interests. User groups are created by analysing the search logs recorded for a sample of 149 users of a professional image search engine in conjunction with the textual and visual features of the clicked images, and evaluated by exploiting their topical classification. The results indicate that the discovered user groups are meaningful and that combining textual and visual features improves the homogeneity of the user groups compared to each individual feature.
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Tsikrika, T., Diou, C. (2014). Multi-evidence User Group Discovery in Professional Image Search. In: de Rijke, M., et al. Advances in Information Retrieval. ECIR 2014. Lecture Notes in Computer Science, vol 8416. Springer, Cham. https://doi.org/10.1007/978-3-319-06028-6_78
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DOI: https://doi.org/10.1007/978-3-319-06028-6_78
Publisher Name: Springer, Cham
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