Abstract
We propose rarity-oriented retrieval methods for serendipity using two approaches. We define rare information as relevant and atypical information. We propose two approaches. In the first approach, we use social bookmark data. We introduce tag estimation to our previous work. The second approach is based on word co-occurrence in a dataset. In both approaches, we use conditional probabilities to express relevancy and atypicality. In experiments, we compared our methods with the relevance-oriented method, the diversity-oriented method, and another rarity-oriented method. Our methods using word co-occurrence obtained better nDCG scores than the other methods.
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Yumoto, T., Yamanaka, T., Nii, M., Kamiura, N. (2016). Rarity-Oriented Information Retrieval: Social Bookmarking vs. Word Co-occurrence. In: Morishima, A., Rauber, A., Liew, C. (eds) Digital Libraries: Knowledge, Information, and Data in an Open Access Society. ICADL 2016. Lecture Notes in Computer Science(), vol 10075. Springer, Cham. https://doi.org/10.1007/978-3-319-49304-6_11
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DOI: https://doi.org/10.1007/978-3-319-49304-6_11
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