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- W2897301114 abstract "Micro-blogging services have emerged as a powerful, real-time, way to disseminate information on the web. A small fraction of the colossal volume of posts overall are relevant. We propose Curator, a micro-blogging recommendation system that ranks micro-blogs appearing on a user’s timeline according to her context. Curator learns user’s time variant preferences from the text of the micro-blogs the user interacts with. Furthermore, Curator infers the user’s home location and the micro-blog’s subject location with the help of textual features. Precisely, we analyze the user’s context dynamically from the micro-blogs and rank them accordingly by using a set of machine learning and natural language processing techniques. Curators extensive performance evaluation on a publicly available dataset show that it outperforms the competitive state-of-the-art by up to 154% on NDCG@5 and 105% on NDCG@25. The results also show that location is a salient feature in Curator." @default.
- W2897301114 created "2018-10-26" @default.
- W2897301114 creator A5018370354 @default.
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- W2897301114 date "2018-01-01" @default.
- W2897301114 modified "2023-09-27" @default.
- W2897301114 title "Curator: Enhancing Micro-Blogs Ranking by Exploiting User’s Context" @default.
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- W2897301114 doi "https://doi.org/10.1007/978-3-319-77116-8_26" @default.
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