FRINK Linked Data Fragments server

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• W2891353368 abstract "In this paper, we study a new entity linking problem where both the entity mentions and the target entities are within a same social media platform. Compared with traditional entity linking problems that link mentions to a knowledge base, this new problem have less information about the target entities. However, if we can successfully link mentions to entities within a social media platform, we can improve a lot of applications such as comparative study in business intelligence and opinion leader finding. To study this problem, we constructed a dataset called Yelp-EL, where the business mentions in Yelp reviews are linked to their corresponding businesses on the platform. We conducted comprehensive experiments and analysis on this dataset with a learning to rank model that takes different types of features as input, as well as a few state-of-the-art entity linking approaches. Our experimental results show that two types of features that are not available in traditional entity linking: social features and location features, can be very helpful for this task." @default.
• W2891353368 created "2018-09-27" @default.
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• W2891353368 date "2018-01-01" @default.
• W2891353368 modified "2023-09-24" @default.
• W2891353368 title "Entity Linking within a Social Media Platform: A Case Study on Yelp" @default.
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• W2891353368 doi "https://doi.org/10.18653/v1/d18-1227" @default.
• W2891353368 hasPublicationYear "2018" @default.
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