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Implicit Linking of Food Entities in Social Media

  • Wen-Haw ChongEmail author
  • Ee-Peng Lim
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11053)

Abstract

Dining is an important part in people’s lives and this explains why food-related microblogs and reviews are popular in social media. Identifying food entities in food-related posts is important to food lover profiling and food (or restaurant) recommendations. In this work, we conduct Implicit Entity Linking (IEL) to link food-related posts to food entities in a knowledge base. In IEL, we link posts even if they do not contain explicit entity mentions. We first show empirically that food venues are entity-focused and associated with a limited number of food entities each. Hence same-venue posts are likely to share common food entities. Drawing from these findings, we propose an IEL model which incorporates venue-based query expansion of test posts and venue-based prior distributions over entities. In addition, our model assigns larger weights to words that are more indicative of entities. Our experiments on Instagram captions and food reviews shows our proposed model to outperform competitive baselines.

Keywords

Entity linking Food entities Query expansion 

Notes

Acknowledgments

This research is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its International Research Centres in Singapore Funding Initiative, and DSO National Laboratories.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Singapore Management UniversitySingaporeSingapore

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