Time-Aware Latent Concept Expansion for Microblog Search


  • Taiki Miyanishi Kobe University
  • Kazuhiro Seki Kobe University
  • Kuniaki Uehara Kobe University




Microblog Search, Latent Concept Expansion, Time-Aware Information Retrieval, Twitter


Incorporating the temporal property of words into query expansion methods based on relevance feedback has been shown to have a significant positive effect on microblog search.In contrast to such word-based query expansion methods, we propose a concept-based query expansion method based on a temporal relevance model that uses the temporal variation of concepts (e.g., terms and phrases) on microblogs. Our model naturally extends an extremely effective existing concept-based relevance model by tracking the concept frequency over time.Moreover, the proposed model produces important concepts that are frequently used within a particular time periodassociated with a given topic, which better discriminate between relevant and non-relevant microblog documents than words.Our experiments using a corpus of microblog data (Tweets2011 corpus) show that the proposed concept-based query expansion method improves search performance significantly, especially for highly relevant documents.




How to Cite

Miyanishi, T., Seki, K., & Uehara, K. (2014). Time-Aware Latent Concept Expansion for Microblog Search. Proceedings of the International AAAI Conference on Web and Social Media, 8(1), 366-375. https://doi.org/10.1609/icwsm.v8i1.14519