Multimodal KB Harvesting for Emerging Spatial Entities

Jinyoung Yeo, Hyunsouk Cho, Jin Woo Park, Seung Won Hwang

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


New entities are being created daily. Though the novelty of these entities naturally attracts mentions, due to lack of prior knowledge, it is more challenging to collect knowledge about such entities than pre-existing entities, whose KBs are comprehensively annotated through LBSNs and EBSNs. In this paper, we focus on knowledge harvesting for emerging spatial entities (ESEs), such as new businesses and venues, assuming we have only a list of ESE names. Existing techniques for knowledge base (KB) harvesting are primarily associated with information extraction from textual corpora. In contrast, we propose a multimodal method for event detection based on the complementary interaction of image, text, and user information between multi-source platforms, namely Flickr and Twitter. We empirically validate our harvesting approaches improve the quality of KB with enriched place and event knowledge.

Original languageEnglish
Article number7814228
Pages (from-to)1073-1086
Number of pages14
JournalIEEE Transactions on Knowledge and Data Engineering
Issue number5
Publication statusPublished - 2017 May 1

Bibliographical note

Funding Information:
This work was supported by Microsoft Research and the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-R2720-16-0007) supervised by the IITP (Institute for Information & communications Technology Promotion).

Publisher Copyright:
© 2017 IEEE.

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics


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