Multimodal KB Harvesting for Emerging Spatial Entities

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...

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Bibliographic Details
Published inIEEE transactions on knowledge and data engineering Vol. 29; no. 5; pp. 1073 - 1086
Main Authors Yeo, Jinyoung, Cho, Hyunsouk, Park, Jin-Woo, Hwang, Seung-won
Format Journal Article
LanguageEnglish
Published New York IEEE 01.05.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Electronic publishing
emerging entity
Encyclopedias
event based social networks
event detection
Flickr
Harvesting
Image detection
Information retrieval
Internet
KB harvesting
Knowledge base
location based social networks
Twitter
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Summary: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.
ISSN:1041-4347
1558-2191
DOI:10.1109/TKDE.2017.2651805