Understanding Emerging Spatial Entities Through KB Harvesting
Keywords:
KB harvesting, Location based Social Networks, Event based Social Networks, Emerging Entity, Event DetectionAbstract
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
References
- S. Scellato, A. Noulas, R. Lambiotte, and C. Mascolo, “Socio-spatial properties of online location-based social networks.” ICWSM, 2011.
- E. Cho, S. A. Myers, and J. Leskovec, “Friendship and mobility: user movement in location-based social networks,” in SIGKDD, 2011.
- Z. Wu, Y. Song, and C. L. Giles, “Exploring multiple feature spaces for novel entity discovery,” in AAAI, 2016.
- K. Feng, G. Cong, S. S. Bhowmick, and S. Ma, “In search of influential event organizers in online social networks,” in SIGMOD, 2014.
- X. Liu, Q. He, Y. Tian, W.-C. Lee, J. McPherson, and J. Han, “Event-based social networks: linking the online and offline social worlds,” in SIGKDD, 2012.
- S. Unankard, X. Li, and M. A. Sharaf, “Emerging event detection in social networks with location sensitivity,” World Wide Web, vol. 18, no. 5, pp. 1393–1417, 2015.
- J. Allan, J. G. Carbonell, G. Doddington, J. Yamron, and Y. Yang, “Topic detection and tracking pilot study final report,” 1998.
- G. Tsatsaronis, I. Varlamis, M. Vazirgiannis, and K. Nørvåg, “Omiotis: A thesaurus-based measure of text relatedness,” in Machine Learning and Knowledge Discovery in Databases, 2009.
- A. Ritter, O. Etzioni, S. Clark et al., “Open domain event extraction from twitter,” in KDD, 2012.
- X.-J. Wang, Z. Xu, L. Zhang, C. Liu, and Y. Rui, “Towards indexing representative images on the web,” in MM, 2012.
- H. S. Packer, J. S. Hare, S. Samangooei, and P. Lewis, “Semantically tagging images of landmarks,” in KECSM, 2012.
- R. Srihari, C. Niu, and W. Li, “A hybrid approach for named entity and sub-type tagging,” in ACL, 2000.
- D. J. Crandall, L. Backstrom, D. Huttenlocher, and J. Kleinberg, “Map-ping the world’s photos,” in WWW, 2009.
- Y.-T. Zheng, M. Zhao, Y. Song, H. Adam, U. Buddemeier, A. Bissacco, F. Brucher, T.-S. Chua, and H. Neven, “Tour the world: building a web-scale landmark recognition engine,” in CVPR, 2009.
- F. Belém, E. Martins, T. Pontes, J. Almeida, and M. Gonçalves, “Associa-tive tag recommendation exploiting multiple textual features,” in SIGIR, 2011.
- T. Cheng, H. W. Lauw, and S. Paparizos, “Entity synonyms for structured web search,” In TKDE, 2012.
- K. Chakrabarti, S. Chaudhuri, T. Cheng, and D. Xin, “A framework for robust discovery of entity synonyms,” in SIGKDD, 2012
Downloads
Published
Issue
Section
License
Copyright (c) IJSRCSEIT

This work is licensed under a Creative Commons Attribution 4.0 International License.