Cross-domain and cross-modality transfer learning for multi-domain and multi-modality event detection

Zhenguo Yang, Min Cheng, Qing Li, Yukun Li, Zehang Lin, Wenyin Liu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)

Abstract

Online news media and social media are popular domains for people to acquire real-world event knowledge. In this work, the problem of multi-domain and multi-modality event detection (MMED) is elaborated. We wish to organize the multi-modality data from multiple domains based on real-world events. To this end, a cross-domain and cross-modality transfer learning (CDM) model is proposed. The CDM model aligns the data by exploiting a dictionary-based alignment strategy, and identifies the event labels of the data samples based on the class-specific reconstruction residual. Extensive experiments conducted on real-world data demonstrate the effectiveness of the proposed models. In particular, a benchmark dataset, denoted as MMED100, is released, which can hopefully be used to promote the research on this topic and advance related applications.

Original languageEnglish
Title of host publicationWeb Information Systems Engineering – WISE 2017 - 18th International Conference, Proceedings
EditorsLu Chen, Athman Bouguettaya, Andrey Klimenko, Fedor Dzerzhinskiy, Stanislav V. Klimenko, Xiangliang Zhang, Qing Li, Yunjun Gao, Weijia Jia
PublisherSpringer-Verlag
Pages516-523
Number of pages8
ISBN (Print)9783319687827
DOIs
Publication statusPublished - 1 Jan 2017
Externally publishedYes
Event18th International Conference on Web Information Systems Engineering, WISE 2017 - Puschino, Russian Federation
Duration: 7 Oct 201711 Oct 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10569 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Web Information Systems Engineering, WISE 2017
CountryRussian Federation
CityPuschino
Period7/10/1711/10/17

Keywords

  • Event detection
  • Multimedia analysis
  • Social media analytics
  • Transfer learning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this