News contextualization with geographic and visual information

  • Authors:

  • Zechao Li;Meng Wang;Jing Liu;Changsheng Xu;Hanqing Lu

  • Affiliations:

  • Institute of Automation, Chinese Academy of Sciences, Beijing, China;School of Computing, National University of Singapore, Singapore, Singapore;Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Automation, Chinese Academy of Sciences, Beijing, China

  • Venue:
  • MM '11 Proceedings of the 19th ACM international conference on Multimedia
  • Year:
  • 2011

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Abstract

In this paper, we investigate the contextualization of news documents with geographic and visual information. We propose a matrix factorization approach to analyze the location relevance for each news document. We also propose a method to enrich the document with a set of web images. For location relevance analysis, we first perform toponym extraction and expansion to obtain a toponym list from news documents. We then propose a matrix factorization method to estimate the location-document relevance scores while simultaneously capturing the correlation of locations and documents. For image enrichment, we propose a method to generate multiple queries from each news document for image search and then employ an intelligent fusion approach to collect a set of images from the search results. Based on the location relevance analysis and image enrichment, we introduce a news browsing system named NewsMap which can support users in reading news via browsing a map and retrieving news with location queries. The news documents with the corresponding enriched images are presented to help users quickly get information. Extensive experiments demonstrate the effectiveness of our approaches.