The Photo News Flusher: A Photo-News Clustering Browser

نویسندگان

  • Tatsuya Iyota
  • Keiji Yanai
چکیده

We propose a novel news browsing system that can cluster photo news articles based on both textual features of articles and image features of news photos for a personal news database which is built by accumulating Web photo news articles. The system provides two types of clustering methods: normal clustering and thread-style clustering. It enables us to browse news articles over several weeks or months visually and find out useful news easily. In this paper, we describe an overview of our system, some examples of uses and user studies.

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تاریخ انتشار 2007