Keyphrase Extraction using Textual and Visual Features

نویسندگان

  • Yaakov HaCohen-Kerner
  • Stefanos Vrochidis
  • Dimitris Liparas
  • Anastasia Moumtzidou
  • Yiannis Kompatsiaris
چکیده

Many current documents include multimedia consisting of text, images and embedded videos. This paper presents a general method that uses Random Forests to automatically extract keyphrases that can be used as very short summaries and to help in retrieval, classification and clustering processes.

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تاریخ انتشار 2014