Measuring the semantic relatedness between words and images

نویسندگان

  • Chee Wee Leong
  • Rada Mihalcea
چکیده

Measures of similarity have traditionally focused on computing the semantic relatedness between pairs of words and texts. In this paper, we construct an evaluation framework to quantify cross-modal semantic relationships that exist between arbitrary pairs of words and images. We study the effectiveness of a corpus-based approach to automatically derive the semantic relatedness between words and images, and perform empirical evaluations by measuring its correlation with human annotators.

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تاریخ انتشار 2011