Supervised information retrieval for text and images

Abstract

We present a novel approach to choosing an appropriate image for a news story. Our method uses the caption of the image to retrieve a suitable image. We have developed a word-extraction engine called WordEx. WordEx uses supervised learning to predict which words in the text of a news story are likely to be present in the caption of an appropriate image. The words extracted by WordEx are then used to retrieve the image from a collection of images. On average, the number of words extracted by WordEx is 10% of the original story text. Therefore, this word-extraction engine can also be applied to text documents for feature reduction.