Supervised information retrieval for text and images

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2004

Author dc:creator

• Kyriakides, Alexandros, 1977-

Advisor dc:contributor.advisor

• Tomaso Poggio.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

en_US

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/28426

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/28426