Abstract
A large portion of news articles contains images of persons whose names appear in the news stories. To provide image search of persons, most search engines construct an index from textual descriptions (such as headline and caption) of images. The index search approach, although very simple and scalable, has one serious drawback. A query of a person name could match some news articles which do not contain images of the target person. Therefore, some irrelevant images could be returned as search results. Our main goal is to improve the performance of the index search approach based on the syntactic analysis of person name entities in the news articles. Given sentences containing person names, we construct a set of syntactic rules for identifying persons in news images. The set of syntactic rules is used to filter out images of non-target persons from the results returned by the index search. From the experimental results, our approach improved the performance over the basic index search by 10% based on the F1-measure.
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Haruechaiyasak, C., Damrongrat, C. (2010). Identifying Persons in News Article Images Based on Textual Analysis. In: Chowdhury, G., Koo, C., Hunter, J. (eds) The Role of Digital Libraries in a Time of Global Change. ICADL 2010. Lecture Notes in Computer Science, vol 6102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13654-2_27
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DOI: https://doi.org/10.1007/978-3-642-13654-2_27
Publisher Name: Springer, Berlin, Heidelberg
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