A multimodal query expansion based on genetic programming for visually-oriented e-commerce applications

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Saraiva:2016:IPM,

• author = "Patricia C. Saraiva and Joao M. B. Cavalcanti and Edleno {S. de Moura} and Marcos A. Goncalves and Ricardo {da S. Torres}",
• title = "A multimodal query expansion based on genetic programming for visually-oriented e-commerce applications",
• journal = "Information Processing \& Management",
• year = "2016",
• ISSN = "0306-4573",
• DOI = "doi:10.1016/j.ipm.2016.03.001",
• URL = "http://www.sciencedirect.com/science/article/pii/S0306457316300206",
• abstract = "We present a novel multimodal query expansion strategy, based on genetic programming (GP), for image search in visually-oriented e-commerce applications. Our GP-based approach aims at both: learning to expand queries with multimodal information and learning to compute the {"}best{"} ranking for the expanded queries. However, different from previous work, the query is only expressed in terms of the visual content, which brings several challenges for this type of application. In order to evaluate the effectiveness of our method, we have collected two datasets containing images of clothing products taken from different online shops. Experimental results indicate that our method is an effective alternative for improving the quality of image search results when compared to a genetic programming system based only on visual information. Our method can achieve gains varying from 10.8percent against the strongest learning-to-rank baseline to 54percent against an adhoc specialized solution for the particular domain at hand.",
• keywords = "genetic algorithms, genetic programming, Content-based image retrieval, Multimodal query expansion, E-commerce",

}

Genetic Programming entries for Patricia Correia Saraiva Joao Marcos B Cavalcanti Edleno Silva de Moura Marcos Andre Goncalves Ricardo da Silva Torres

Citations