A Comparative Study of Ensemble Techniques Based on Genetic Programming: A Case Study in Semantic Similarity Assessment

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@Article{DBLP:journals/ijseke/Gil23,

• author = "Jorge Martinez-Gil",
• title = "A Comparative Study of Ensemble Techniques Based on Genetic Programming: A Case Study in Semantic Similarity Assessment",
• journal = "International Journal of Software Engineering and Knowledge Engineering",
• volume = "33",
• number = "2",
• pages = "289--312",
• year = "2023",
• month = feb,
• keywords = "genetic algorithms, genetic programming, Cartesian Genetic Programming, Ensemble learning, semantic similarity measurement",
• ISSN = "0218-1940",
• URL = "https://doi.org/10.1142/S0218194022500772",
• DOI = "doi:10.1142/S0218194022500772",
• timestamp = "Sat, 29 Apr 2023 01:00:00 +0200",
• biburl = "https://dblp.org/rec/journals/ijseke/Gil23.bib",
• bibsource = "dblp computer science bibliography, https://dblp.org",
• size = "24 pages",
• abstract = "The challenge of assessing semantic similarity between pieces of text through computers has attracted considerable attention from industry and academia. New advances in neural computation have developed very sophisticated concepts, establishing a new state of the art in this respect. we go one step further by proposing new techniques built on the existing methods. To do so, we bring to the table the stacking concept that has given such good results and propose a new architecture for ensemble learning based on genetic programming. As there are several possible variants, we compare them all and try to establish which one is the most appropriate to achieve successful results in this context. Analysis of the experiments indicates that Cartesian Genetic Programming seems to give better average results.",
• notes = "Software Competence Center Hagenberg GmbH, Softwarepark 32a, 4232 Hagenberg, Austria",

}

Genetic Programming entries for Jorge Martinez-Gil

Citations