Grammatical Evolution in a Matrix Factorization Recommender System
| Autor: | Matevž Kunaver, Iztok Fajfar |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
business.industry
Computer science 05 social sciences Genetic programming 010501 environmental sciences Recommender system Machine learning computer.software_genre 01 natural sciences Field (computer science) Matrix decomposition Grammatical evolution 0501 psychology and cognitive sciences Artificial intelligence business computer 050107 human factors 0105 earth and related environmental sciences |
| Zdroj: | Artificial Intelligence and Soft Computing ISBN: 9783319393773 ICAISC (1) |
| DOI: | 10.1007/978-3-319-39378-0_34 |
| Popis: | This paper presents preliminary results of using grammatical evolution to evolve expressions that calculate the user/item features used in the matrix factorization recommendation algorithm. The experiment was performed primarily to determine whether grammatical evolution can be applied to this field, and to compare the results with those of the ’traditional’ algorithm. For the purpose of the experiment, we used the CoMoDa dataset, which features realistic data collected over five years. The preliminary results are promising and offer a lot of possible future work, some of which is discussed at the end of the paper. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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