Typology of Personalization in Recommender Systems
Purpose: With the development of science and technology, large volumes of structured, semi-structured, and unstructured data are generated daily at breakneck speeds from various sources. This data generated by different users share many common patterns that can be filtered and analyzed to make recom...
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| Format: | Article |
| Language: | fas |
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Ayandegan Institute of Higher Education, Tonekabon,
2022-05-01
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| Series: | مدیریت نوآوری و راهبردهای عملیاتی |
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| Online Access: | http://www.journal-imos.ir/article_137336_b477c29e386e9d8a9d9c70e359d1544c.pdf |
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| _version_ | 1832577791592235008 |
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| author | Marziyeh Nourahmadi Hojjatollah Sadeqi |
| author_facet | Marziyeh Nourahmadi Hojjatollah Sadeqi |
| author_sort | Marziyeh Nourahmadi |
| collection | DOAJ |
| description | Purpose: With the development of science and technology, large volumes of structured, semi-structured, and unstructured data are generated daily at breakneck speeds from various sources. This data generated by different users share many common patterns that can be filtered and analyzed to make recommendations for a product, goods, or service of interest to users. Recommender systems are software tools that provide suggestions to users based on their needs. One of the critical issues in recommender systems is providing personalized advice that fits the users' mood.Methodology: In this research, with a bibliometric approach using the bibliometric library in R software, all the research done on applying recommended systems in personalization is reviewed.Findings: Using the bibliometrics approach while defining recommender systems and their types, we presented an overview of the personalization field and different kinds of personalization. We also discussed the personalization process and described recommender systems as an integral part. Then, the challenges of implementing recommendation systems will be discussed, and finally, the areas in which the problem of personalization of recommendation systems can be raised.Originality/Value: The present study, with a comprehensive review of all research in this field, can help researchers imagine and select appropriate methods for classifying and analyzing data as a toolbox for using recommender systems in personalization. |
| format | Article |
| id | doaj-art-1832f51f4dad4b569853554d94acaa5f |
| institution | Kabale University |
| issn | 2783-1345 2717-4581 |
| language | fas |
| publishDate | 2022-05-01 |
| publisher | Ayandegan Institute of Higher Education, Tonekabon, |
| record_format | Article |
| series | مدیریت نوآوری و راهبردهای عملیاتی |
| spelling | doaj-art-1832f51f4dad4b569853554d94acaa5f2025-01-30T14:55:45ZfasAyandegan Institute of Higher Education, Tonekabon,مدیریت نوآوری و راهبردهای عملیاتی2783-13452717-45812022-05-0131123110.22105/imos.2021.290478.1117137336Typology of Personalization in Recommender SystemsMarziyeh Nourahmadi0Hojjatollah Sadeqi1Department of Financial Engineering, Faculty of Economic, Management and Accounting, Yazd University, Yazd, Iran.Department of Finance and Accounting, Faculty of Management and Economics, Yazd University, Yazd, Iran.Purpose: With the development of science and technology, large volumes of structured, semi-structured, and unstructured data are generated daily at breakneck speeds from various sources. This data generated by different users share many common patterns that can be filtered and analyzed to make recommendations for a product, goods, or service of interest to users. Recommender systems are software tools that provide suggestions to users based on their needs. One of the critical issues in recommender systems is providing personalized advice that fits the users' mood.Methodology: In this research, with a bibliometric approach using the bibliometric library in R software, all the research done on applying recommended systems in personalization is reviewed.Findings: Using the bibliometrics approach while defining recommender systems and their types, we presented an overview of the personalization field and different kinds of personalization. We also discussed the personalization process and described recommender systems as an integral part. Then, the challenges of implementing recommendation systems will be discussed, and finally, the areas in which the problem of personalization of recommendation systems can be raised.Originality/Value: The present study, with a comprehensive review of all research in this field, can help researchers imagine and select appropriate methods for classifying and analyzing data as a toolbox for using recommender systems in personalization.http://www.journal-imos.ir/article_137336_b477c29e386e9d8a9d9c70e359d1544c.pdfpersonalizationrecommender systemsuser personalitybibliometrics approach |
| spellingShingle | Marziyeh Nourahmadi Hojjatollah Sadeqi Typology of Personalization in Recommender Systems مدیریت نوآوری و راهبردهای عملیاتی personalization recommender systems user personality bibliometrics approach |
| title | Typology of Personalization in Recommender Systems |
| title_full | Typology of Personalization in Recommender Systems |
| title_fullStr | Typology of Personalization in Recommender Systems |
| title_full_unstemmed | Typology of Personalization in Recommender Systems |
| title_short | Typology of Personalization in Recommender Systems |
| title_sort | typology of personalization in recommender systems |
| topic | personalization recommender systems user personality bibliometrics approach |
| url | http://www.journal-imos.ir/article_137336_b477c29e386e9d8a9d9c70e359d1544c.pdf |
| work_keys_str_mv | AT marziyehnourahmadi typologyofpersonalizationinrecommendersystems AT hojjatollahsadeqi typologyofpersonalizationinrecommendersystems |