Personalized Sliding Window Recommendation Algorithm Based on Sequence Alignment
With the explosive growth of the amount of information in social networks, the recommendation system, as an application of social networks, has attracted widespread attention in recent years on how to obtain user-interested content in massive data. At present, in the process of algorithm design of t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/24/11/1662 |
| _version_ | 1827644478816518144 |
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| author | Lei Zhou Bolun Chen Hu Liu Liuyang Wang |
| author_facet | Lei Zhou Bolun Chen Hu Liu Liuyang Wang |
| author_sort | Lei Zhou |
| collection | DOAJ |
| description | With the explosive growth of the amount of information in social networks, the recommendation system, as an application of social networks, has attracted widespread attention in recent years on how to obtain user-interested content in massive data. At present, in the process of algorithm design of the recommending system, most methods ignore structural relationships between users. Therefore, in this paper, we designed a personalized sliding window for different users by combining timing information and network topology information, then extracted the information sequence of each user in the sliding window and obtained the similarity between users through sequence alignment. The algorithm only needs to extract part of the data in the original dataset, and the time series comparison shows that our method is superior to the traditional algorithm in recommendation Accuracy, Popularity, and Diversity. |
| first_indexed | 2024-03-09T18:20:12Z |
| format | Article |
| id | doaj.art-0ba5b375436243a8a4d29d2694fb545a |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-09T18:20:12Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-0ba5b375436243a8a4d29d2694fb545a2023-11-24T08:18:49ZengMDPI AGEntropy1099-43002022-11-012411166210.3390/e24111662Personalized Sliding Window Recommendation Algorithm Based on Sequence AlignmentLei Zhou0Bolun Chen1Hu Liu2Liuyang Wang3Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian 223003, ChinaFaculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian 223003, ChinaFaculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian 223003, ChinaFaculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian 223003, ChinaWith the explosive growth of the amount of information in social networks, the recommendation system, as an application of social networks, has attracted widespread attention in recent years on how to obtain user-interested content in massive data. At present, in the process of algorithm design of the recommending system, most methods ignore structural relationships between users. Therefore, in this paper, we designed a personalized sliding window for different users by combining timing information and network topology information, then extracted the information sequence of each user in the sliding window and obtained the similarity between users through sequence alignment. The algorithm only needs to extract part of the data in the original dataset, and the time series comparison shows that our method is superior to the traditional algorithm in recommendation Accuracy, Popularity, and Diversity.https://www.mdpi.com/1099-4300/24/11/1662personalized sliding windowrecommendation algorithmsequence alignment |
| spellingShingle | Lei Zhou Bolun Chen Hu Liu Liuyang Wang Personalized Sliding Window Recommendation Algorithm Based on Sequence Alignment Entropy personalized sliding window recommendation algorithm sequence alignment |
| title | Personalized Sliding Window Recommendation Algorithm Based on Sequence Alignment |
| title_full | Personalized Sliding Window Recommendation Algorithm Based on Sequence Alignment |
| title_fullStr | Personalized Sliding Window Recommendation Algorithm Based on Sequence Alignment |
| title_full_unstemmed | Personalized Sliding Window Recommendation Algorithm Based on Sequence Alignment |
| title_short | Personalized Sliding Window Recommendation Algorithm Based on Sequence Alignment |
| title_sort | personalized sliding window recommendation algorithm based on sequence alignment |
| topic | personalized sliding window recommendation algorithm sequence alignment |
| url | https://www.mdpi.com/1099-4300/24/11/1662 |
| work_keys_str_mv | AT leizhou personalizedslidingwindowrecommendationalgorithmbasedonsequencealignment AT bolunchen personalizedslidingwindowrecommendationalgorithmbasedonsequencealignment AT huliu personalizedslidingwindowrecommendationalgorithmbasedonsequencealignment AT liuyangwang personalizedslidingwindowrecommendationalgorithmbasedonsequencealignment |