Deep learning based web service recommendation methods: A survey

被引:2
|
作者
Mecheri, Karima [1 ]
Klai, Sihem [2 ]
Souici-Meslati, Labiba [1 ]
机构
[1] Badji Mokhtar Annaba Univ, Dept Comp Sci, LISCO Lab, POB 12, Annaba, Algeria
[2] Badji Mokhtar Annaba Univ, Dept Comp Sci, LABGED Lab, Annaba, Algeria
关键词
Deep learning; recommendation systems; web services; mashup; quality of service; performance evaluation metrics; NEURAL-NETWORK; AWARE; FACTORIZATION; PREDICTION; QUALITY;
D O I
10.3233/JIFS-224565
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Web service recommender systems have a fundamental role in the selection, composition and substitution of services. Indeed, they are used in several application areas such as Web APIs and Cloud Computing. Likewise, Deep Learning techniques have brought undeniable advantages and solutions to the challenges faced by recommendations in all areas. Unfortunately, the field of Web services has not yet benefited well from these deep methods, moreover, the works using these methods for Web services domain are very recent compared to the works of other fields. Thus, the objective of this paper is to study and analyze state-of-the-art work on Web services recommender systems based on Deep Learning techniques. This analysis will help readers wishing to work in this field, and allows us to direct our future work concerning the Web services recommendation by exploiting the advantages of Deep Learning techniques.
引用
收藏
页码:9879 / 9899
页数:21
相关论文
共 50 条
  • [1] Deep Learning Based Recommendation: A Survey
    Liu, Juntao
    Wu, Caihua
    INFORMATION SCIENCE AND APPLICATIONS 2017, ICISA 2017, 2017, 424 : 451 - 458
  • [2] SURVEY ON WEB SERVICE RECOMMENDATION BASED ON USER HISTORY
    Arunachalam, N.
    Amuthan, A.
    Sharmilla, M.
    Ushanandhini, K.
    2017 INTERNATIONAL CONFERENCE ON COMPUTATION OF POWER, ENERGY INFORMATION AND COMMUNICATION (ICCPEIC), 2017, : 305 - 309
  • [3] Combination service recommendation based on deep learning
    Huang, Li
    Zhao, Lu
    Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2024, 30 (09): : 3257 - 3273
  • [4] Interpretable web service recommendation based on disentangled representation learning
    Huang, Ying
    Cao, Zhiying
    Chen, Siyuan
    Zhang, Xiuguo
    Wang, Peipeng
    Cao, Qilei
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2023, 45 (01) : 133 - 145
  • [5] Personalized web service recommendation through mishmash technique and deep learning model
    Kumar, S. Ganesh
    Sridhar, S. S.
    Hussain, Azham
    Manikanthan, S., V
    Padmapriya, T.
    MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (07) : 9091 - 9109
  • [6] Personalized web service recommendation through mishmash technique and deep learning model
    S. Ganesh Kumar
    S. S. Sridhar
    Azham Hussain
    S. V. Manikanthan
    T. Padmapriya
    Multimedia Tools and Applications, 2022, 81 : 9091 - 9109
  • [7] Cross domain and adversarial learning based deep learning approach for web recommendation
    Asha, K. N.
    Rajkumar, R.
    INTERNATIONAL JOURNAL OF CRITICAL INFRASTRUCTURES, 2024, 20 (04) : 341 - 355
  • [8] Responsive and intelligent service recommendation method based on deep learning in cloud service
    Yu, Lei
    Duan, Yucong
    FRONTIERS IN GENETICS, 2022, 13
  • [9] A Survey of Lipreading Methods Based on Deep Learning
    Hao, Mingfeng
    Mamut, Mutelep
    Ubul, Kurban
    PROCEEDINGS OF 2020 2ND INTERNATIONAL CONFERENCE ON IMAGE PROCESSING AND MACHINE VISION AND INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION AND MACHINE LEARNING, IPMV 2020, 2020, : 31 - 39
  • [10] A Survey on Web Service Mining Using QoS and Recommendation Based on Multidimensional Approach
    Feddaoui, Ilhem
    Felhi, Faical
    Bergi, Imran Hassan
    Akaichi, Jalel
    INTELLIGENT INTERACTIVE MULTIMEDIA SYSTEMS AND SERVICES 2016, 2016, 55 : 439 - 450