Academic literature on the topic 'Sequence-aware recommender system'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Sequence-aware recommender system.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Sequence-aware recommender system"
Zha, Yongfu, Yongjian Zhang, Zhixin Liu, and Yumin Dong. "Self-Attention Based Time-Rating-Aware Context Recommender System." Computational Intelligence and Neuroscience 2022 (September 17, 2022): 1–10. http://dx.doi.org/10.1155/2022/9288902.
Full textSun, Ninghua, Tao Chen, Longya Ran, and Wenshan Guo. "Dynamic and Static Features-Aware Recommendation with Graph Neural Networks." Computational Intelligence and Neuroscience 2022 (April 21, 2022): 1–11. http://dx.doi.org/10.1155/2022/5484119.
Full textQuadrana, Massimo, Paolo Cremonesi, and Dietmar Jannach. "Sequence-Aware Recommender Systems." ACM Computing Surveys 51, no. 4 (September 6, 2018): 1–36. http://dx.doi.org/10.1145/3190616.
Full textXu, Yanan, Yanmin Zhu, and Jiadi Yu. "Modeling Multiple Coexisting Category-Level Intentions for Next Item Recommendation." ACM Transactions on Information Systems 39, no. 3 (May 6, 2021): 1–24. http://dx.doi.org/10.1145/3441642.
Full textMahmud, Umar. "UML based Model of a Context Aware System." International Journal of Advanced Pervasive and Ubiquitous Computing 7, no. 1 (January 2015): 1–16. http://dx.doi.org/10.4018/ijapuc.2015010101.
Full textWu, Shiwen, Yuanxing Zhang, Chengliang Gao, Kaigui Bian, and Bin Cui. "GARG: Anonymous Recommendation of Point-of-Interest in Mobile Networks by Graph Convolution Network." Data Science and Engineering 5, no. 4 (July 29, 2020): 433–47. http://dx.doi.org/10.1007/s41019-020-00135-z.
Full textQiu, Ruihong, Zi Huang, Tong Chen, and Hongzhi Yin. "Exploiting Positional Information for Session-Based Recommendation." ACM Transactions on Information Systems 40, no. 2 (April 30, 2022): 1–24. http://dx.doi.org/10.1145/3473339.
Full textLevitan, Michael M., Gary E. Crawford, and Andrew Hardwick. "Practical Considerations for Pressure-Rate Deconvolution of Well Test Data." SPE Journal 11, no. 01 (March 1, 2006): 35–47. http://dx.doi.org/10.2118/90680-pa.
Full textKala, K. U., and M. Nandhini. "Context-Category Specific sequence aware Point-Of-Interest Recommender System with Multi-Gated Recurrent Unit." Journal of Ambient Intelligence and Humanized Computing, December 9, 2019. http://dx.doi.org/10.1007/s12652-019-01583-w.
Full textLiu, Xiao, Bonan Gao, Basem Suleiman, Han You, Zisu Ma, Yu Liu, and Ali Anaissi. "Privacy-Preserving Personalized Fitness Recommender System ( P 3 FitRec ) : A Multi-level Deep Learning Approach." ACM Transactions on Knowledge Discovery from Data, January 13, 2023. http://dx.doi.org/10.1145/3572899.
Full textBooks on the topic "Sequence-aware recommender system"
1st, Kala K. U., and Nandhini M. 2nd. Deep Learning Model for Categorical Context Adaptation in Sequence-Aware Recommender Systems. INSC International Publisher (IIP), 2021.
Find full textBook chapters on the topic "Sequence-aware recommender system"
Kala, K. U., and M. Nandhini. "Two-Way Sequence Modeling for Context-Aware Recommender Systems with Multiple Interactive Bidirectional Gated Recurrent Unit." In Lecture Notes in Electrical Engineering, 129–37. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2612-1_12.
Full textZhou, Mingming, and Yabo Xu. "Challenges to Use Recommender Systems to Enhance Meta-Cognitive Functioning in Online Learners." In Educational Recommender Systems and Technologies, 282–301. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-61350-489-5.ch012.
Full textZhou, Mingming, and Yabo Xu. "Challenges to Use Recommender Systems to Enhance Meta-Cognitive Functioning in Online Learners." In Data Mining, 1916–35. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2455-9.ch099.
Full textConference papers on the topic "Sequence-aware recommender system"
Quadrana, Massimo, Paolo Cremonesi, and Dietmar Jannach. "Sequence-aware Recommender Systems." In UMAP '18: 26th Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3209219.3209270.
Full textQuadrana, Massimo, and Paolo Cremonesi. "Sequence-aware recommendation." In RecSys '18: Twelfth ACM Conference on Recommender Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3240323.3241621.
Full textQuadrana, Massimo, Dietmar Jannach, and Paolo Cremonesi. "Tutorial: Sequence-Aware Recommender Systems." In WWW '19: The Web Conference. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3308560.3320091.
Full textFelicioni, Nicolò, Andrea Donati, Luca Conterio, Luca Bartoccioni, Davide Yi Xian Hu, Cesare Bernardis, and Maurizio Ferrari Dacrema. "Multi-Objective Blended Ensemble For Highly Imbalanced Sequence Aware Tweet Engagement Prediction." In RecSys Challenge '20: Proceedings of the Recommender Systems Challenge 2020. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3415959.3415998.
Full text