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Improving Music Recommendation in Session-Based Collaborative Filtering by Using Temporal Context

Ricardo Dias, Manuel J. Fonseca
2013 2013 IEEE 25th International Conference on Tools with Artificial Intelligence  
In this work, we explore the usage of temporal context and session diversity in Session-based Collaborative Filtering techniques for music recommendation.  ...  Music recommendation systems based on Collaborative Filtering methods have been extensively developed over the last years.  ...  APPLYING TEMPORAL CONTEXT ON SESSION-BASED COLLABORATIVE FILTERING ALGORITHMS Music recommendation systems relying on content-based methods or collaborative filtering, rarely take time into account, something  ... 
doi:10.1109/ictai.2013.120 dblp:conf/ictai/DiasF13 fatcat:jp7okcj2fzd4lh7t5gjjbr5efi

A Neighbor-guided Memory-based Neural Network for Session-aware Recommendation

Yupu Guo, Yanxiang Ling, Honghui Chen
2020 IEEE Access  
Session-aware recommendation is a special form of session-based recommendation, where users' historical interactions before the current session are available.  ...  To tackle the above problems, we propose a neighbor-guided memory-based neural network (MNN) for session-aware recommendation task, which comprehensively considers users' short-term intent, long-term preference  ...  ., Neighbor-guided Memory-based Neural Network for session-aware recommendation task.  ... 
doi:10.1109/access.2020.3006360 fatcat:64dyzhwwnjdnllzlcic2k2vqt4

Accurate web recommendations based on profile-specific url-predictor neural networks

Olfa Nasraoui, Mrudula Pavuluri
2004 Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters - WWW Alt. '04  
While most recommenders are inherently context sensitive, our approach is context ultrasensitive because a different recommendation model is designed for each profile separately.  ...  We present a Context Ultra-Sensitive Approach based on two-step Recommender systems . Our approach relies on a committee of profile-specific neural networks.  ...  However, k-NN is notorious for its high computational and memory costs at recommendation time.  ... 
doi:10.1145/1013367.1013445 dblp:conf/www/NasraouiP04 fatcat:3ttcafl6q5fl7n6auf7txw3d2a

Accurate web recommendations based on profile-specific url-predictor neural networks

Olfa Nasraoui, Mrudula Pavuluri
2004 Alternate track papers & posters of the 13th international conference on World Wide Web - WWW Alt. '04  
While most recommenders are inherently context sensitive, our approach is context ultrasensitive because a different recommendation model is designed for each profile separately.  ...  We present a Context Ultra-Sensitive Approach based on two-step Recommender systems . Our approach relies on a committee of profile-specific neural networks.  ...  However, k-NN is notorious for its high computational and memory costs at recommendation time.  ... 
doi:10.1145/1010432.1010510 fatcat:j43piadnxngh7gr5zkpv5a2ihm

Preserving Privacy in Web Recommender Systems [chapter]

Ranieri Baraglia, Claudio Lucchese, Salvatore Orlando, Raffaele Perego, Fabrizio Silvestri
2010 Chapman & Hall/CRC Data Mining and Knowledge Discovery Series  
The knowledge base on which the model used for making recommendations is built, is incrementally updated without tracking user sessions.  ...  In this case, users may adopt techniques that avoid server-based session reconstruction, and that do not worsen the accuracy of the model extracted by πSUGGEST.  ...  Therefore, the server component of πSUGGEST is not aware of the user sensitive data, i.e. identity and sessions, but still it can build a model for the generation of good recommendations.  ... 
doi:10.1201/b10373-22 fatcat:ja73n4duv5gx5m3zsndo33kgvi

Time Weight Content-based Extensions of Temporal Graphs for Personalized Recommendation

Armel Jacques Nzekon Nzeko'o, Maurice Tchuente, Matthieu Latapy
2017 Proceedings of the 13th International Conference on Web Information Systems and Technologies  
The Session-based Temporal Graph (STG) has been proposed by Xiang et al. to provide temporal recommendations by combining long-and short-term preferences.  ...  Recommender systems are an answer to information overload on the web. They filter and present to customer, a small subset of items that he is most likely to be interested in.  ...  Finally, we present some graph-based recommender systems. Time aware recommender systems Ding et al.  ... 
doi:10.5220/0006288202680275 dblp:conf/webist/NzekooTL17 fatcat:pxy6nepxyzebhnmyrwinijuvi4

Survey on Recommendation of Personalized Travel Sequence

Mayuri D. Aswale, Dr. Dharmadhikari S. C.
2017 IJARCCE  
It recommends personalized users travel interest and recommend a sequence of travel interest instead of an individual point of interest.  ...  Now a day, traveling recommendation is important for user who is the plan for traveling. There are many existing techniques which are used for travel recommendation.  ...  Significance in recommending sequential activities. It not considering longer check-in sessions Using trajectories for collaborative filtering-based POI Recommendation. H.  ... 
doi:10.17148/ijarcce.2017.6122 fatcat:lwfeqtmakbcoxke5uqn3ut4od4

TLSAN: Time-aware Long- and Short-term Attention Network for Next-item Recommendation

Jianqing Zhang, Dongjing Wang, Dongjin Yu
2021 Neurocomputing  
Recently, deep neural networks are widely applied in recommender systems for their effectiveness in capturing/modeling users' preferences.  ...  Firstly, TLSAN models "personalized time-aggregation" and learn user-specific temporal taste via trainable personalized time position embeddings with category-aware correlations in long-term behaviors.  ...  Conclusion and Future Work In summary, we propose a new model: Time-aware Long-and Short-term Attention Network (TLSAN), which recommends the next most suitable item for the target users based on their  ... 
doi:10.1016/j.neucom.2021.02.015 fatcat:53ktosol6bgsdk34y7tycr76qu

FairRec: Fairness-aware News Recommendation with Decomposed Adversarial Learning [article]

Chuhan Wu, Fangzhao Wu, Xiting Wang, Yongfeng Huang, Xing Xie
2021 arXiv   pre-print
user interest information for fairness-aware news recommendation.  ...  News recommendation is important for online news services. Existing news recommendation models are usually learned from users' news click behaviors.  ...  attribute-independent user interest information for making fairness-aware news recommendation.  ... 
arXiv:2006.16742v2 fatcat:ajuqjjwowvgahn6pda5zrfv24y

Cultural adaptation of cognitive behaviour therapy for depression: a qualitative study exploring views of patients and practitioners from India

Sayma Jameel, Manjula Munivenkatappa, Shyam Sundar Arumugham, K Thennarasu
2022 The Cognitive Behaviour Therapist  
The present study is an attempt to explore the views of patients and therapists in India by following an evidence-based approach that focuses on three areas for adaptation: (1) awareness of relevant cultural  ...  Culturally sensitive assessment and formulation with minor adaptation in clinical practice was recommended.  ...  We thank the therapists and the patients who participated in the study for their time and contribution.  ... 
doi:10.1017/s1754470x22000137 fatcat:epquv4lfhzdhtosprkb3k2y67u

Time-weighted Attentional Session-Aware Recommender System [article]

Mei Wang, Weizhi Li, Yan Yan
2019 arXiv   pre-print
Session-based Recurrent Neural Networks (RNNs) are gaining increasing popularity for recommendation task, due to the high autocorrelation of user's behavior on the latest session and the effectiveness  ...  And then, our ASARS framework promotes two novel models: (1) an inter-session temporal dynamic model that captures the long-term user interaction for RNN recommender system.  ...  Obviously, the global attention model for dwelling time helps more in session-based RNN model.  ... 
arXiv:1909.05414v1 fatcat:wprgje6jsbh33a4djewf3r5qda

Access control management in a distributed environment supporting dynamic collaboration

Basit Shafiq, Elisa Bertino, Arif Ghafoor
2005 Proceedings of the 2005 workshop on Digital identity management - DIM '05  
The paper discusses these issues in detail and presents a framework for access control and trust management in a distributed collaborative environment.  ...  Specification of access control requirements for dynamic collaboration is challenging mainly because of the limited or lack of knowledge about remote users' identities and affiliations.  ...  The work reported in this paper has been partially sponsored by the National Science Foundation under the ITR Grant No. 0428554 "The Design and Use of Digital Identities" and by the sponsors of Center for  ... 
doi:10.1145/1102486.1102503 dblp:conf/dim/ShafiqBG05 fatcat:lyoobqr7hjalbjxldkktnte56i

Classification of the User's Intent Detection in Ecommerce systems – Survey and Recommendations

Marek Koniew, Institute of Informatics, Silesian University of Technology, Gliwice, Poland
2020 International Journal of Information Engineering and Electronic Business  
interests handling.  ...  We find that various aspects of customer intent detection can be tackled by leveraging tremendous recent recommendation systems' progress.  ...  For instance, Phuong et al. [50] propose a way to combine Collaborative Filtering (CF) and session-based profile to incorporate more context into the model.  ... 
doi:10.5815/ijieeb.2020.06.01 fatcat:zcooazhm2jcqfmmegq7syyj7oq

Mobile Multimedia Recommendation in Smart Communities: A Survey [article]

Feng Xia, Nana Yaw Asabere, Ahmedin Mohammed Ahmed, Jing Li, Xiangjie Kong
2013 arXiv   pre-print
Mobile device users usually store and use multimedia contents based on their personal interests and preferences.  ...  In order to tackle this problem, researchers have developed various techniques that recommend multimedia for mobile users.  ...  Collaborative recommendations can be grouped into two general classes: memory-based and model-based.  ... 
arXiv:1312.6565v1 fatcat:myep75jg4fcvhgscrxjmouoksm

Diversification in Session-based News Recommender Systems [article]

Alireza Gharahighehi, Celine Vens
2021 arXiv   pre-print
In this study we propose scenarios to make these session-based recommender systems diversity-aware and to address the filter bubble phenomenon.  ...  In this context, session-based recommenders are able to recommend next items given the sequence of previous items in the active session.  ...  .: Sequence and time aware neigh- borhood for session-based recommendations: Stan.  ... 
arXiv:2102.03265v1 fatcat:bzougwfvwvflheogd5x55m5ai4
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