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Christos Anagnostopoulos, Kostas Kolomvatsos
2015 International Journal of Machine Learning and Cybernetics  
Both ML and CI could provide means for the creation of intelligent systems that will respond to user/application queries in the minimum time together with the highest possible performance.  ...  Drifts are detected by comparing two accuracies: (i) the accuracy of an ensemble on the recent examples, and (ii) the accuracy from the beginning of the learning process.  ...  Finally, in the last paper, Boratto, L. and Carta, S. present a set of group recommender systems that automatically detect groups of users by clustering them, in order to respect a constraint on the maximum  ... 
doi:10.1007/s13042-015-0429-3 fatcat:6ml6qxnwxvb33mbdvpu67rooey

Artificial intelligence in recommender systems

Qian Zhang, Jie Lu, Yaochu Jin
2020 Complex & Intelligent Systems  
recommender systems.  ...  It carefully surveys various issues related to recommender systems that use AI, and also reviews the improvements made to these systems through the use of such AI approaches as fuzzy techniques, transfer  ...  [163] built a fuzzy user-interest drift detection approach to deal with dynamic user preferences in rapidly changing big data, using fuzzy relationships to measure user-interest consistency.  ... 
doi:10.1007/s40747-020-00212-w fatcat:ev3cyoy2mjeuhmq3rymkx2shsy

A Preface to the Special Issue on Emerging and Intelligent Information Services

Maozhen Li, Zhijun Ding
2020 Computing and informatics  
In [6] Pang et al. focused on recommendation systems, and introduced stability variables and time-sensitive factors to solve the problem of user interest drift, and improve the accuracy of prediction.  ...  In [5], Zhang et al. considered the strength of user relationship, the similarity of entities, and the degree of user interest in recommendation systems.  ...  In [6] Pang et al. focused on recommendation systems, and introduced stability variables and time-sensitive factors to solve the problem of user interest drift, and improve the accuracy of prediction  ... 
doi:10.31577/cai_2020_1-2_1 fatcat:76usud75gvg73mfqtuii2dfoou

Application of Fuzzy Logic for User Classification in Personalized Web Search

Sendhilkumar S, Selvakumar K, Mahalakshmi G.S
2014 International Journal on Cybernetics & Informatics  
This work proposes a fuzzy based user classification model to suit a personalised web search environment.  ...  This fluctuating nature of user behaviour and user interest shall be well interpreted within a fuzzy setting. Prior to analysing user behaviour, nature of user interests has to be collected.  ...  A recommendation system based on fuzzy linguistic modelling has this approach as its core.  ... 
doi:10.5121/ijci.2014.3303 fatcat:ykw3nrbphvfcdg7mhdam3y7hgm

Research on English Movie Resource Information Mining Based on Dynamic Data Stream Classification

Jinhui Duan, Rui Gao, Chi-Hua Chen
2021 Security and Communication Networks  
Through the analysis of massive amounts of film and television data, the application system can effectively push the works that users may like.  ...  Secondly, we use the fuzzy neural network algorithm to conduct data mining on related film and television resource information.  ...  In other scenarios, the system can help users to find works that may be of interest through the information related to the movie plot.  ... 
doi:10.1155/2021/5518913 fatcat:dhyq7afstjdwpciozzgbfxq334

Recommender System Based on Temporal Models: A Systematic Review

Idris Rabiu, Naomie Salim, Aminu Da'u, Akram Osman
2020 Applied Sciences  
Over the years, the recommender systems (RS) have witnessed an increasing growth for its enormous benefits in supporting users' needs through mapping the available products to users based on their observed  ...  In this setting, however, more users, items and rating data are being constantly added to the system, causing several shifts in the underlying relationship between users and items to be recommended, a  ...  Introduction In recent times, the recommender systems (RS) have witnessed an increasing growth for its enormous benefits in supporting users' needs through mapping the available products to users based  ... 
doi:10.3390/app10072204 fatcat:4wxaa35kg5cvhnq57p3yn67uyq

Active Fuzzy Weighting Ensemble for Dealing with Concept Drift

Fan Dong, Jie Lu, Guangquan Zhang, Kan Li
2018 International Journal of Computational Intelligence Systems  
Once a drift is confirmed, it uses data instances accumulated by the drift detection method to create a new base classifier.  ...  Then, it applies fuzzy instance weighting and a dynamic voting strategy to organize all the existing base classifiers to construct an ensemble learning model.  ...  Data in non-stationary environments always involves concept drift and is a very pervasive phenomenon in real-world applications, such as changes in user interest in recommender systems, the emergence of  ... 
doi:10.2991/ijcis.11.1.33 fatcat:ewnhymmexjfxzdlg24qqgj24hu

Decremental Learning of Evolving Fuzzy Inference Systems Using a Sliding Window

Manuel Bouillon, Eric Anquetil, Abdullah Almaksour
2012 2012 11th International Conference on Machine Learning and Applications  
Our on-line recognizer is based on an evolving fuzzy inference system.  ...  system.  ...  This paper focuses on the decremental learning of such an evolving recognizer, based on a fuzzy inference system. The aim of decremental learning is twofold.  ... 
doi:10.1109/icmla.2012.110 dblp:conf/icmla/BouillonAA12 fatcat:m3phodua4bgcthoi5ktfrq44wu

Recommender Systems for Large-Scale Social Networks: A review of challenges and solutions

Magdalini Eirinaki, Jerry Gao, Iraklis Varlamis, Konstantinos Tserpes
2018 Future generations computer systems  
When this wealth of data is leveraged by recommender systems, the resulting coupling can help address interesting problems related to social engagement, member recruitment, and friend recommendations.  ...  In this work we review the various facets of large-scale social recommender systems, summarizing the challenges and interesting problems and discussing some of the solutions.  ...  Data volatility From the early works on recommender systems that capture the user interest drifts [69, 70] , to more recent works that model the dynamics of user interest in activity streams [71] , the  ... 
doi:10.1016/j.future.2017.09.015 fatcat:jdllbp6snfckfj7xfpu4xycfii

Recommender system application developments: A survey

Jie Lu, Dianshuang Wu, Mingsong Mao, Wei Wang, Guangquan Zhang
2015 Decision Support Systems  
A recommender system aims to provide users with personalized online product or service recommendations to handle the increasing online information overload problem and improve customer relationship management  ...  (such as e-business) and application platforms (such as mobile-based platforms).  ...  Concept drift techniques [175] should be introduced into recommender systems to model users' preference drift and improve the recommendation performance in a fast changing environment [176] .  ... 
doi:10.1016/j.dss.2015.03.008 fatcat:y4phvn677zaondsbjkn56orxt4

Recognizing Context-Aware Human Sociability Patterns Using Pervasive Monitoring for Supporting Mental Health Professionals

Ivan Rodrigues de Moura, Ariel Soares Teles, Markus Endler, Luciano Reis Coutinho, Francisco José da Silva e Silva
2020 Sensors  
As an alternative, we present a solution to detect context-aware sociability patterns and behavioral changes based on social situations inferred from ubiquitous device data.  ...  The proposed solution consists of an algorithm based on frequent pattern mining and complex event processing to detect periods of the day in which the individual usually socializes.  ...  Additionally, this solution recommends social exercises based on information on the intensity of social activities, time and location. Lane et al.  ... 
doi:10.3390/s21010086 pmid:33375630 fatcat:ruyavlolwfbg7aoslunazpseou

Exploiting Rating Abstention Intervals for Addressing Concept Drift in Social Network Recommender Systems

Dionisis Margaris, Costas Vassilakis
2018 Informatics  
Recommender systems are based on information about users' past behavior to formulate recommendations about their future actions.  ...  field of recommender systems.  ...  [31] present a novel method for detecting concept drift in a case-based reasoning system. They introduce a new competence model that detects differences through changes in competence.  ... 
doi:10.3390/informatics5020021 fatcat:b2y7s2yfvbhixad3ct4wip7ndy

Statistical Detection of Online Drifting Twitter Spam

Shigang Liu, Jun Zhang, Yang Xiang
2016 Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security - ASIA CCS '16  
We observe existing machine learning based detection methods suffer from the problem of Twitter spam drift, i.e., the statistical properties of spam tweets vary over time.  ...  The new method employs two new techniques, fuzzy-based redistribution and asymmetric sampling.  ...  Fuzzy-Based Redistribution To alleviate the imbalance between spam and non-spam classes in the training data, we develop a new fuzzy-based redistribution algorithm.  ... 
doi:10.1145/2897845.2897928 dblp:conf/ccs/Liu0X16 fatcat:rroswjq5drgs7imnoedrujr3ri

WebKDD 2005

Olfa Nasraoui, Osmar R. Zaïane, Myra Spiliopoulou, Bamshad Mobasher, Brij Masand, Philip S. YU
2005 SIGKDD Explorations  
In Heterogeneous Attribute Utility Model: A New Approach for Modeling User Profiles for Recommendation Systems, Schickel and Faltings made the case that both Collaborative filtering and Preference-based  ...  "How should an intelligent recommender system be designed to resist various malicious manipulations, such as schilling attacks that try to alter user ratings to influence the recommendations?"  ... 
doi:10.1145/1117454.1117475 fatcat:kd2fftl6n5dc7cen5ssvqeq6zm

Intelligent Health Recommendation System for Computer Users [article]

Qi Guo, Zixuan Wang, Ming Li, Hamid Aghajan
2015 arXiv   pre-print
When combining these visual cues, a system of intelligent personal assistants for computer users is proposed.  ...  By means of non-rigid face tracking system, data are analyzed to determine the 3D head pose, blink rate and yawn frequency of computer users.  ...  [14] proposed a kerneled fuzzy rough sets based yawn detection algorithm.  ... 
arXiv:1504.07858v1 fatcat:hhjwzjsygbbqtklcccixyhpc2q
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