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Exploiting User Preference for Online Learning in Web Content Optimization Systems

Jiang Bian, Bo Long, Lihong Li, Taesup Moon, Anlei Dong, Yi Chang
2014 ACM Transactions on Intelligent Systems and Technology  
To address these problems, we propose to explore a new dynamic pairwise learning methodology for Web portal content optimization, in which we exploit dynamic user preferences extracted based on users'  ...  To attract more users to various content modules on the Web portal, it is necessary to design a recommender system that can effectively achieve Web portal content optimization by automatically estimating  ...  To summarize, our specific contributions include: -A general pairwise learning methodology that exploits dynamic user preferences for online learning in the Web content optimization system.  ... 
doi:10.1145/2493259 fatcat:qp4lvhadrbhstbafchk4rigrgy

Reinforcement Learning for Online Information Seeking [article]

Xiangyu Zhao and Long Xia and Jiliang Tang and Dawei Yin
2019 arXiv   pre-print
In this paper, we give an overview of deep reinforcement learning for search, recommendation, and online advertising from methodologies to applications, review representative algorithms, and discuss some  ...  Search, recommendation, and online advertising are the three most important information-providing mechanisms on the web.  ...  Exploitation/Exploration Dilemma Traditional recommender systems suffer from the exploitation-exploration dilemma, where exploitation is to recommend items that are predicted to best match users' preferences  ... 
arXiv:1812.07127v4 fatcat:pyc75g5hufcs5b3f75gonbkp24

Web Information Personalization: Challenges and Approaches [chapter]

Cyrus Shahabi, Yi-Shin Chen
2003 Lecture Notes in Computer Science  
To date, recommendation systems and personalized web search systems are the most successful examples of Web personalization.  ...  To alleviate this problem, personalization becomes a popular remedy to customize the Web environment towards a user's preference.  ...  In order to improve the accuracy of returned results, researchers proposed different techniques for incorporating user preferences into metasearch systems.  ... 
doi:10.1007/978-3-540-39845-5_2 fatcat:bzlhauh3a5altctfwda6jab4qe

Exploiting Reinforcement Learning to Profile Users and Personalize Web Pages

Stefano Ferretti, Silvia Mirri, Catia Prandi, Paola Salomoni
2014 2014 IEEE 38th International Computer Software and Applications Conference Workshops  
In this paper, we present a Web content adaptation system that is able to automatically adapt textual elements of Web pages, based on the user profile and preferences.  ...  In particular, a reinforcement learning algorithm, i.e. q-learning, based on the idea of reward/punishment is utilized as the machine learning system that manages the user profile.  ...  ACKNOWLEDGMENT The authors wish to thank Alberto Fariselli for his precious support.  ... 
doi:10.1109/compsacw.2014.45 dblp:conf/compsac/FerrettiMPS14 fatcat:jcynqby4kvhepccwxnr7jc6oca

Ontology-Based User Profiling for Personalized Acces to Information within Collaborative Learning System

Mohammed Amine Alimam, Yasyn Elyusufi, Hamid Seghiouer
2014 International Journal of Euro-Mediterranean Studies  
This is especially evident with the rise of internet and web 2.0 platforms that have transformed users' role from mere content consumers to fully content consumers-producers.  ...  This paper proceeds with a categorization of the main tools and functions that characterize the personalization learning aspect, in order to discuss their trade-offs with collaborative learning systems  ...  In this case, the type of content may be provided for users according to their choices and preferences (Cheng et al. 2009 ).  ... 
doaj:35903f37cc714b35b3a5ccab2d346c84 fatcat:cfa2czehifdrrautzwtw6kpju4

Living analytics methods for the web observatory

Ernesto Diaz-Aviles
2013 Proceedings of the 22nd International Conference on World Wide Web - WWW '13 Companion  
We center the discussion on two areas: (i) Recommender Systems for Big Fast Data and (ii) Collective Intelligence, both key components towards an analytics toolbox for our Web Observatory.  ...  The hundred of millions of users who are actively participating in the Social Web are exposed to ever-growing amounts of sites, relationships, and information.  ...  Little effort has been devoted to exploiting learning to rank in a personalized setting, specially in the domain of epidemic intelligence.  ... 
doi:10.1145/2487788.2488169 dblp:conf/www/Diaz-Aviles13 fatcat:woxilu7ahnanpasywnsjnus5wy

User Action Interpretation for Online Content Optimization

Jiang Bian, Anlei Dong, Xiaofeng He, Srihari Reddy, Yi Chang
2013 IEEE Transactions on Knowledge and Data Engineering  
To address this challenge, we investigate a couple of critical aspects of the online learning framework for personalized content optimization on Web portal services, and, in this paper, we propose deeper  ...  To attract more users to various content modules on the Web portal, it is necessary to design a recommender system that can effectively achieve online content optimization by automatically estimating content  ...  Online Learning To enable online learning for content optimization, we introduce a parallel-serving-buckets approach.  ... 
doi:10.1109/tkde.2012.130 fatcat:fqicym4ndbeiphkpvln4fannre

Contextual Online Learning for Multimedia Content Aggregation

Cem Tekin, Mihaela van der Schaar
2015 IEEE transactions on multimedia  
Our proposed content aggregation algorithm is able to learn online what content to gather and how to match content and users by exploiting similarities between consumer types.  ...  A key challenge for such systems is to accurately predict what type of content each of its consumers prefers in a certain context, and adapt these predictions to the evolving consumers' preferences, contexts  ...  For instance, in [4] , [11] a recommender system that learns the preferences of its users in an online way based on the ratings submitted by the users is provided.  ... 
doi:10.1109/tmm.2015.2403234 fatcat:2uklijueuzexdnb74o7xb6bobe

A Survey on Filtering Unwanted Messages from Online Social Network Users Wall Using Text Classification
English

Akshay Bagal, Shriniwas Gadage
2014 International Journal of Innovative Research in Computer and Communication Engineering  
This is achieved through a flexible rule based system in which users to customize the filtering criteria to be applied to their walls, and a Machine Learning (ML) based soft classification and short text  ...  Therefore the users who are using Online Social Networks(OSN) requires control over the unwanted messages that are posted on thier walls and to avoid the unwanted content which is displayed on private  ...  The content based user preferences is the key idea of proposed system [12] .  ... 
doi:10.15680/ijircce.2014.0212005 fatcat:piij3fiwkjhgjatqu7k3qgwgly

Learning technologies for people with disabilities

Mohsen Laabidi, Mohamed Jemni, Leila Jemni Ben Ayed, Hejer Ben Brahim, Amal Ben Jemaa
2014 Journal of King Saud University: Computer and Information Sciences  
Then, we will present recent research works conducted in our research Laboratory LaTICE toward the development of an accessible online learning environment for persons with disabilities from the design  ...  In this paper, we will cover basic concepts of e-accessibility, universal design and assistive technologies, with a special focus on accessible e-learning systems.  ...  -Some systems use accessible learning resource designed to be accessible to everyone, but not optimal to every user.  ... 
doi:10.1016/j.jksuci.2013.10.005 fatcat:srht3kuhuzcg5fnybvoqxvqs74

A Multi Intelligent Agent-based Approach for Optimizing Commercial Recommendations

Chaimae Lamaakchaoui, Abdellah Azmani, Mustapha EL Jarroudi
2014 International Journal of Computer Applications  
In the present paper a model of a multi agent based system is presented, which helps marketers on the one hand to address its products to the best targets and in the another hand to generate relevant product  ...  recommendations for customers that best match their interests and needs.  ...  Recommender systems are systems that predict what the most suitable contents (product, service, web page, news, video,) are for one customer [7] according to his tastes and preferences.  ... 
doi:10.5120/19013-0537 fatcat:sinsdxnmm5fgtgqaexe3xodaqe

Multi-dimensional technology-enabled social learning approach

Hristijan Petreski, Sofia Tsekeridou, Neeli R. Prasad, Zhen-Hua Tan
2016 Διεθνές Συνέδριο για την Ανοικτή & εξ Αποστάσεως Εκπαίδευση  
With the support of the technology and the IT revolution, the users once merely consumers, are actively producing and sharing content on the Web, using social networks to keep in touch, express, distribute  ...  This paper aims to precede one step further by proposing a multi-dimensional approach for technology-enabled social learning that further exploits implicit knowledge hidden in socially contributed textual  ...  innovation, etc.) can be discovered and exploited to advance the learning potential of today's e-learning systems; how the extracted knowledge can be evaluated and recommended to the users.  ... 
doi:10.12681/icodl.626 fatcat:oyscm5o4evcfnj4j2f5qc7nsse

Automatic Optimization of Web Recommendations Using Feedback and Ontology Graphs [chapter]

Nick Golovin, Erhard Rahm
2005 Lecture Notes in Computer Science  
The architecture combines recommendations from different algorithms in a recommendation database and applies feedback-based machine learning to optimize the selection of the presented recommendations.  ...  Web recommendation systems have become a popular means to improve the usability of web sites.  ...  Fig. 3 shows an example of an ontology graph for website content. Ontology graphs for web users and time are built in a similar way.  ... 
doi:10.1007/11531371_49 fatcat:mghw6kefsjbateene2q6moebuq

Online Customization and Enrollment Application Network (OCEAN)

E. Kongar, A. Abu Zaghleh, T. Sobh
2007 International Journal of Emerging Technologies in Learning (iJET)  
This paper introduces the Online Customization and Enrollment Application Network (OCEAN), developed in the School of Engineering at the University of Bridgeport.  ...  students to customize their preferences in the course selection process depending on the targeted graduate concentrations, degrees, and/or dual degree programs.  ...  They designed a system that houses an instructor authoring tool linked to a repository of highquality interactive learning content with topics in biomedical sciences.  ... 
doaj:6a43ee245fb74f8e9af6691e754f73f7 fatcat:mvn3jwkuazfc3kxaumyh6zq5xi

Guest editorial: WWWJ special issue of the 21th international Conference on Web Information Systems Engineering (WISE 2020)

Hua Wang, Zhisheng Huang
2021 World wide web (Bussum)  
It was processed through online and off-line for participants as some countries have closed board due to the global pandemic situation. However, WISE2020 was very successful.  ...  area of Web technologies, methodologies, and applications.  ...  Special thanks to the journal editors for their great help and support in organizing the issue.  ... 
doi:10.1007/s11280-021-00973-5 fatcat:53rcdamanfcive2gtohywj22yq
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