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Location-Aware and Personalized Collaborative Filtering for Web Service Recommendation : A Review

Chinnu Priya, Suja Rani
2016 International Journal of Computer Applications  
which are also known as Quality of Service(QoS) while finding and selecting appropriate web services.Collaborative filtering[3] approach predicts the QoS values of the web services effectively.Existing  ...  and services in selecting similar neighbors for the target user and service and thereby making personalized service recommendation for service users.  ...  Memory based collaborative filtering is also known as neighborhood-based CF and it makes use of the entire user-item database to generate a prediction.Based on the user neighborhood or item neighborhood  ... 
doi:10.5120/ijca2016908089 fatcat:jsexhlak7zgzfewidh25gdjoam

Personalized QoS Prediction of Cloud Services via Learning Neighborhood-based Model [article]

Hao Wu, Jun He, Bo Li, Yijian Pei
2015 arXiv   pre-print
To address this issue, this paper proposes neighborhood-based approach for QoS prediction of cloud services by taking advantages of collaborative intelligence.  ...  Particularly, the demand for efficient quality-of-service (QoS) evaluation is becoming urgently strong.  ...  Conclusion and future works Based on principles of collaborative filtering and machine learning, we propose a neighborhood-based framework for making personalized QoS prediction of cloud services.  ... 
arXiv:1508.04537v1 fatcat:o5mofh7bvvex3fnovzuqbfe4yu

Personalized QoS Prediction of Cloud Services via Learning Neighborhood-Based Model [chapter]

Hao Wu, Jun He, Bo Li, Yijian Pei
2016 Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering  
This paper proposes neighborhood-based approach for QoSprediction of cloud services by taking advantages of collaborative intelligence.  ...  Experimental results show that the learned neighborhood-based models can overcome existing difficulties of heuristic collaborative filtering methods and achieve superior performance than state-of-the-art  ...  Conclusion and Future Works Founded on the principles of collaborative filtering and machine learning, we propose a neighborhood-based framework for making personalized QoS-prediction of cloud services  ... 
doi:10.1007/978-3-319-28910-6_10 fatcat:bkhzbpfiwzemjar3ypcdsm2hdi

A framework for Health Services Recommender System

Mrs. Anjali S. Gaikwad
2018 International Journal for Research in Applied Science and Engineering Technology  
With the rapid growth of health disease in the country, recommendation for health services is taken a vital role in public sector.  ...  Medical system providing 24/7 help system and providing health services. Recommender system is a key factor to identify the services and receiving the better services in today's scenario.  ...  Model-based collaborative filtering algorithm: -Model based CF algorithm provide item recommendation by first developing a model of user ratings.  ... 
doi:10.22214/ijraset.2018.4432 fatcat:djfph56wung5njii3rlqb74vmy

Biclustering based Collaborative Filtering Algorithm for Personalized Web Service Recommendation

M. Chandralekha, Saranya K.G., G. Sudha
2016 International Journal of Computer Applications  
Collaborative filtering (CF) is a technique to carry out automatic suggestions for a user based on the view of other users with similar taste.  ...  To deal with the data sparsity problem a novel collaborative filtering recommendation algorithm is proposed based on biclustering.  ...  The QoS prediction method can also identify a set of high-quality Web services, and directly recommend them to an active user for selection.  ... 
doi:10.5120/ijca2016909871 fatcat:d3oxl3iz65cvfngtsbs6nv6ae4

Effective Constraint based Clustering Approach for Collaborative Filtering Recommendation using Social Network Analysis

Kanimozhi S
2011 Bonfring International Journal of Data Mining  
Collaborative Filtering (CF) is an eminent technique in recommender systems. CF uses relationships between users and recommends items to the active user based on the ratings of his/her neighbors.  ...  The application of this approach is studied in two application scenarios: academic venue recommendation based on collaboration information and trust-based recommendation.  ...  Collaborative filtering [6] make recommendations based on the ratings of item i by the set of users whose rating S.  ... 
doi:10.9756/bijdm.i1003 fatcat:p2hrvvpi4zbgbiho6e334s22sa

Effective Constraint based Clustering Approach for Collaborative Filtering Recommendation using Social Network Analysis

Kanimozhi S
2011 Bonfring International Journal of Data Mining  
Collaborative Filtering (CF) is an eminent technique in recommender systems. CF uses relationships between users and recommends items to the active user based on the ratings of his/her neighbors.  ...  The application of this approach is studied in two application scenarios: academic venue recommendation based on collaboration information and trust-based recommendation.  ...  Collaborative filtering [6] make recommendations based on the ratings of item i by the set of users whose rating S.  ... 
doi:10.9756/bijdm.1003 fatcat:jwhnzx6lybe4nnx4dz6nmw4qz4

A Survey on Different Recommendation Techniques

2021 International Journal of Emerging Trends in Engineering Research  
Prediction plays an important role in recommender systems while making the recommendation for users, prediction ensures the quality of suggestions for their users.  ...  Recommender systems are used to provide recommendation or suggestions on services and items to the users. It provides suggestions which based on prediction.  ...  TYPES OF RECOMMENDATION TECHNIQUES Content Based Filtering Technique This technique is based on domain and it is used the attributes of content to produce the predictions for users. A.  ... 
doi:10.30534/ijeter/2021/019112021 fatcat:il67kmrjavbcbj2mwx2yzapzwm

Item-based collaborative filtering recommendation algorithms

Badrul Sarwar, George Karypis, Joseph Konstan, John Reidl
2001 Proceedings of the tenth international conference on World Wide Web - WWW '01  
To address these issues we have explored item-based collaborative filtering techniques.  ...  In traditional collaborative filtering systems the amount of work increases with the number of participants in the system.  ...  Acknowledgments Funding for this research was provided in part by the National Science Foundation under grants IIS 9613960, IIS 9734442, and IIS 9978717 with additional funding by Net Perceptions Inc.  ... 
doi:10.1145/371920.372071 dblp:conf/www/SarwarKKR01 fatcat:qd6ygbmmsvg2hp7skfg4rrwr6u

Improving Neighborhood-Based Collaborative Filtering by a Heuristic Approach and an Adjusted Similarity Measure

Yasser El Madani El Alami, El Habib Nfaoui, Omar El Beqqali
2015 International Conference on Big Data Cloud and Applications  
This paper presents a new algorithm for neighborhood selection based on two heuristic approaches.  ...  Collaborative filtering" is the most used approach in recommendation systems since it provides good predictions.  ...  BACKGROUND The term of collaborative filtering (CF) was introduced by David Goldberg in [11] where he proposed a mail system called Tapestry that filters documents based on users' interest in order to  ... 
dblp:conf/bdca/AlamiNB15 fatcat:i5pob2cc2rdtrbuxu57eawlxhq

Aggregated Quantified Response Time Matrix Formulation (ARMF) - A New Quality of Service Paradigm Technique

Balika J. Chelliah, K. Vivekanandan
2015 Journal of Software  
The goal of QoS is to select the appropriate web services for the customers achieve their goals.  ...  But they face difficulties in identifying the right quality of a service based on functionality.  ...  A collaborative quality-of-service (QoS) prediction approach is introduced that implements the concept of neighborhood-integrated matrix factorization (NIMF) to select the best Web Service by using the  ... 
doi:10.17706//jsw.10.9.1070-1078 fatcat:rt5ozlfvzfaypii7zpiqpgblse

Aggregated Quantified Response Time Matrix Formulation (ARMF) - A New Quality of Service Paradigm Technique

Balika. J. Chelliah, K. Vivekanandan
2015 Journal of Software  
The goal of QoS is to select the appropriate web services for the customers achieve their goals.  ...  But they face difficulties in identifying the right quality of a service based on functionality.  ...  A collaborative quality-of-service (QoS) prediction approach is introduced that implements the concept of neighborhood-integrated matrix factorization (NIMF) to select the best Web Service by using the  ... 
doi:10.17706/jsw.10.9.1070-1078 fatcat:24ibvmx4gng6vecpasxwo6dxmu

Location-Aware Collaborative Filtering for Web Service Recommendations Based on User and Service History

Balika J Chelliah, K. Vivekanandan
2017 Journal of Engineering Science and Technology Review  
Due to the large number of candidates, it is difficult for a user to select the service best suited to their needs.  ...  location of the users for the filtering process.  ...  Overview of the Proposed Model Collaborative Filtering (CF) is a method where recommendations are made by automatically predicting user preferences by collecting the preferences of similar users.  ... 
doi:10.25103/jestr.105.23 fatcat:duslebh7p5bc7fwfe4c445j4qm

A Survey on Personalized Recommendation System for Web Services

2016 International Journal of Science and Research (IJSR)  
Collaborative filtering technique is a most popular technique used for the recommendation system. We will present the research related to collaborative filtering has been done.  ...  Web services are integrated software components for the support of interoperable machines interaction over a network, Many different Techniques and algorithms of recommendations are discussed, In this  ...  to address the QoS prediction problem in[8].Drawbacks:-Inflexible Quality of predictions , Synonyms, Problem and Cold-start problem.2.2.2 Memory Based Collaborative Filtering a) Item based collaborative  ... 
doi:10.21275/v5i3.nov162232 fatcat:zkxnxbpmo5grhgp7neiknyvacm

Personalized and Accurate QoS Prediction Approach Based on Online Learning Matrix Factorization for Web Services

Jian-Long Xu, Chang-Sheng Zhu, L. Long, Y. Li, X. Li, Y. Dai, H. Yang
2017 ITM Web of Conferences  
Quality of Service (QoS) prediction has played an important role in service computing.  ...  In order to provide high accurate and efficient QoS prediction performance for Web services, we propose a personalized and accurate QoS prediction approach namely PAOMF.  ...  Acknowledgment This research was financially supported by the Guangdong High-Level University Project "Green Technologies for Marine Industries", Guangdong Common Colleges Young Innovative Talents Project  ... 
doi:10.1051/itmconf/20171203027 fatcat:o63zlua2drhw3plmy5v5vrdq4a
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