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A Recommendation System for the Semantic Web [chapter]

Victor Codina, Luigi Ceccaroni
2010 Advances in Intelligent and Soft Computing  
In this paper, we present a personalizedrecommendation system, a system that makes use of representations of items and user-profiles based on ontologies in order to provide semantic applications with personalized  ...  Recommendation systems can take advantage of semantic reasoningcapabilities to overcome common limitations of current systems and improve the recommendations' quality.  ...  Thus, the system infers that the user is interested in Sport and Golf with the same DOI_weight (0.62).  ... 
doi:10.1007/978-3-642-14883-5_6 dblp:conf/dcai/CodinaC10 fatcat:5zkhekfknfheppqdikmphbwhw4

Propagating User Interests in Ontology-Based User Model [chapter]

Federica Cena, Silvia Likavec, Francesco Osborne
2011 Lecture Notes in Computer Science  
Such ontological approach to user profiling has been proven successful in addressing the cold-start problem in recommender systems, since it allows for propagation from a small number of initial concepts  ...  In this paper we address the problem of propagating user interests in ontology-based user models. Our ontology-based user model (OBUM) is devised as an overlay over the domain ontology.  ...  In user-adaptive and recommender systems [7, 1] , a User Model stores the available information about a user by maintaining user properties such as interests, preferences, knowledge, goals and other facts  ... 
doi:10.1007/978-3-642-23954-0_28 fatcat:gwvmlkxgenfpxlrbwjqfzpj644

Dynamic Trust Management for Community Based Mobile Grid Application

2019 International Journal of Engineering and Advanced Technology  
It assists individuals with beating impression of vulnerability, threat and participates in client acknowledgment to utilization on grid services and applications.  ...  Trust plays an important role for handling the security in the community based system.  ...  It is very essential for people to overcome perceptions of uncertainty and risk and engage in user acceptance and consumption of community based services and applications.  ... 
doi:10.35940/ijeat.b3437.129219 fatcat:sd7jiwtqmve4ro7uujy3svedqu

Trust aware recommender system with distrust in different views of trusted users

S.N.A.M. Mahtar, S Masrom, N Omar, N Khairudin, S.K.N.A. Rahim, Z.I. Rizman
2018 Journal of Fundamental and Applied Sciences  
The main problems in the CF recommender system are sparsity and cold start.  ...  Furthermore, based on an empirical experiment, the performances of two recommender system approaches with trust aware and distrust in different views of trusted users are also reported in this paper.  ...  In other words, it provides recommendations to a particular user that are based upon other users' recommendations with similar interest or profiles.  ... 
doi:10.4314/jfas.v9i5s.13 fatcat:fhrkwxoas5bbzerq3frstbylsq

Property-based Semantic Similarity and Relatedness for Improving Recommendation Accuracy and Diversity

Silvia Likavec, Francesco Osborne, Federica Cena
2015 International Journal on Semantic Web and Information Systems (IJSWIS)  
These measures are used in the propagation of user interest values in ontology-based user models to other similar or related concepts in the domain.  ...  The authors tested their algorithm in event recommendation domain and in recipe domain and showed that property-based propagation based on similarity outperforms the standard edge-based propagation.  ...  This propagation of user interests can be seen as a special case of spreading activation theory (Salton and Buckley, 1988) , since starting from a user interest in one domain object, it is possible to  ... 
doi:10.4018/ijswis.2015100101 fatcat:m6kexectzzfjfk7r4outeevxsa

Property-Based Interest Propagation in Ontology-Based User Model [chapter]

Federica Cena, Silvia Likavec, Francesco Osborne
2012 Lecture Notes in Computer Science  
Starting from initial user feedback on an object, we calculate user interest in this particular object and its properties and further propagate user interest to other objects in the ontology, similar or  ...  We tested our approach for interest propagation with a real adaptive application and obtained an improvement with respect to IS-A-propagation of interest values.  ...  The system records implicitly the user actions, inferring from them the interest for the object the action is performed on, and uses it to incrementally create and update the user model by modifying the  ... 
doi:10.1007/978-3-642-31454-4_4 fatcat:gvagsfdsdnatnglzibcibu6poy

Anisotropic propagation of user interests in ontology-based user models

Federica Cena, Silvia Likavec, Francesco Osborne
2013 Information Sciences  
We tackle the problem of propagation of user interests in such a conceptual hierarchy.  ...  propagation which enables propagation among siblings, in addition to vertical propagation among ancestors and descendants; (ii) anisotropic vertical propagation which permits user interests to be propagated  ...  [30] , the authors try to increase the accuracy of the user profiles and hence usefulness of the recommendations in hybrid recommender systems.  ... 
doi:10.1016/j.ins.2013.07.006 fatcat:olizmmzhlzav7cfdy7glira4bm


Z. Bahramian, R. Ali Abbaspour, C. Claramunt
2017 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The results show the overall performance of the proposed context-aware tourism recommender systems by an experimental application to the city of Tehran.  ...  It also incorporates contextual information to improve the recommendation process.  ...  spreading activation to model and propagate the user interest.  ... 
doi:10.5194/isprs-archives-xlii-4-w4-333-2017 fatcat:nnf4lmyhkzbk5nywcq7gmyz6w4

A Community Based Reliable Trusted Framework for Collaborative Filtering

Satya Keerthi Gorripati, M.Kamala Kumari, Anupama Angadi
2019 International Journal of Intelligent Systems and Applications  
: The first step identifies the trusted relations of the current user by allowing trust propagation in the trust network.  ...  In the process of reducing limitations of traditional approaches and to improve the quality of recommender systems, a reliability based community method is introduced.This method comprises of three steps  ...  On the other hand Collaborative Filtering (CF) systems gather the interests/opinions from the users in terms of ratings and provide recommendations based on interests.  ... 
doi:10.5815/ijisa.2019.02.07 fatcat:sz3snsb2hfbq5jivxgffpd2b3y

Graph Neural Networks in Recommender Systems: A Survey

Shiwen Wu, Fei Sun, Wentao Zhang, Xu Xie, Bin Cui
2022 ACM Computing Surveys  
In recommender systems, the main challenge is to learn the effective user/item representations from their interactions and side information (if any).  ...  Due to the important application value of recommender systems, there have always been emerging works in this field.  ...  ACKNOWLEDGEMENT This work is supported by NSFC (No. 61832001), Beijing Academy of Artiicial Intelligence (BAAI), and PKU-Tencent Joint Research Lab.  ... 
doi:10.1145/3535101 fatcat:hgv2tbx3k5hzbnkupwsysqwjmy

A probabilistic model for user interest propagation in recommender systems

Samuel Mensah, Chunming Hu, Xue Li, Xudong Liu, Richong Zhang
2020 IEEE Access  
INDEX TERMS Propagation, recommender system, sum-product algorithm, user interest modeling.  ...  To this end, we propose a framework which avoids the sole dependence of user activities to infer user interests and allows the exploitation of the direct relationship between users to propagate user interests  ...  This paper is an extension of our paper titled ''User interest propagation and its application in recommender system'' which appeared in IEEE ICTAI'17.  ... 
doi:10.1109/access.2020.3001210 fatcat:n32dkgtjanc37nrq67awyk3zqe

Selective Propagation of Social Data in Decentralized Online Social Network [chapter]

Udeep Tandukar, Julita Vassileva
2012 Lecture Notes in Computer Science  
Due to the fact that most current OSNs are centralized, people are forced to share their data with the site, in order to be able to share it with their friends, and thus they lose control over it.  ...  This paper discusses an approach for propagation of social data in a decentralized OSN so as to reduce irrelevant data among users.  ...  That is why it is desirable for the representation of user data in the user model to follow some ontology so that it could be understood and interpreted outside of the context of the application in which  ... 
doi:10.1007/978-3-642-28509-7_20 fatcat:nkuorw3bovc4nh6wyodmvgspya

Application of Trust and Distrust in Recommender System: A Study

Parthasarathi Chakraborty, Sunil Karforma
2016 International Journal of Computer Applications  
In recent time, trust becomes an important issue in designing effective recommender systems. In this paper we have studied the role of trust and distrust in designing recommender systems.  ...  Recommender systems help customers to choose right product or service from large number of alternatives available on Internet.  ...  Do authors proposed the concept of profile-level and item-level trust in the context of recommender systems.  ... 
doi:10.5120/ijca2016909153 fatcat:pawsquxjszbqvjjtfwoczboeku

Kernel Optimization Based Enhanced Preference Learning for Online Movie Recommendation

Sreelekshmi. B
2018 International Journal for Research in Applied Science and Engineering Technology  
Recommendation systems have wide range of applications in today's digital life. Recommendation is performed on books, products, dresses, movies, music and so on.  ...  The proposed system is a movie recommendation system which related on user preferences or interests. This system produces an accurate movie recommendation to users.  ...  Therefore, it is important to adapt social recommendation system to the real-world online applications where data arrives consecutively and user preferences or interests may change dynamically and rapidly  ... 
doi:10.22214/ijraset.2018.5119 fatcat:tpvs6uoprzfppgxmkz7ihaanti

Knowledge-Aware Multispace Embedding Learning for Personalized Recommendation

Meng Jian, Chenlin Zhang, Xin Fu, Lifang Wu, Zhangquan Wang
2022 Sensors  
Recommender systems help users filter items they may be interested in from massive multimedia content to alleviate information overload.  ...  In this work, we explore the semantic correlations between items on modeling users' interests and propose knowledge-aware multispace embedding learning (KMEL) for personalized recommendation.  ...  Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s22062212 pmid:35336383 pmcid:PMC8954710 fatcat:zsuwtkqmwbc5zgm7ijvhbrkjk4
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