A topical PageRank based algorithm for recommender systems
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
A Novel Recommending Algorithm Based on Topical PageRank
AI '08 Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Exploiting Positive and Negative Graded Relevance Assessments for Content Recommendation
WAW '09 Proceedings of the 6th International Workshop on Algorithms and Models for the Web-Graph
Scholarly paper recommendation via user's recent research interests
Proceedings of the 10th annual joint conference on Digital libraries
Temporal recommendation on graphs via long- and short-term preference fusion
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A source independent framework for research paper recommendation
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
Leveraging the linkedin social network data for extracting content-based user profiles
Proceedings of the fifth ACM conference on Recommender systems
Link analysis in mind maps: a new approach to determining document relatedness
Proceedings of the 4th International Conference on Uniquitous Information Management and Communication
Fast Recommendation on Bibliographic Networks
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Exploiting potential citation papers in scholarly paper recommendation
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
Towards a personalized, scalable, and exploratory academic recommendation service
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
A unified graph model for personalized query-oriented reference paper recommendation
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Research paper recommender system evaluation: a quantitative literature survey
Proceedings of the International Workshop on Reproducibility and Replication in Recommender Systems Evaluation
Modeling and broadening temporal user interest in personalized news recommendation
Expert Systems with Applications: An International Journal
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Every day researchers from all over the world have to filter the huge mass of existing research papers with the crucial aim of finding out useful publications related to their current work. In this paper we propose a research paper recommending algorithm based on the Citation Graph and random-walker properties. The PaperRank algorithm is able to assign a preference score to a set of documents contained in a digital library and linked one each other by bibliographic references. A data set of papers extracted by ACM Portal has been used for testing and very promising performances have been measured.