Constructing literature abstracts by computer: techniques and prospects
Information Processing and Management: an International Journal - Special issue on natural language processing and information retrieval
Efficient mining of emerging patterns: discovering trends and differences
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
A Machine-Oriented Logic Based on the Resolution Principle
Journal of the ACM (JACM)
Twenty Years of Document Image Analysis in PAMI
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rank aggregation methods for the Web
Proceedings of the 10th international conference on World Wide Web
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Relational Data Mining
Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
Discovery of frequent DATALOG patterns
Data Mining and Knowledge Discovery
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
An efficient boosting algorithm for combining preferences
The Journal of Machine Learning Research
Learning to rank using gradient descent
ICML '05 Proceedings of the 22nd international conference on Machine learning
A Data Mining Approach to Reading Order Detection
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
Learning query-biased web page summarization
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Label ranking by learning pairwise preferences
Artificial Intelligence
ManyAspects: a system for highlighting diverse concepts in documents
Proceedings of the VLDB Endowment
A complex network approach to text summarization
Information Sciences: an International Journal
Learning to order: a relational approach
MCD'07 Proceedings of the 3rd ECML/PKDD international conference on Mining complex data
Mining ranking models from dynamic network data
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
MedRank: discovering influential medical treatments from literature by information network analysis
ADC '13 Proceedings of the Twenty-Fourth Australasian Database Conference - Volume 137
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A key task in data mining and information retrieval is learning preference relations. Most of methods reported in the literature learn preference relations between objects which are represented by attribute-value pairs or feature vectors (propositional representation). The growing interest in data mining techniques which are able to directly deal with more sophisticated representations of complex objects, motivates the investigation of relational learning methods for learning preference relations. In this paper, we present a probabilistic relational data mining method which permits to model preference relations between complex objects. Preference relations are then used to rank objects. Experiments on two ranking problems for scientific literature mining prove the effectiveness of the proposed method.