Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Interactive theory revision: an inductive logic programming approach
Interactive theory revision: an inductive logic programming approach
Global partial orders from sequential data
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Rank aggregation methods for the Web
Proceedings of the 10th international conference on World Wide Web
Machine Learning
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
Relational Data Mining
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Process Mining: Discovering Direct Successors in Process Logs
DS '02 Proceedings of the 5th International Conference on Discovery Science
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Correcting the Document Layout: A Machine Learning Approach
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Document Transformation System from Papers to XML Data Based on Pivot XML Document Method
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Integrated text and image understanding for document understanding
HLT '94 Proceedings of the workshop on Human Language Technology
Optimized XY-Cut for Determining a Page Reading Order
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Learning Recursive Theories in the Normal ILP Setting
Fundamenta Informaticae
A Data Mining Approach to Reading Order Detection
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
Journal of Artificial Intelligence Research
Complex objects ranking: a relational data mining approach
Proceedings of the 2010 ACM Symposium on Applied Computing
Mining ranking models from dynamic network data
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
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In some applications it is necessary to sort a set of elements according to an order relationship which is not known a priori. In these cases, a training set of ordered elements is often available, from which the order relationship can be automatically learned. In this work, it is assumed that the correct succession of elements in a training sequence (or chain) is given, so that it is possible to induce the definition of two predicates, first/1 and succ/2, which are then used to establish an ordering relationship. A peculiarity of this work is the relational representation of training data which allows various relationships between ordered elements to be expressed in addition to the ordering relationship. Therefore, an ILP learning algorithm is applied to induce the definitions of the two predicates. Two methods are reported for the identification of either single chains or multiple chains on new objects. They have been applied to the problem of learning the reading order of layout components extracted from document images. Experimental results show the effectiveness of the proposed solution.