Foundations of statistical natural language processing
Foundations of statistical natural language processing
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
Relational Peculiarity Oriented Data Mining
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Efficiently Mining Frequent Trees in a Forest: Algorithms and Applications
IEEE Transactions on Knowledge and Data Engineering
Feature-rich part-of-speech tagging with a cyclic dependency network
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
A comparison of statistical significance tests for information retrieval evaluation
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
ORIGAMI: Mining Representative Orthogonal Graph Patterns
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Standing Out in a Crowd: Selecting Attributes for Maximum Visibility
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Maintenance of top-k materialized views
Distributed and Parallel Databases
The essence of knowledge (bases) through entity rankings
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Everything is relative. Cars are compared by gas per mile, websites by page rank, students based on GPA, scientists by number of publications, and celebrities by beauty or wealth. In this paper, we study the characteristics of such entity rankings based on a set of rankings obtained from a popular Web portal. The obtained insights are integrated in our approach, coined Pantheon. Pantheon maintains sets of top-k rankings and reports identified changes in a way that appeals to users, using a novel combination of different characteristics like competitiveness, information entropy, and scale of change. Entity rankings are assembled by combining entity type attributes with data-driven categorical constraints and sorting criteria on numeric attributes. We report on the results of an experimental evaluation using real-world data obtained from a basketball statistics website.