Combining weights into scores: a linear transform approach

Authors:
Sam Yuan Sung;Tianming Hu
Affiliations:
Department of Computer Science, South Texas College, McAllen;Department of Computer Science, Dongguan University of Technology, Dongguan, China
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

Citing 11
Cited 0

Weighted minimum and maximun operations in fuzzy sets theory

Information Sciences: an International Journal
Research problems in data warehousing

CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Maintenance of data cubes and summary tables in a warehouse

SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Fuzzy queries in multimedia database systems

PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Optimal multi-step k-nearest neighbor search

SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
A formula for incorporating weights into scoring rules

Theoretical Computer Science - Special issue on the 6th International Conference on Database Theory—ICDT '97
Modern Information Retrieval

Modern Information Retrieval
Incorporating User Preferences in Multimedia Queries

ICDT '97 Proceedings of the 6th International Conference on Database Theory
Towards heterogeneous multimedia information systems: the Garlic approach

RIDE '95 Proceedings of the 5th International Workshop on Research Issues in Data Engineering-Distributed Object Management (RIDE-DOM'95)
Score normalization in multimodal biometric systems

Pattern Recognition
Multi-step ranking of alternatives in a multi-criteria and multi-expert decision making environment

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Ranking has been widely used in many applications. A ranking scheme usually employs a scoring rule that assigns a final numerical value to every object to be ranked. A scoring rule normally involves the use of one to many scores, and it gives more weight to the scores that are more important. In this paper, we give a scheme that can combine weights into scores in a natural way and compare our scheme to the formula given by Fagin. Also given are some additional properties that are desirable for weighted scoring rules. Finally, we discuss other interesting issues on weighted scoring rules.