Real life, real users, and real needs: a study and analysis of user queries on the web
Information Processing and Management: an International Journal
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Lazy Associative Classification
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Communications of the ACM
Journal of the American Society for Information Science and Technology
Multi-label Lazy Associative Classification
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Differences in impact factor across fields and over time
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
A brief survey of automatic methods for author name disambiguation
ACM SIGMOD Record
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The impact of scientific research has traditionally been quantified using productivity indices such as the well-known h-index. On the other hand, different research fields---in fact, even different research areas within a single field---may have very different publishing patterns, which may not be well described by a single, global index. In this paper, we argue that productivity indices should account for the singularities of the publication patterns of different research areas, in order to produce an unbiased assessment of the impact of scientific research. Inspired by ranking aggregation approaches in distributed information retrieval, we propose a novel approach for ranking researchers across multiple research areas. Our approach is generic and produces cross-area versions of any global productivity index, such as the volume of publications, citation count and even the h-index. Our thorough evaluation considering multiple areas within the broad field of Computer Science shows that our cross-area indices outperform their global counterparts when assessed against the official ranking produced by CNPq, the Brazilian National Research Council for Scientific and Technological Development. As a result, this paper contributes a valuable mechanism to support the decisions of funding bodies and research agencies, for example, in any research assessment effort.