M
Mark D. Smucker
Researcher at University of Waterloo
Publications - 90
Citations - 3284
Mark D. Smucker is an academic researcher from University of Waterloo. The author has contributed to research in topics: Relevance (information retrieval) & Relevance feedback. The author has an hindex of 25, co-authored 86 publications receiving 2974 citations. Previous affiliations of Mark D. Smucker include University of Wisconsin-Madison & University of Massachusetts Amherst.
Papers
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Proceedings ArticleDOI
A comparison of statistical significance tests for information retrieval evaluation
TL;DR: It is discovered that there is little practical difference between the randomization, bootstrap, and t tests and their use should be discontinued for measuring the significance of a difference between means.
Journal ArticleDOI
Efficient and effective spam filtering and re-ranking for large web datasets
TL;DR: It is shown that a simple content-based classifier with minimal training is efficient enough to rank the “spamminess” of every page in the ClueWeb09 dataset using a standard personal computer in 48 hours, and effective enough to yield significant and substantive improvements in the fixed-cutoff precision as well as rank measures of nearly all submitted runs.
ReportDOI
UMass at TREC 2004: Novelty and HARD
Nasreen Abdul-Jaleel,James Allan,W. Bruce Croft,Fernando Diaz,Leah S. Larkey,Xiaoyan Li,Mark D. Smucker,Courtney Wade +7 more
TL;DR: The primary findings for passage retrieval are that document retrieval methods performed better than passage retrieval methods on the passage evaluation metric of binary preference at 12,000 characters, and that clarification forms improved passage retrieval for every retrieval method explored.
Proceedings ArticleDOI
Time-based calibration of effectiveness measures
TL;DR: This paper introduces a time-biased gain measure, which allows us to evaluate system performance in human terms, while maintaining the simplicity and repeatability of system-oriented tests, and examines properties of the measure, contrasting it to traditional effectiveness measures, and exploring its extension to other aspects and environments.
Posted Content
Preferential Partner Selection in an Evolutionary Study of Prisoner's Dilemma
TL;DR: In this article, the authors investigate the evolutionary prisoner's dilemma in which agents use expected payoffs to choose and refuse partners, and find that the average payoffs attained with preferential partner selection tend to be more narrowly confined to a few isolated payoff regions.