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KDD
2006
ACM
129views Data Mining» more  KDD 2006»
16 years 5 months ago
Bias and controversy: beyond the statistical deviation
In this paper, we investigate how deviation in evaluation activities may reveal bias on the part of reviewers and controversy on the part of evaluated objects. We focus on a `data...
Hady Wirawan Lauw, Ee-Peng Lim, Ke Wang
KDD
2006
ACM
200views Data Mining» more  KDD 2006»
16 years 5 months ago
A Random-Walk Based Scoring Algorithm Applied to Recommender Engines
Recommender systems are an emerging technology that helps consumers find interesting products and useful resources. A recommender system makes personalized product suggestions by e...
Augusto Pucci, Marco Gori, Marco Maggini
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
16 years 5 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
KDD
2005
ACM
109views Data Mining» more  KDD 2005»
16 years 5 months ago
Overcoming Incomplete User Models in Recommendation Systems Via an Ontology
Abstract. To make accurate recommendations, recommendation systems currently require more data about a customer than is usually available. We conjecture that the weaknesses are due...
Vincent Schickel-Zuber, Boi Faltings
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
16 years 5 months ago
Why collective inference improves relational classification
Procedures for collective inference make simultaneous statistical judgments about the same variables for a set of related data instances. For example, collective inference could b...
David Jensen, Jennifer Neville, Brian Gallagher