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DAGSTUHL
2006
15 years 5 months ago
Reference Point Approaches and Objective Ranking
The paper presents a reflection on some of the basic assumptions and philosophy of reference point approaches, stressing their unique concentration on the sovereignty of the subje...
Andrzej P. Wierzbicki
SDM
2007
SIAM
107views Data Mining» more  SDM 2007»
15 years 5 months ago
On Demand Phenotype Ranking through Subspace Clustering
High throughput biotechnologies have enabled scientists to collect a large number of genetic and phenotypic attributes for a large collection of samples. Computational methods are...
Xiang Zhang, Wei Wang 0010, Jun Huan
IR
2011
14 years 11 months ago
Learning to rank for why-question answering
In this paper, we evaluate a number of machine learning techniques for the task of ranking answers to why-questions. We use TF-IDF together with a set of 36 linguistically motivate...
Suzan Verberne, Hans van Halteren, Daphne Theijsse...
SSDBM
2008
IEEE
107views Database» more  SSDBM 2008»
15 years 10 months ago
ProUD: Probabilistic Ranking in Uncertain Databases
There are a lot of application domains, e.g. sensor databases, traffic management or recognition systems, where objects have to be compared based on vague and uncertain data. Feat...
Thomas Bernecker, Hans-Peter Kriegel, Matthias Ren...
COOPIS
1999
IEEE
15 years 8 months ago
Using Fagin's Algorithm for Merging Ranked Results in Multimedia Middleware
A distributed multimedia information system allows users to access data of different modalities, from different data sources, ranked by various combinationsof criteria. In [6], Fa...
Edward L. Wimmers, Laura M. Haas, Mary Tork Roth, ...