Fusion Via a Linear Combination of Scores

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Condorcet fusion for improved retrieval (2002, methodology): “This work has been followed by more extensive studies, especially in the recent past (for example, [2, 22, 31, 26, 29, 14, 33, 12, 4, 18, 16, 19, 23, 32, 5, 36, 28].”
Building efficient and effective metasearch engines (2002, background): “The result merging problem in this case is also known as data fusion [Vogt and Cottrell 1999].”
Spotting opinion spammers using behavioral footprints (2013, background): “In the supervised setting, one usually employs regression to learn the weights [41].”
A Multimodal Scheme for Program Segmentation and Representation in Broadcast Video Streams (2008, methodology): “In terms of later fusion, linear fusion models [38] have been widely applied to combine different uni-model classi-ﬁers (more popular in TRECVID [39]), in which those combination weights may be learnt from logistic regression.”
Improving recommendation lists through topic diversification (2005, methodology): “Most approaches use variations of the “linear combination of score” model (LC), described by Vogt and Cottrell [32].”
Concept-Based Information Retrieval Using Explicit Semantic Analysis (2011, methodology): “FUSED SELECTIVE ESA-BASED RETRIEVAL A large body of research [Croft 2000; Fox and Shaw 1994; Lee 1995; Vogt and Cottrell 1999] shows that combining (also known as fusion of) retrieval methods may improve .nal results.”