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CHI
2011
ACM
12 years 11 months ago
Apolo: making sense of large network data by combining rich user interaction and machine learning
Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...
Duen Horng Chau, Aniket Kittur, Jason I. Hong, Chr...
MM
2004
ACM
129views Multimedia» more  MM 2004»
14 years 1 months ago
A novel log-based relevance feedback technique in content-based image retrieval
Relevance feedback has been proposed as an important technique to boost the retrieval performance in content-based image retrieval (CBIR). However, since there exists a semantic g...
Chu-Hong Hoi, Michael R. Lyu
DEXAW
2007
IEEE
116views Database» more  DEXAW 2007»
14 years 2 months ago
Regression Relevance Models for Data Fusion
Data fusion has been investigated by many researchers in the information retrieval community and has become an effective technique for improving retrieval effectiveness. In this p...
Shengli Wu, Yaxin Bi, Sally I. McClean
ECIR
2003
Springer
13 years 9 months ago
From Uncertain Inference to Probability of Relevance for Advanced IR Applications
Uncertain inference is a probabilistic generalisation of the logical view on databases, ranking documents according to their probabilities that they logically imply the query. For ...
Henrik Nottelmann, Norbert Fuhr
SIGIR
2009
ACM
14 years 2 months ago
Risky business: modeling and exploiting uncertainty in information retrieval
Most retrieval models estimate the relevance of each document to a query and rank the documents accordingly. However, such an approach ignores the uncertainty associated with the ...
Jianhan Zhu, Jun Wang, Ingemar J. Cox, Michael J. ...