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ICMLC
2010
Springer
13 years 3 months ago
A comparative study on two large-scale hierarchical text classification tasks' solutions
: Patent classification is a large scale hierarchical text classification (LSHTC) task. Though comprehensive comparisons, either learning algorithms or feature selection strategies...
Jian Zhang, Hai Zhao, Bao-Liang Lu
AIRS
2010
Springer
13 years 3 months ago
Relevance Ranking Using Kernels
This paper is concerned with relevance ranking in search, particularly that using term dependency information. It proposes a novel and unified approach to relevance ranking using ...
Jun Xu, Hang Li, Chaoliang Zhong
TREC
2004
13 years 6 months ago
The Hong Kong Polytechnic University at the TREC 2004 Robust Track
In the robust track, we mainly tested our passage-based retrieval model with different passage sizes and weighting schemes. In our approach, we used two retrieval models, namely t...
D. Y. Wang, Robert Wing Pong Luk, Kam-Fai Wong
TREC
2008
13 years 6 months ago
FEUP at TREC 2008 Blog Track: Using Temporal Evidence for Ranking and Feed Distillation
This paper presents the participation of FEUP, from University of Porto, in the TREC 2008 Blog Track. FEUP participated in two tasks, the baseline adhoc retrieval task and the blo...
Sérgio Nunes, Cristina Ribeiro, Gabriel Dav...
HICSS
2006
IEEE
163views Biometrics» more  HICSS 2006»
13 years 11 months ago
Learning Ranking vs. Modeling Relevance
The classical (ad hoc) document retrieval problem has been traditionally approached through ranking according to heuristically developed functions (such as tf.idf or bm25) or gene...
Dmitri Roussinov, Weiguo Fan