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ECIR
2010
Springer
13 years 7 months ago
Maximum Margin Ranking Algorithms for Information Retrieval
Abstract. Machine learning ranking methods are increasingly applied to ranking tasks in information retrieval (IR). However ranking tasks in IR often differ from standard ranking t...
Shivani Agarwal, Michael Collins
GECCO
2009
Springer
151views Optimization» more  GECCO 2009»
14 years 4 months ago
Swarming to rank for information retrieval
This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, SwarmRank...
Ernesto Diaz-Aviles, Wolfgang Nejdl, Lars Schmidt-...
WWW
2007
ACM
14 years 10 months ago
A kernel based structure matching for web services search
This paper describes a kernel based Web Services (abbreviated as service) matching mechanism for service discovery and integration. The matching mechanism tries to exploit the lat...
Yu Jianjun, Guo Shengmin, Su Hao, Zhang Hui, Xu Ke
ICML
2008
IEEE
14 years 10 months ago
Optimizing estimated loss reduction for active sampling in rank learning
Learning to rank is becoming an increasingly popular research area in machine learning. The ranking problem aims to induce an ordering or preference relations among a set of insta...
Pinar Donmez, Jaime G. Carbonell
SEMCO
2007
IEEE
14 years 4 months ago
Ontology Evaluation and Ranking using OntoQA
Ontologies form the cornerstone of the Semantic Web and are intended to help researchers to analyze and share knowledge, and as more ontologies are being introduced, it is difficu...
Samir Tartir, I. Budak Arpinar