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» Term Ranking for Clustering Web Search Results
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CIKM
2010
Springer
13 years 7 months ago
Online learning for recency search ranking using real-time user feedback
Traditional machine-learned ranking algorithms for web search are trained in batch mode, which assume static relevance of documents for a given query. Although such a batch-learni...
Taesup Moon, Lihong Li, Wei Chu, Ciya Liao, Zhaohu...
AIRS
2010
Springer
13 years 6 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
SIGIR
2012
ACM
11 years 11 months ago
An exploration of ranking heuristics in mobile local search
Users increasingly rely on their mobile devices to search local entities, typically businesses, while on the go. Even though recent work has recognized that the ranking signals in...
Yuanhua Lv, Dimitrios Lymberopoulos, Qiang Wu
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
12 years 4 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...
ACMDIS
2008
ACM
13 years 11 months ago
Evaluating the effectiveness of term frequency histograms for supporting interactive web search tasks
Throughout many of the different types of Web searches people perform, the primary tasks are to first craft a query that effectively captures their information needs, and then eva...
Orland Hoeber, Xue Dong Yang