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CIKM
2010
Springer
15 years 5 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...
KDD
2010
ACM
300views Data Mining» more  KDD 2010»
15 years 5 months ago
Using data mining techniques to address critical information exchange needs in disaster affected public-private networks
Crisis Management and Disaster Recovery have gained immense importance in the wake of recent man and nature inflicted calamities. A critical problem in a crisis situation is how t...
Li Zheng, Chao Shen, Liang Tang, Tao Li, Steven Lu...
SIGIR
2005
ACM
16 years 2 days ago
Predicting query difficulty on the web by learning visual clues
We describe a method for predicting query difficulty in a precision-oriented web search task. Our approach uses visual features from retrieved surrogate document representations (...
Eric C. Jensen, Steven M. Beitzel, David A. Grossm...
WWW
2001
ACM
16 years 7 months ago
Crawling the Hidden Web
Current-day crawlers retrieve content only from the publicly indexable Web, i.e., the set of Web pages reachable purely by following hypertext links, ignoring search forms and pag...
Sriram Raghavan, Hector Garcia-Molina
SAINT
2002
IEEE
15 years 11 months ago
On Updating in Very Short Time by Distributed Search Engines
Almost conventional search engines employ centralized architecture. However, such an engine is not suitable for fresh information retrieval because it spends a long time to collec...
Nobuyoshi Sato, Minoru Uehara, Yoshifumi Sakai, Hi...