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» Analysis of Web Search Engine Clicked Documents
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CIKM
2010
Springer
13 years 8 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...
EMNLP
2010
13 years 7 months ago
Learning Recurrent Event Queries for Web Search
Recurrent event queries (REQ) constitute a special class of search queries occurring at regular, predictable time intervals. The freshness of documents ranked for such queries is ...
Ruiqiang Zhang, Yuki Konda, Anlei Dong, Pranam Kol...
SIGIR
2010
ACM
14 years 1 months ago
Clicked phrase document expansion for sponsored search ad retrieval
We present a document expansion approach that uses Conditional Random Field (CRF) segmentation to automatically extract salient phrases from ad titles. We then supplement the ad d...
Dustin Hillard, Chris Leggetter
EMNLP
2009
13 years 7 months ago
Mining Search Engine Clickthrough Log for Matching N-gram Features
User clicks on a URL in response to a query are extremely useful predictors of the URL's relevance to that query. Exact match click features tend to suffer from severe data s...
Huihsin Tseng, Longbin Chen, Fan Li, Ziming Zhuang...
AIRS
2010
Springer
13 years 7 months ago
Effective Time Ratio: A Measure for Web Search Engines with Document Snippets
The dominant method for evaluating search engines is the Cranfield paradigm, but the existing metrics do not consider some modern search engines features, such as document snippets...
Jing He, Baihan Shu, Xiaoming Li, Hongfei Yan