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SIGIR
2011
ACM
14 years 10 months ago
Learning to rank from a noisy crowd
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
Abhimanu Kumar, Matthew Lease
SIGIR
2011
ACM
14 years 10 months ago
Faster temporal range queries over versioned text
Versioned textual collections are collections that retain multiple versions of a document as it evolves over time. Important large-scale examples are Wikipedia and the web collect...
Jinru He, Torsten Suel
SIGIR
2011
ACM
14 years 10 months ago
Time-based query performance predictors
Query performance prediction is aimed at predicting the retrieval effectiveness that a query will achieve with respect to a particular ranking model. In this paper, we study quer...
Nattiya Kanhabua, Kjetil Nørvåg
SIGIR
2011
ACM
14 years 10 months ago
Learning search tasks in queries and web pages via graph regularization
As the Internet grows explosively, search engines play a more and more important role for users in effectively accessing online information. Recently, it has been recognized that ...
Ming Ji, Jun Yan, Siyu Gu, Jiawei Han, Xiaofei He,...
SIGIR
2011
ACM
14 years 10 months ago
Learning online discussion structures by conditional random fields
Online forum discussions are emerging as valuable information repository, where knowledge is accumulated by the interaction among users, leading to multiple threads with structure...
Hongning Wang, Chi Wang, ChengXiang Zhai, Jiawei H...