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SIGIR
2011
ACM
12 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
12 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
12 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
12 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
12 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...
SIGIR
2011
ACM
12 years 10 months ago
Mining weakly labeled web facial images for search-based face annotation
In this paper, we investigate a search-based face annotation framework by mining weakly labeled facial images that are freely available on the internet. A key component of such a ...
Dayong Wang, Steven C. H. Hoi, Ying He
SIGIR
2011
ACM
12 years 10 months ago
Fast context-aware recommendations with factorization machines
The situation in which a choice is made is an important information for recommender systems. Context-aware recommenders take this information into account to make predictions. So ...
Steffen Rendle, Zeno Gantner, Christoph Freudentha...
SIGIR
2011
ACM
12 years 10 months ago
Social context summarization
We study a novel problem of social context summarization for Web documents. Traditional summarization research has focused on extracting informative sentences from standard docume...
Zi Yang, Keke Cai, Jie Tang, Li Zhang, Zhong Su, J...
SIGIR
2011
ACM
12 years 10 months ago
ViewSer: enabling large-scale remote user studies of web search examination and interaction
Web search behaviour studies, including eye-tracking studies of search result examination, have resulted in numerous insights to improve search result quality and presentation. Ye...
Dmitry Lagun, Eugene Agichtein
SIGIR
2011
ACM
12 years 10 months ago
Faster top-k document retrieval using block-max indexes
Large search engines process thousands of queries per second over billions of documents, making query processing a major performance bottleneck. An important class of optimization...
Shuai Ding, Torsten Suel