Stem clickthrough$ (all stems)

20 papers:

CHI-2012-TopkaraPLDWB #email #enterprise #quote #video

“You’ve got video”: increasing clickthrough when sharing enterprise video with email (MT, SP, JCL, AD, SW, JB), pp. 565–568.

SIGIR-2011-GaoTY #modelling #semantics #web

Clickthrough-based latent semantic models for web search (JG, KT, WtY), pp. 675–684.

SIGIR-2011-HeZSLY #evaluation #retrieval #web

Efficiently collecting relevance information from clickthroughs for web retrieval system evaluation (JH, WXZ, BS, XL, HY), pp. 275–284.

SIGIR-2011-LiHZW #information retrieval #query #segmentation #using

Unsupervised query segmentation using clickthrough for information retrieval (YL, BJPH, CZ, KW), pp. 285–294.

CIKM-2010-GaoHN #modelling #web #word

Clickthrough-based translation models for web search: from word models to phrase models (JG, XH, JYN), pp. 1139–1148.

CIKM-2009-HeZL #comparison #evaluation #retrieval

Evaluation of methods for relative comparison of retrieval systems based on clickthroughs (JH, CZ, XL), pp. 2029–2032.

KDD-2009-GuptaBR #learning

Catching the drift: learning broad matches from clickthrough data (SG, MB, MR), pp. 1165–1174.

KDD-2009-WangWZ #named #quality #ranking #web

PSkip: estimating relevance ranking quality from web search clickthrough data (KW, TW, ZZ), pp. 1355–1364.

SIGIR-2009-GaoYLDN #ranking #web

Smoothing clickthrough data for web search ranking (JG, WY, XL, KD, JYN), pp. 355–362.

CIKM-2008-CustisA #corpus #query #statistics

Investigating external corpus and clickthrough statistics for query expansion in the legal domain (TC, KAK), pp. 1363–1364.

CIKM-2008-MaYKL #learning #query #semantics

Learning latent semantic relations from clickthrough data for query suggestion (HM, HY, IK, MRL), pp. 709–718.

CIKM-2008-RadlinskiKJ #how #quality #question #retrieval

How does clickthrough data reflect retrieval quality? (FR, MK, TJ), pp. 43–52.

ECIR-2008-ShokouhiST #documentation #effectiveness #order

Investigating the Effectiveness of Clickthrough Data for Document Reordering (MS, FS, AT), pp. 591–595.

KDD-2007-RadlinskiJ #learning #ranking

Active exploration for learning rankings from clickthrough data (FR, TJ), pp. 570–579.

SIGIR-2007-ClarkeADW #web

The influence of caption features on clickthrough patterns in web search (CLAC, EA, STD, RWW), pp. 135–142.

SIGIR-2007-YeungCB #documentation #retrieval

Improving retrieval accuracy by weighting document types with clickthrough data (PCKY, CLAC, SB), pp. 759–760.

ECIR-2005-JiangSZ #web

Applying Associative Relationship on the Clickthrough Data to Improve Web Search (XMJ, WGS, HJZ), pp. 475–486.

SIGIR-2005-JoachimsGPHG #feedback

Accurately interpreting clickthrough data as implicit feedback (TJ, LAG, BP, HH, GG), pp. 154–161.

SIGIR-2005-SunSZYLC #summary #using

Web-page summarization using clickthrough data (JTS, DS, HJZ, QY, YL, ZC), pp. 194–201.

KDD-2002-Joachims #optimisation #using

Optimizing search engines using clickthrough data (TJ), pp. 133–142.