Person: Irwin King

DBLP: King:Irwin

Facilitated 1 volumes:

Ed

Contributed to:

2014

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2012

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2019

Wrote 39 papers:

CIKM-2014-RahimiSK #analysis #axiom #information retrieval

Axiomatic Analysis of Cross-Language Information Retrieval (RR, AS, IK), pp. 1875–1878.

CIKM-2014-ZhaoMK #collaboration #personalisation #ranking #social

Leveraging Social Connections to Improve Personalized Ranking for Collaborative Filtering (TZ, JJM, IK), pp. 261–270.

RecSys-2014-ChengXZKL

Gradient boosting factorization machines (CC, FX, TZ, IK, MRL), pp. 265–272.

RecSys-2014-LingLK #approach #recommendation

Ratings meet reviews, a combined approach to recommend (GL, MRL, IK), pp. 105–112.

CIKM-2012-GargKL #network #rating #social

Information propagation in social rating networks (PG, IK, MRL), pp. 2279–2282.

CIKM-2012-XinKALH #design #modelling

Do ads compete or collaborate?: designing click models with full relationship incorporated (XX, IK, RA, MRL, HH), pp. 1839–1843.

ASE-2011-ZhengMLXK #mining #testing #web

Mining test oracles of web search engines (WZ, HM, MRL, TX, IK), pp. 408–411.

CIKM-2011-LiKL #community

Question routing in community question answering: putting category in its place (BL, IK, MRL), pp. 2041–2044.

CIKM-2011-LiSLKC #identification #twitter

Question identification on twitter (BL, XS, MRL, IK, EYC), pp. 2477–2480.

CIKM-2011-YangZKL #how #learning #question #why

Can irrelevant data help semi-supervised learning, why and how? (HY, SZ, IK, MRL), pp. 937–946.

CIKM-2011-YuKL #approach #bidirectional #bottom-up #information management #top-down #towards

Towards a top-down and bottom-up bidirectional approach to joint information extraction (XY, IK, MRL), pp. 847–856.

SIGIR-2011-MaLKL #modelling #probability #recommendation #web

Probabilistic factor models for web site recommendation (HM, CL, IK, MRL), pp. 265–274.

CIKM-2010-LiK #community

Routing questions to appropriate answerers in community question answering services (BL, IK), pp. 1585–1588.

CIKM-2010-YangKL #feature model #learning #multi #online

Online learning for multi-task feature selection (HY, IK, MRL), pp. 1693–1696.

ICML-2010-XuJYKL #kernel #learning #multi #performance

Simple and Efficient Multiple Kernel Learning by Group Lasso (ZX, RJ, HY, IK, MRL), pp. 1175–1182.

ICML-2010-YangXKL #learning #online

Online Learning for Group Lasso (HY, ZX, IK, MRL), pp. 1191–1198.

CIKM-2009-DengKL #retrieval #using

Enhancing expertise retrieval using community-aware strategies (HD, IK, MRL), pp. 1733–1736.

CIKM-2009-LinLK #named #novel #similarity

MatchSim: a novel neighbor-based similarity measure with maximum neighborhood matching (ZL, MRL, IK), pp. 1613–1616.

CIKM-2009-MaYKL #collaboration #consistency #matrix #statistics

Semi-nonnegative matrix factorization with global statistical consistency for collaborative filtering (HM, HY, IK, MRL), pp. 767–776.

CIKM-2009-XinKDL #framework #multi #random #recommendation #social

A social recommendation framework based on multi-scale continuous conditional random fields (XX, IK, HD, MRL), pp. 1247–1256.

ICML-2009-XuJYLK #feature model

Non-monotonic feature selection (ZX, RJ, JY, MRL, IK), pp. 1145–1152.

KDD-2009-DengLK #algorithm #graph

A generalized Co-HITS algorithm and its application to bipartite graphs (HD, MRL, IK), pp. 239–248.

RecSys-2009-MaLK #learning #recommendation #trust

Learning to recommend with trust and distrust relationships (HM, MRL, IK), pp. 189–196.

SIGIR-2009-DengKL #graph #modelling #query #representation

Entropy-biased models for query representation on the click graph (HD, IK, MRL), pp. 339–346.

SIGIR-2009-MaKL #learning #recommendation #social #trust

Learning to recommend with social trust ensemble (HM, IK, MRL), pp. 203–210.

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-MaYLK #mining #network #process #social #using

Mining social networks using heat diffusion processes for marketing candidates selection (HM, HY, MRL, IK), pp. 233–242.

CIKM-2008-MaYLK08a #matrix #named #probability #recommendation #social #using

SoRec: social recommendation using probabilistic matrix factorization (HM, HY, MRL, IK), pp. 931–940.

CIKM-2008-XuJHLK #categorisation

Semi-supervised text categorization by active search (ZX, RJ, KH, MRL, IK), pp. 1517–1518.

ICDAR-2007-WeiKL

Bibliographic Attributes Extraction with Layer-upon-Layer Tagging (WW, IK, JHML), pp. 804–808.

SIGIR-2007-MaKL #collaboration #effectiveness #predict

Effective missing data prediction for collaborative filtering (HM, IK, MRL), pp. 39–46.

SIGIR-2007-YangKL #named #web

DiffusionRank: a possible penicillin for web spamming (HY, IK, MRL), pp. 431–438.

ICML-2004-HuangYKL #classification #learning #scalability

Learning large margin classifiers locally and globally (KH, HY, IK, MRL).

MLDM-1999-KingL #clustering #information retrieval #learning

Non-hierarchical Clustering with Rival Penalized Competitive Learning for Information Retrieval (IK, TKL), pp. 116–130.

ICPR-1998-DuanKC0 #algorithm

Intra-block algorithm for digital watermarking (FYD, IK, LWC, LX), pp. 1589–1591.

ICPR-1996-FungLK #2d #detection #random

Randomized generalized Hough transform for 2-D gray scale object detection (PFF, WSL, IK), pp. 511–515.

JCDL-2012-DengHLK #modelling #network #ranking

Modeling and exploiting heterogeneous bibliographic networks for expertise ranking (HD, JH, MRL, IK), pp. 71–80.

ESEC-FSE-2018-GaoZ0LLK #named

INFAR: insight extraction from app reviews (CG, JZ, DL0, CYL, MRL, IK), pp. 904–907.

ASE-2019-GaoZX0LK #automation #generative #overview

Automating App Review Response Generation (CG, JZ, XX0, DL0, MRL, IK), pp. 163–175.