BibSLEIGH
BibSLEIGH corpus
BibSLEIGH tags
BibSLEIGH bundles
BibSLEIGH people
CC-BY
Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
email twitter
Used together with:
start (30)
recommend (25)
user (7)
system (7)
base (6)

Stem cold$ (all stems)

42 papers:

HCIDUXU-DD-2015-BystrickyB
The Cold Desert of Software Reality (JB, JB), pp. 3–11.
KDDKDD-2015-ZhangW #recommendation
A Collective Bayesian Poisson Factorization Model for Cold-start Local Event Recommendation (WZ, JW), pp. 1455–1464.
RecSysRecSys-2015-AharonAADGS #named #recommendation
ExcUseMe: Asking Users to Help in Item Cold-Start Recommendations (MA, OA, NAE, DDC, SG, OS), pp. 83–90.
RecSysRecSys-2015-BarjastehFMER #recommendation
Cold-Start Item and User Recommendation with Decoupled Completion and Transduction (IB, RF, FM, AHE, HR), pp. 91–98.
RecSysRecSys-2015-GrausW #elicitation #experience #user interface
Improving the User Experience during Cold Start through Choice-Based Preference Elicitation (MPG, MCW), pp. 273–276.
VLDBVLDB-2014-EldawyLL #database
Trekking Through Siberia: Managing Cold Data in a Memory-Optimized Database (AE, JJL, PÅL), pp. 931–942.
CIKMCIKM-2014-ZhaoCWZNW #named #social
SocialTransfer: Transferring Social Knowledge for Cold-Start Cowdsourcing (ZZ, JC, FW, MZ, WN, YW), pp. 779–788.
ICMLICML-c2-2014-HoulsbyHG #learning #matrix #robust
Cold-start Active Learning with Robust Ordinal Matrix Factorization (NH, JMHL, ZG), pp. 766–774.
RecSysRecSys-2014-Braunhofer #recommendation
Hybridisation techniques for cold-starting context-aware recommender systems (MB), pp. 405–408.
RecSysRecSys-2014-BraunhoferCR #hybrid #recommendation
Switching hybrid for cold-starting context-aware recommender systems (MB, VC, FR), pp. 349–352.
RecSysRecSys-2014-SaveskiM #learning #recommendation
Item cold-start recommendations: learning local collective embeddings (MS, AM), pp. 89–96.
RecSysRecSys-2014-SedhainSBXC #collaboration #recommendation #social
Social collaborative filtering for cold-start recommendations (SS, SS, DB, LX, JC), pp. 345–348.
RecSysRecSys-2014-TrevisiolASJ #graph #recommendation
Cold-start news recommendation with domain-dependent browse graph (MT, LMA, RS, AJ), pp. 81–88.
SEKESEKE-2014-TianWHZG #feedback #recommendation #using #web #web service
Cold-Start Web Service Recommendation Using Implicit Feedback (GT, JW, KH, WZ, PG), pp. 371–376.
SIGIRSIGIR-2014-ZhangTZX #algorithm #recommendation
Addressing cold start in recommender systems: a semi-supervised co-training algorithm (MZ, JT, XZ, XX), pp. 73–82.
OSDIOSDI-2014-BalakrishnanBDEGHLOPR #named
Pelican: A Building Block for Exascale Cold Data Storage (SB, RB, AD, PE, AG, DH, SL, AO, EP, AITR), pp. 351–365.
VLDBVLDB-2013-AlexiouKL #adaptation
Adaptive Range Filters for Cold Data: Avoiding Trips to Siberia (KA, DK, PÅL), pp. 1714–1725.
RecSysRecSys-2013-AharonABLABLRS #named #online #persistent #recommendation #set
OFF-set: one-pass factorization of feature sets for online recommendation in persistent cold start settings (MA, NA, EB, RL, RA, TB, LL, RR, OS), pp. 375–378.
RecSysRecSys-2013-Guo #recommendation #similarity #trust
Integrating trust and similarity to ameliorate the data sparsity and cold start for recommender systems (GG), pp. 451–454.
SIGIRSIGIR-2013-LinSKC #modelling #recommendation #twitter
Addressing cold-start in app recommendation: latent user models constructed from twitter followers (JL, KS, MYK, TSC), pp. 283–292.
HPCAHPCA-2013-ZebchukCTSM #named
RECAP: A region-based cure for the common cold (cache) (JZ, HWC, XT, VS, AM), pp. 83–94.
CHICHI-2012-HalveyWBH #feedback #quote
“Baby it’s cold outside”: the influence of ambient temperature and humidity on thermal feedback (MH, GW, SAB, SAH), pp. 715–724.
RecSysRecSys-2012-LeviMDT #recommendation
Finding a needle in a haystack of reviews: cold start context-based hotel recommender system (AL, OM, CD, NT), pp. 115–122.
RecSysRecSys-2012-LeviMDT12a #recommendation
Finding a needle in a haystack of reviews: cold start context-based hotel recommender system demo (AL, OM, CD, NT), pp. 305–306.
SACSAC-2012-SaidJA #collaboration
Analyzing weighting schemes in collaborative filtering: cold start, post cold start and power users (AS, BJJ, SA), pp. 2035–2040.
ICSEICSE-2012-ForbesKR #challenge #navigation #open source #research
When open source turns cold on innovation — The challenges of navigating licensing complexities in new research domains (CF, IK, JR), pp. 1447–1448.
HCIHIMI-v1-2011-NakanishiY #using
Applicability of Touch Sense Controllers Using Warm and Cold Sensations (MN, SY), pp. 470–477.
ICEISICEIS-v4-2011-LiangY #enterprise #how
How to Control the Distribution Cost of the Cold Chain Logistics Enterprise (SXL, GY), pp. 716–719.
RecSysRecSys-2011-LiuMLY #elicitation #rating #recommendation
Wisdom of the better few: cold start recommendation via representative based rating elicitation (NNL, XM, CL, QY), pp. 37–44.
SIGIRSIGIR-2011-ZhouYZ #functional #matrix #recommendation
Functional matrix factorizations for cold-start recommendation (KZ, SHY, HZ), pp. 315–324.
KDDKDD-2010-LeroyCB #predict
Cold start link prediction (VL, BBC, FB), pp. 393–402.
RecSysRecSys-2009-CremonesiT #analysis #recommendation
Analysis of cold-start recommendations in IPTV systems (PC, RT), pp. 233–236.
RecSysRecSys-2009-GivonL #predict #recommendation
Predicting social-tags for cold start book recommendations (SG, VL), pp. 333–336.
RecSysRecSys-2009-ParkC #recommendation
Pairwise preference regression for cold-start recommendation (STP, WC), pp. 21–28.
RecSysRecSys-2008-GunawardanaM #recommendation
Tied boltzmann machines for cold start recommendations (AG, CM), pp. 19–26.
SACSAC-2008-VictorCTC #recommendation #trust
Whom should I trust?: the impact of key figures on cold start recommendations (PV, CC, AT, MDC), pp. 2014–2018.
RecSysRecSys-2007-NguyenDB #induction #recommendation #rule-based
Improving new user recommendations with rule-based induction on cold user data (ATN, ND, CB), pp. 121–128.
KDDKDD-2006-ParkPMGD #recommendation #robust
Naïve filterbots for robust cold-start recommendations (STP, DP, OM, NG, DD), pp. 699–705.
SIGIRSIGIR-2002-ScheinPUP #metric #recommendation
Methods and metrics for cold-start recommendations (AIS, AP, LHU, DMP), pp. 253–260.
FMVDME-1991-1-Bril #algebra #specification #using
A Model-Oriented Method for Algebraic Specification using COLD-1 as Notation (RJB), pp. 106–124.
FMVDME-1991-1-MiddelburgL #comparison #logic
LPF and MPLω — A Logical Comparison of VDM SL and COLD-K (CAM, GRRdL), pp. 279–308.
ESECESEC-1991-Linden #specification
Specification in COLD-1 of a CAD-Package for Drawing Shadow Masks (FvdL), pp. 101–121.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.