Stem crowd$ (all stems)

160 papers:

HT-2015-Baeza-YatesS #analysis #generative

Wisdom of the Crowd or Wisdom of a Few?: An Analysis of Users’ Content Generation (RABY, DST), pp. 69–74.

HT-2015-GadirajuSFK #behaviour #categorisation #comprehension

Breaking Bad: Understanding Behavior of Crowd Workers in Categorization Microtasks (UG, PS, BF, RK), pp. 33–38.

SIGMOD-2015-AmsterdamerKM #interface #mining #named #natural language

NL2CM: A Natural Language Interface to Crowd Mining (YA, AK, TM), pp. 1433–1438.

SIGMOD-2015-HungTWA #validation

Minimizing Efforts in Validating Crowd Answers (NQVH, DCT, MW, KA), pp. 999–1014.

SIGMOD-2015-WangXL #adaptation #approach

Crowd-Based Deduplication: An Adaptive Approach (SW, XX, CHL), pp. 1263–1277.

SANER-2015-SassoML #detection #problem

Misery loves company: CrowdStacking traces to aid problem detection (TDS, AM, ML), pp. 131–140.

CHI-2015-0005RSP #mobile #named #physics #process

CrowdMonitor: Mobile Crowd Sensing for Assessing Physical and Digital Activities of Citizens during Emergencies (TL, CR, TS, VP), pp. 4083–4092.

CHI-2015-FlinthamVWABBPP

Run Spot Run: Capturing and Tagging Footage of a Race by Crowds of Spectators (MDF, RV, MLW, EJA, SB, AB, TP, DP, JS), pp. 747–756.

CHI-2015-LaseckiRMB #sequence

The Effects of Sequence and Delay on Crowd Work (WSL, JMR, AM, JPB), pp. 1375–1378.

CHI-2015-LesselAK #analysis #people

Analysis of Recycling Capabilities of Individuals and Crowds to Encourage and Educate People to Separate Their Garbage Playfully (PL, MA, AK), pp. 1095–1104.

CHI-2015-RobertR #performance

Crowd Size, Diversity and Performance (LR, DMR), pp. 1379–1382.

CHI-2015-SalehiIBAOMC

We Are Dynamo: Overcoming Stalling and Friction in Collective Action for Crowd Workers (NS, LI, MSB, AA, EO, KM, C), pp. 1621–1630.

CSCW-2015-ChengB #classification #hybrid #machine learning #named

Flock: Hybrid Crowd-Machine Learning Classifiers (JC, MSB), pp. 600–611.

CSCW-2015-ChengSMFHD #eye tracking #online #social

Social Eye Tracking: Gaze Recall with Online Crowds (SC, ZS, XM, JLF, SEH, AKD), pp. 454–463.

CSCW-2015-GuyHC #crowdsourcing #enterprise #framework #game studies

Games for Crowds: A Crowdsourcing Game Platform for the Enterprise (IG, AH, YC), pp. 1860–1871.

CSCW-2015-KobayashiAIST #multi

Motivating Multi-Generational Crowd Workers in Social-Purpose Work (MK, SA, TI, SS, HT), pp. 1813–1824.

CSCW-2015-QuattroneCM #bias #dataset

There’s No Such Thing as the Perfect Map: Quantifying Bias in Spatial Crowd-sourcing Datasets (GQ, LC, PDM), pp. 1021–1032.

CSCW-2015-WangWWSZZZ #collaboration

Crowds on Wall Street: Extracting Value from Collaborative Investing Platforms (GW, TW, BW, DS, ZZ, HZ, BYZ), pp. 17–30.

CSCW-2015-XuRDB #design #feedback #process #using

A Classroom Study of Using Crowd Feedback in the Iterative Design Process (AX, HR, SPD, BPB), pp. 1637–1648.

HCI-IT-2015-ScavarelliA #interactive

An Exploration of Shape in Crowd Computer Interactions (AS, AA), pp. 775–786.

KDD-2015-MaLLQGZSZJH #crowdsourcing #fine-grained #named

FaitCrowd: Fine Grained Truth Discovery for Crowdsourced Data Aggregation (FM, YL, QL, MQ, JG, SZ, LS, BZ, HJ, JH), pp. 745–754.

KDD-2015-ShashidharPA #machine learning

Spoken English Grading: Machine Learning with Crowd Intelligence (VS, NP, VA), pp. 2089–2097.

RecSys-2015-DalyBS #recommendation

Crowd Sourcing, with a Few Answers: Recommending Commuters for Traffic Updates (ED, MB, FS), pp. 253–256.

RecSys-2015-KazaiCYV #personalisation

A Personalised Reader for Crowd Curated Content (GK, DC, IY, MV), pp. 325–326.

SIGIR-2015-HungTWA #named #validation

ERICA: Expert Guidance in Validating Crowd Answers (NQVH, DCT, MW, KA), pp. 1037–1038.

POPL-2015-CochranDLMV #synthesis

Program Boosting: Program Synthesis via Crowd-Sourcing (RAC, LD, BL, DM, MV), pp. 677–688.

REFSQ-2015-GroenDA #perspective #requirements #research #towards

Towards Crowd-Based Requirements Engineering A Research Preview (ECG, JD, SA), pp. 247–253.

SAC-2015-JuniorDOFB #performance #web

Handling flash-crowd events to improve the performance of web applications (UdPJ, LMdAD, DdO, YF, VCB), pp. 769–774.

ESEC-FSE-2015-ChenK #debugging

Crowd debugging (FC, SK), pp. 320–332.

ICSE-v1-2015-LaTozaCJZH #case study #contest #design

Borrowing from the Crowd: A Study of Recombination in Software Design Competitions (TDL, MC, LJ, MZ, AvdH), pp. 551–562.

ICSE-v2-2015-GomezMMR #debugging

When App Stores Listen to the Crowd to Fight Bugs in the Wild (MG, MM, MM, RR), pp. 567–570.

ICSE-v2-2015-LaTozaH #development

A Vision of Crowd Development (TDL, AvdH), pp. 563–566.

ASE-2014-HamidiAL #adaptation #using

Constructing adaptive configuration dialogs using crowd data (SH, PA, SL), pp. 485–490.

DAC-2014-WietfeldID #mobile #performance

Resource Efficient Mobile Communications for Crowd-Sensing (CW, CI, BD), p. 6.

HT-2014-Baeza-Yates #ad hoc

The wisdom of ad-hoc crowds (RABY), pp. 1–2.

HT-2014-KawaseSNHN

Exploiting the wisdom of the crowds for characterizing and connecting heterogeneous resources (RK, PS, BPN, EH, WN), pp. 56–65.

SIGMOD-2014-AmsterdamerDMNS #mining #named #query

OASSIS: query driven crowd mining (YA, SBD, TM, SN, AS), pp. 589–600.

SIGMOD-2014-MuhlbauerRSRK0

One DBMS for all: the brawny few and the wimpy crowd (TM, WR, RS, AR, AK, TN), pp. 697–700.

SIGMOD-2014-ParameswaranTGW #named #tool support

DataSift: a crowd-powered search toolkit (AGP, MHT, HGM, JW), pp. 885–888.

SIGMOD-2014-ParkW #named

CrowdFill: collecting structured data from the crowd (HP, JW), pp. 577–588.

SIGMOD-2014-ZhangZCJC #named

CrowdMatcher: crowd-assisted schema matching (CJZ, ZZ, LC, HVJ, CCC), pp. 721–724.

VLDB-2014-AmsterdamerDMNS #mining #ontology

Ontology Assisted Crowd Mining (YA, SBD, TM, SN, AS), pp. 1597–1600.

VLDB-2014-ParameswaranBG0PW #algorithm #rating

Optimal Crowd-Powered Rating and Filtering Algorithms (AGP, SB, HGM, AG, NP, JW), pp. 685–696.

VLDB-2014-ZhangTC

Where To: Crowd-Aided Path Selection (CJZ, YT, LC), pp. 2005–2016.

VLDB-2015-MozafariSFJM14 #dataset #learning #scalability

Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning (BM, PS, MJF, MIJ, SM), pp. 125–136.

ICPC-2014-SouzaCM #development #ranking

Ranking crowd knowledge to assist software development (LBLdS, ECC, MdAM), pp. 72–82.

CIAA-2014-Sirakoulis #automaton

Cellular Automata for Crowd Dynamics (GCS), pp. 58–69.

CHI-2014-BighamL #information management

Crowd storage: storing information on existing memories (JPB, WSL), pp. 601–604.

CHI-2014-FastSWBB #ide #programming

Emergent, crowd-scale programming practice in the IDE (EF, DS, LW, JRB, MSB), pp. 2491–2500.

CHI-2014-LaseckiWFB #dependence #using

Finding dependencies between actions using the crowd (WSL, LW, GF, JPB), pp. 3095–3098.

CHI-2014-PiccardiCZWA #towards

Towards crowd-based customer service: a mixed-initiative tool for managing Q&A sites (TP, GC, MZ, JW, CA), pp. 2725–2734.

CHI-2014-VaishWCCB #crowdsourcing

Twitch crowdsourcing: crowd contributions in short bursts of time (RV, KW, JC, BC, MSB), pp. 3645–3654.

CHI-2014-YuKK

Searching for analogical ideas with crowds (LY, AK, REK), pp. 1225–1234.

CHI-2014-YuKK14a #distributed #generative #idea

Distributed analogical idea generation: inventing with crowds (LY, AK, REK), pp. 1245–1254.

CSCW-2014-AndreKD #category theory #clustering #synthesis

Crowd synthesis: extracting categories and clusters from complex data (PA, AK, SPD), pp. 989–998.

CSCW-2014-CrossBRCT #education #named #online

VidWiki: enabling the crowd to improve the legibility of online educational videos (AC, MB, DR, EC, WT), pp. 1167–1175.

CSCW-2014-KimCB #collaboration #named

Ensemble: exploring complementary strengths of leaders and crowds in creative collaboration (JK, JC, MSB), pp. 745–755.

CSCW-2014-LaseckiTK #information management

Information extraction and manipulation threats in crowd-powered systems (WSL, JT, EK), pp. 248–256.

CSCW-2014-QuattroneMC #behaviour

Mind the map: the impact of culture and economic affluence on crowd-mapping behaviours (GQ, AJM, LC), pp. 934–944.

CSCW-2014-XuHB #design #feedback #generative #named #using #visual notation

Voyant: generating structured feedback on visual designs using a crowd of non-experts (AX, SWH, BPB), pp. 1433–1444.

CSCW-2014-YuAKK #comparison #learning #quality #social

A comparison of social, learning, and financial strategies on crowd engagement and output quality (LY, PA, AK, RK), pp. 967–978.

CSCW-2014-ZhuDKK #assessment #learning #performance

Reviewing versus doing: learning and performance in crowd assessment (HZ, SPD, REK, AK), pp. 1445–1455.

DUXU-DI-2014-Al-SalhieAA #detection #multi

Multimedia Surveillance in Event Detection: Crowd Analytics in Hajj (LAS, MAZ, AAW), pp. 383–392.

SCSM-2014-LeonardoFGPSSUWC #identification #social #social media #trust

Identifying Locations of Social Significance: Aggregating Social Media Content to Create a New Trust Model for Exploring Crowd Sourced Data and Information (ADL, SF, AG, FP, WS, TS, AU, DW, JBC), pp. 170–177.

CIKM-2014-Zhang0T #collaboration #framework #named #probability #query

MaC: A Probabilistic Framework for Query Answering with Machine-Crowd Collaboration (CJZ, LC, YT), pp. 11–20.

ICML-c2-2014-SinglaBBKK #education

Near-Optimally Teaching the Crowd to Classify (AS, IB, GB, AK, AK), pp. 154–162.

ICML-c2-2014-ZhouLPM

Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy (DZ, QL, JCP, CM), pp. 262–270.

ICPR-2014-BeraM #multi #realtime #using

Realtime Multilevel Crowd Tracking Using Reciprocal Velocity Obstacles (AB, DM), pp. 4164–4169.

ICPR-2014-Climent-PerezMR #detection #multi #using

Multi-view Event Detection in Crowded Scenes Using Tracklet Plots (PCP, DNM, PR), pp. 4370–4375.

ICPR-2014-FradiD #detection #recognition

Sparse Feature Tracking for Crowd Change Detection and Event Recognition (HF, JLD), pp. 4116–4121.

ICPR-2014-KimBKC #multi #online #people

MAP-Based Online Data Association for Multiple People Tracking in Crowded Scenes (SWK, MB, KK, JYC), pp. 1212–1217.

ICPR-2014-LimKLC #detection #similarity

Crowd Saliency Detection via Global Similarity Structure (MKL, VJK, CCL, CSC), pp. 3957–3962.

ICPR-2014-LuWMST #detection #modelling

Anomaly Detection through Spatio-temporal Context Modeling in Crowded Scenes (TL, LW, XM, PS, CLT), pp. 2203–2208.

ICPR-2014-ZouYCDJ #clustering #correlation #topic #video

A Belief Based Correlated Topic Model for Trajectory Clustering in Crowded Video Scenes (JZ, QY, YC, DSD, JJ), pp. 2543–2548.

KDD-2014-Cao0J #elicitation #online

From labor to trader: opinion elicitation via online crowds as a market (CCC, LC, HVJ), pp. 1067–1076.

KDD-2014-TongCC #named #performance #topic

TCS: efficient topic discovery over crowd-oriented service data (YT, CCC, LC), pp. 861–870.

KDD-2014-WangWW

Quantifying herding effects in crowd wisdom (TW, DW, FW), pp. 1087–1096.

MLDM-2014-AnandWA #information management #scalability

A Method of Crowd-Sourced Information Extraction From Large Data Files (IMA, AW, PA), pp. 431–436.

RE-2014-BreauxS #policy #privacy #requirements #scalability

Scaling requirements extraction to the crowd: Experiments with privacy policies (TDB, FS), pp. 163–172.

ICSE-2014-StolF #case study #crowdsourcing #development

Two’s company, three’s a crowd: a case study of crowdsourcing software development (KJS, BF), pp. 187–198.

HT-2013-LiangCCK #how #modelling #social #social media

How big is the crowd?: event and location based population modeling in social media (YL, JC, ZC, KYK), pp. 99–108.

SIGMOD-2013-AmsterdamerGMS #mining

Crowd mining (YA, YG, TM, PS), pp. 241–252.

VLDB-2013-AmsterdamerGMS #mining #named

CrowdMiner: Mining association rules from the crowd (YA, YG, TM, PS), pp. 1250–1253.

VLDB-2013-KaplanLMN #query

Answering Planning Queries with the Crowd (HK, IL, TM, SN), pp. 697–708.

VLDB-2013-WhangLG

Question Selection for Crowd Entity Resolution (SEW, PL, HGM), pp. 349–360.

CSMR-2013-PonzanelliBL #comprehension #development

Leveraging Crowd Knowledge for Software Comprehension and Development (LP, AB, ML), pp. 57–66.

CHI-2013-DowGW #case study #using

A pilot study of using crowds in the classroom (SD, EG, AW), pp. 227–236.

CHI-2013-HuangF #crowdsourcing #exclamation #social

Don’t hide in the crowd!: increasing social transparency between peer workers improves crowdsourcing outcomes (SWH, WTF), pp. 621–630.

CHI-2013-LeeKYSG #mobile

Analyzing crowd workers in mobile pay-for-answer q&a (UL, JK, EY, JS, MG), pp. 533–542.

CSCW-2013-KitturNBGSZLH #future of

The future of crowd work (AK, JVN, MSB, EG, ADS, JZ, ML, JH), pp. 1301–1318.

CSCW-2013-LaseckiSKB #process #realtime #recognition

Real-time crowd labeling for deployable activity recognition (WSL, YCS, HAK, JPB), pp. 1203–1212.

CSCW-2013-MashhadiQC #ubiquitous

Putting ubiquitous crowd-sourcing into context (AJM, GQ, LC), pp. 611–622.

CSCW-2013-ParkSLB #contest #design #scalability

Crowd vs. crowd: large-scale cooperative design through open team competition (CHP, KS, JHL, SHB), pp. 1275–1284.

DHM-SET-2013-Yamamoto #modelling

Investigation of an Agent-Based Modeling on Crowd Evacuation and Its Application to Real Buildings (FY), pp. 373–382.

DUXU-CXC-2013-KuramotoIYT #exclamation #gamification #people

Stand Up, Heroes! : Gamification for Standing People on Crowded Public Transportation (IK, TI, KY, YT), pp. 538–547.

ECIR-2013-0001S #game studies #query #refinement

Comparing Crowd-Based, Game-Based, and Machine-Based Approaches in Initial Query and Query Refinement Tasks (CGH, PS), pp. 495–506.

KDD-2013-JoglekarGP

Evaluating the crowd with confidence (MJ, HGM, AGP), pp. 686–694.

KDD-2013-ZhaoYNG #framework #learning #twitter

A transfer learning based framework of crowd-selection on twitter (ZZ, DY, WN, SG), pp. 1514–1517.

SAC-2013-BraunCHMM #framework #named #realtime #visualisation

CrowdVis: a framework for real time crowd visualization (HB, VJC, RH, FPM, SRM), pp. 989–995.

ICST-2013-PastoreMF #named #problem #question

CrowdOracles: Can the Crowd Solve the Oracle Problem? (FP, LM, GF), pp. 342–351.

DAC-2012-LiSJ #crowdsourcing #named #towards #verification

CrowdMine: towards crowdsourced human-assisted verification (WL, SAS, SJ), pp. 1254–1255.

DAC-2012-ZhaoSL #3d #analysis

Analysis of DC current crowding in through-silicon-vias and its impact on power integrity in 3D ICs (XZ, MS, SKL), pp. 157–162.

SIGMOD-2012-GuoPG

So who won?: dynamic max discovery with the crowd (SG, AGP, HGM), pp. 385–396.

SIGMOD-2012-ParameswaranGPPRW #algorithm #named

CrowdScreen: algorithms for filtering data with humans (AGP, HGM, HP, NP, AR, JW), pp. 361–372.

VLDB-2012-MorishimaSMAF #crowdsourcing #declarative #framework #named

CyLog/Crowd4U: A Declarative Platform for Complex Data-centric Crowdsourcing (AM, NS, TM, HA, SF), pp. 1918–1921.

VLDB-2012-SelkeLB #bound #database

Pushing the Boundaries of Crowd-enabled Databases with Query-driven Schema Expansion (JS, CL, WTB), pp. 538–549.

VLDB-2012-WangKFF #crowdsourcing #named

CrowdER: Crowdsourcing Entity Resolution (JW, TK, MJF, JF), pp. 1483–1494.

VLDB-2013-0002KMMO12

Counting with the Crowd (AM, DRK, SM, RM, SO), pp. 109–120.

CHI-2012-GomezL #interactive #modelling #performance

Modeling task performance for a crowd of users from interaction histories (SRG, DHL), pp. 2465–2468.

CHI-2012-HeimerlGCPH #named #physics

CommunitySourcing: engaging local crowds to perform expert work via physical kiosks (KH, BG, KC, TSP, BH), pp. 1539–1548.

CHI-2012-OuyangL #gesture #recognition

Bootstrapping personal gesture shortcuts with the wisdom of the crowd and handwriting recognition (TO, YL), pp. 2895–2904.

CHI-2012-TangB #video

#EpicPlay: crowd-sourcing sports video highlights (AT, SB), pp. 1569–1572.

CSCW-2012-DabbishFKP #online

Fresh faces in the crowd: turnover, identity, and commitment in online groups (LAD, RF, RK, TP), pp. 245–248.

CSCW-2012-DowKKH

Shepherding the crowd yields better work (SD, APK, SRK, BH), pp. 1013–1022.

CSCW-2012-KitturKAK #named #visual notation

CrowdWeaver: visually managing complex crowd work (AK, SK, PA, RK), pp. 1033–1036.

CIKM-2012-KamathC #realtime #retrieval #web

Content-based crowd retrieval on the real-time web (KYK, JC), pp. 195–204.

CIKM-2012-WhitingZJAL #named

CrowdTiles: presenting crowd-based information for event-driven information needs (SW, KZ, JMJ, OA, TL), pp. 2698–2700.

ECIR-2012-HosseiniCMKV #documentation #multi #on the

On Aggregating Labels from Multiple Crowd Workers to Infer Relevance of Documents (MH, IJC, NMF, GK, VV), pp. 182–194.

ICPR-2012-IwasakiKN #segmentation

Dense motion segmentation of articulated objects in crowds (MI, AK, KN), pp. 861–865.

ICPR-2012-JinB #multi #simulation

Single camera multi-person tracking based on crowd simulation (ZJ, BB), pp. 3660–3663.

KDD-2012-TianZ #learning

Learning from crowds in the presence of schools of thought (YT, JZ), pp. 226–234.

KDD-2012-ZhangTLCJWL #web

Harnessing the wisdom of the crowds for accurate web page clipping (LZ, LT, PL, EC, LJ, MW, GL), pp. 570–578.

SIGIR-2012-JungL #matrix #probability

Inferring missing relevance judgments from crowd workers via probabilistic matrix factorization (HJJ, ML), pp. 1095–1096.

SIGIR-2012-McCreadieMO #automation #crowdsourcing #named

CrowdTerrier: automatic crowdsourced relevance assessments with terrier (RM, CM, IO), p. 1005.

HT-2011-AshmanACST

Implicit association via crowd-sourced coselection (HA, MA, SC, GS, MT), pp. 7–16.

SIGMOD-2011-FranklinKKRX #crowdsourcing #named #query

CrowdDB: answering queries with crowdsourcing (MJF, DK, TK, SR, RX), pp. 61–72.

VLDB-2011-FengFKKMRWX #named #query

CrowdDB: Query Processing with the VLDB Crowd (AF, MJF, DK, TK, SM, SR, AW, RX), pp. 1387–1390.

FASE-2011-MassinkLBH #modelling

Modelling Non-linear Crowd Dynamics in Bio-PEPA (MM, DL, AB, JH), pp. 96–110.

CHI-2011-YuN

Cooks or cobblers?: crowd creativity through combination (LY, JVN), pp. 1393–1402.

CHI-2011-ZimmermanTGYHATHS #co-evolution #design

Field trial of Tiramisu: crowd-sourcing bus arrival times to spur co-design (JZ, AT, CG, DY, CH, RA, NRT, YH, AS), pp. 1677–1686.

OCSC-2011-OhiraMM #communication #interactive #interface #named #online #visual notation

CICRO: An Interactive Visual Interface for Crowd Communication Online (MO, HM, KiM), pp. 251–260.

ICML-2011-TamuzLBSK #adaptation #kernel #learning

Adaptively Learning the Crowd Kernel (OT, CL, SB, OS, AK), pp. 673–680.

ICML-2011-YanRFD #learning

Active Learning from Crowds (YY, RR, GF, JGD), pp. 1161–1168.

KDD-2011-LiL #behaviour #community #detection #framework #generative #modelling #network #simulation #social

Social flocks: a crowd simulation framework for social network generation, community detection, and collective behavior modeling (CTL, SDL), pp. 765–768.

SIGIR-2011-CaverleeCEHKM #monitoring #named #realtime #web

CrowdTracker: enabling community-based real-time web monitoring (JC, ZC, BE, CFH, KYK, JM), pp. 1283–1284.

SIGIR-2011-FeildAG #distributed #named

CrowdLogging: distributed, private, and anonymous search logging (HAF, JA, JG), pp. 375–384.

SIGIR-2011-KumarL #learning #rank

Learning to rank from a noisy crowd (AK, ML), pp. 1221–1222.

SIGMOD-2010-Amer-YahiaDKKF #algorithm #big data

Crowds, clouds, and algorithms: exploring the human side of “big data” applications (SAY, AD, JMK, NK, MJF), pp. 1259–1260.

CIKM-2010-LuETP #clustering #video #visualisation

Visualization and clustering of crowd video content in MPCA subspace (HL, HLE, MT, KNP), pp. 1777–1780.

ICPR-2010-FengZH #detection #learning #online #self

Online Learning with Self-Organizing Maps for Anomaly Detection in Crowd Scenes (JF, CZ, PH), pp. 3599–3602.

ICPR-2010-GuoM #detection #using

Action Detection in Crowded Videos Using Masks (PG, ZM), pp. 1767–1770.

ICPR-2010-OzturkYA #detection

Detecting Dominant Motion Flows in Unstructured/Structured Crowd Scenes (OO, TY, KA), pp. 3533–3536.

ICPR-2010-SrikrishnanC #analysis #linear #using

Crowd Motion Analysis Using Linear Cyclic Pursuit (VS, SC), pp. 3340–3343.

ICPR-2010-WidhalmB #learning

Learning Major Pedestrian Flows in Crowded Scenes (PW, NB), pp. 4064–4067.

CIKM-2009-MohammedFD #analysis

Walking in the crowd: anonymizing trajectory data for pattern analysis (NM, BCMF, MD), pp. 1441–1444.

SIGIR-2009-LiuMH #multi #named #ranking #visual notation

CrowdReranking: exploring multiple search engines for visual search reranking (YL, TM, XSH), pp. 500–507.

CASE-2008-WangLCS #modelling #optimisation

Modeling and optimization of crowd guidance for building emergency evacuation (PW, PBL, SCC, JS), pp. 328–334.

CSCW-2008-KitturK #coordination #quality #wiki

Harnessing the wisdom of crowds in wikipedia: quality through coordination (AK, REK), pp. 37–46.

CSCW-2008-SinghT #interactive

The confusion of crowds: non-dyadic help interactions (VS, MBT), pp. 699–702.

ICPR-2008-HuAS08a #learning #using

Learning motion patterns in crowded scenes using motion flow field (MH, SA, MS), pp. 1–5.

ICPR-2008-IhaddadeneD #analysis #realtime

Real-time crowd motion analysis (NI, CD), pp. 1–4.

SAC-2008-VizzariPS #3d #execution #framework #simulation #visualisation

A framework for execution and 3D visualization of situated cellular agent based crowd simulations (GV, GP, FSCdS), pp. 18–22.

CSCW-2006-LampeES #social

A face(book) in the crowd: social Searching vs. social browsing (CL, NBE, CS), pp. 167–170.

ICPR-v1-2006-AndradeBF #detection #modelling

Modelling Crowd Scenes for Event Detection (ELA, SB, RBF), pp. 175–178.

ICPR-v1-2006-AndradeBF06a #analysis #markov #modelling

Hidden Markov Models for Optical Flow Analysis in Crowds (ELA, SB, RBF), pp. 460–463.

ICPR-v3-2006-KongGT #approach #invariant

A Viewpoint Invariant Approach for Crowd Counting (DK, DG, HT), pp. 1187–1190.

ICPR-v3-2006-TsaiSH #multi

Multiple Human Objects Tracking in Crowded Scenes (YTT, HCS, CLH), pp. 51–54.

ICPR-v4-2006-CuiZZS #multi #people #robust #using

Robust Tracking of Multiple People in Crowds Using Laser Range Scanners (JC, HZ, HZ, RS), pp. 857–860.

SAC-2006-PanAHSY #named #network

FCAN: Flash Crowds Alleviation Network (CP, MA, MBH, TS, NY), pp. 759–765.

CHI-1997-BenfordGL #collaboration

Crowded Collaborative Virtual Environments (SB, CG, DL), pp. 59–66.