Travelled to:
1 × Brazil
1 × Canada
1 × Chile
1 × France
1 × Greece
1 × Korea
1 × Russia
1 × South Korea
2 × USA
3 × China
Collaborated with:
M.A.Gonçalves F.Belém F.Figueiredo F.Benevenuto V.Almeida M.A.Vasconcelos T.Pontes E.F.Martins C.P.Costa A.Veloso M.Nezhadbiglari P.Figueira G.Pacheco K.P.Gummadi E.Santos-Neto M.Ripeanu G.D.Gonçalves R.L.T.Santos V.Soares M.Sumbana R.S.Oliveira A.A.Ferreira A.H.F.Laender T.Rodrigues V.A.F.Almeida F.Atalla D.Miranda J.Padilha J.A.Pereira E.Figueiredo A.Garcia C.Sant'Anna K.C.Gonçalves A.B.Vieira A.P.C.d.Silva H.T.M.Neto S.V.A.Campos S.M.R.Ricci D.A.Guimarães F.M.Belém R.O.Prates M.Mowbray V.C.d.Oliveira G.d.C.M.Gomes W.C.Brandão N.Ziviani H.Pinto D.F.d.Oliveira E.S.d.Moura M.Cristo
Talks about:
popular (7) recommend (5) content (5) peer (5) tag (5) studi (4) textual (3) scholar (3) qualiti (3) network (3)
Person: Jussara M. Almeida
DBLP: Almeida:Jussara_M=
Contributed to:
Wrote 20 papers:
- TPDL-2015-FigueiraPAG #case study #on the
- On the Impact of Academic Factors on Scholar Popularity: A Cross-Area Study (PF, GP, JMA, MAG), pp. 139–152.
- CAiSE-2014-PadilhaPFAGS #detection #effectiveness #empirical #metric #on the #smell
- On the Effectiveness of Concern Metrics to Detect Code Smells: An Empirical Study (JP, JAP, EF, JMA, AG, CS), pp. 656–671.
- CHI-2014-FigueiredoABG #case study #social #social media
- Does content determine information popularity in social media?: a case study of youtube videos’ content and their popularity (FF, JMA, FB, KPG), pp. 979–982.
- HT-2014-Santos-NetoPAR #data flow #on the #optimisation
- On the choice of data sources to improve content discoverability via textual feature optimization (ESN, TP, JMA, MR), pp. 273–278.
- JCDL-2014-GoncalvesFAG #case study #community #research
- Characterizing scholar popularity: A case study in the Computer Science research community (GDG, FF, JMA, MAG), pp. 57–66.
- SAC-2014-VasconcelosAG #code review #predict #what
- What makes your opinion popular?: predicting the popularity of micro-reviews in foursquare (MAV, JMA, MAG), pp. 598–603.
- ECIR-2013-BelemMAG #recommendation
- Exploiting Novelty and Diversity in Tag Recommendation (FB, EFM, JMA, MAG), pp. 380–391.
- RecSys-2013-BelemSAG #recommendation #topic
- Topic diversity in tag recommendation (FB, RLTS, JMA, MAG), pp. 141–148.
- CIKM-2012-OliveiraGBBAZG #automation #query #recommendation
- Automatic query expansion based on tag recommendation (VCdO, GdCMG, FB, WCB, JMA, NZ, MAG), pp. 1985–1989.
- PDP-2012-GoncalvesVASNC #network
- Characterizing Dynamic Properties of the SopCast Overlay Network (KCG, ABV, JMA, APCdS, HTMN, SVAC), pp. 319–326.
- TPDL-2012-SumbanaGSAV #automation #classification #detection #wiki
- Automatic Vandalism Detection in Wikipedia with Active Associative Classification (MS, MAG, RSO, JMA, AV), pp. 138–143.
- SIGIR-2011-BelemMPAG #multi #recommendation
- Associative tag recommendation exploiting multiple textual features (FB, EFM, TP, JMA, MAG), pp. 1033–1042.
- SIGIR-2011-RicciGBAGP #named #quality #recommendation #web
- GreenMeter: a tool for assessing the quality and recommending tags for web 2.0 applications (SMRR, DAG, FMB, JMA, MAG, ROP), pp. 1279–1280.
- CIKM-2009-FigueiredoBPAGFMC #quality #web
- Evidence of quality of textual features on the web 2.0 (FF, FB, HP, JMA, MAG, DFdO, ESdM, MC), pp. 909–918.
- ECDL-2009-FerreiraGALV #ambiguity #generative #named
- SyGAR — A Synthetic Data Generator for Evaluating Name Disambiguation Methods (AAF, MAG, JMA, AHFL, AV), pp. 437–441.
- SIGIR-2009-BenevenutoRAAG #detection #network #online #social #video
- Detecting spammers and content promoters in online video social networks (FB, TR, VAFA, JMA, MAG), pp. 620–627.
- SAC-2008-AtallaMAGA #behaviour #peer-to-peer #quality #web
- Analyzing the impact of churn and malicious behavior on the quality of peer-to-peer web search (FA, DM, JMA, MAG, VA), pp. 1137–1144.
- SAC-2007-CostaSAA #network #peer-to-peer
- Fighting pollution dissemination in peer-to-peer networks (CPC, VS, JMA, VA), pp. 1586–1590.
- SAC-2006-BenevenutoCVAAM
- Impact of peer incentives on the dissemination of polluted content (FB, CPC, MAV, VA, JMA, MM), pp. 1875–1879.
- JCDL-2016-NezhadbiglariGA #predict
- Early Prediction of Scholar Popularity (MN, MAG, JMA), pp. 181–190.