BibSLEIGH — Ido

Travelled to:

1 × Australia
1 × Austria
1 × Chile
1 × Georgia
1 × Italy
1 × Spain
1 × Switzerland
1 × United Kingdom
10 × USA
2 × Canada
2 × China

Collaborated with:

I.Ronen M.Jacovi W.Geyer E.Uziel A.Perer D.Carmel T.Daniel S.Kremer-Davidson N.Zwerdling ∅ S.Ur E.Shahar M.Barnea E.Kravi N.Aizenbud-Reshef N.Meshulam S.Ofek-Koifman S.Yogev A.Hashavit Y.Corem A.Raviv C.Dugan T.Steier T.Matthews R.Levin E.Bolshinsky G.Mark D.R.Raban A.Danan J.Freyne N.Har'El S.Porat S.Weber T.Oral A.Barger Y.Dubinsky O.Greenshpan I.Turbahn Y.Mass H.Roitman J.Chen M.J.Muller E.Agichtein Y.Kanza A.Mejer D.Pelleg M.Müller K.Ehrlich V.Soroka S.Farrell A.Jaimes P.Agulló P.Moore P.Nandy C.Nastar H.Schinzel S.Chernov C.Y.Chi Q.Liao Y.Pan S.Zhao T.P.Moran M.X.Zhou D.R.Millen C.Lin N.S.Shami J.Yang L.Panc T.Ratchford J.C.Rasmussen Y.Assogba T.Soule S.Lupushor J.Ferrar

Talks about:

social (21) recommend (11) enterpris (11) media (7) search (6) network (5) peopl (5) stream (4) person (4) base (4)

Person: Ido Guy

DBLP: Guy:Ido

Facilitated 1 volumes:

Contributed to:

2015

2014

2012

2011

2010

2009

2008

Wrote 29 papers:

CSCW-2015-GuyHC #crowdsourcing #enterprise #framework #game studies #platform: Games for Crowds: A Crowdsourcing Game Platform for the Enterprise (IG, AH, YC), pp. 1860–1871.
RecSys-2015-Guy #personalisation #recommendation: The Role of User Location in Personalized Search and Recommendation (IG), p. 236.
SIGIR-2015-GuyLDB #case study #enterprise #recommendation #social: Islands in the Stream: A Study of Item Recommendation within an Enterprise Social Stream (IG, RL, TD, EB), pp. 665–674.
SIGIR-2015-KraviAGKMP #comprehension #web: Searcher in a Strange Land: Understanding Web Search from Familiar and Unfamiliar Locations (EK, EA, IG, YK, AM, DP), pp. 855–858.
CSCW-2014-JacoviGKPA #enterprise #social #social media: The perception of others: inferring reputation from social media in the enterprise (MJ, IG, SKD, SP, NAR), pp. 756–766.
CSCW-2014-MarkGKJ #enterprise #social #social media: Most liked, fewest friends: patterns of enterprise social media use (GM, IG, SKD, MJ), pp. 393–404.
CSCW-2014-ShamiYPDRRASSLGGF #comprehension #enterprise #social #social media: Understanding employee social media chatter with enterprise social pulse (NSS, JY, LP, CD, TR, JCR, YA, TS, TS, SL, WG, IG, JF), pp. 379–392.
RecSys-2014-GuyG #recommendation #social #tutorial: Social recommender system tutorial (IG, WG), pp. 403–404.
SIGIR-2014-RonenGKB #community #recommendation #social #social media: Recommending social media content to community owners (IR, IG, EK, MB), pp. 243–252.
CHI-2012-GuyURWO #enterprise #people #scalability: Best faces forward: a large-scale study of people search in the enterprise (IG, SU, IR, SW, TO), pp. 1775–1784.
CHI-2012-MullerEMPRG #community #enterprise #online #social #social media: Diversity among enterprise online communities: collaborating, teaming, and innovating through social media (MM, KE, TM, AP, IR, IG), pp. 2815–2824.
CHI-2012-RabanDRG #people: Impression formation in corporate people tagging (DRR, AD, IR, IG), pp. 569–578.
CIKM-2012-GuySBRD #enterprise #process: Swimming against the streamz: search and analytics over the enterprise activity stream (IG, TS, MB, IR, TD), pp. 1587–1591.
CSCW-2012-Aizenbud-ReshefBGDK #enterprise #social: Bon voyage: social travel planning in the enterprise (NAR, AB, IG, YD, SKD), pp. 819–828.
CHI-2011-GuyPDGT #crowdsourcing #game studies #graph #social: Guess who?: enriching the social graph through a crowdsourcing game (IG, AP, TD, OG, IT), pp. 1373–1382.
CIKM-2011-CarmelUGMR #generative #word: Folksonomy-based term extraction for word cloud generation (DC, EU, IG, YM, HR), pp. 2437–2440.
CSCW-2011-ChiLPZMMZMLG #collaboration #research #social: Smarter social collaboration at IBM research (CYC, QL, YP, SZ, TM, TPM, MXZ, DRM, CYL, IG), pp. 159–166.
CSCW-2011-GuyURPJ #enterprise #recommendation: Do you want to know?: recommending strangers in the enterprise (IG, SU, IR, AP, MJ), pp. 285–294.
RecSys-2011-GuyRR #personalisation #process: Personalized activity streams: sifting through the “river of news” (IG, IR, AR), pp. 181–188.
CSCW-2010-GuyJPRU #mining #people #similarity #social #social media: Same places, same things, same people?: mining user similarity on social media (IG, MJ, AP, IR, EU), pp. 41–50.
RecSys-2010-GuyJAMNNS #industrial #perspective #recommendation: Will recommenders kill search?: recommender systems — an industry perspective (IG, AJ, PA, PM, PN, CN, HS), pp. 7–12.
SIGIR-2010-GuyZRCU #people #recommendation #social #social media: Social media recommendation based on people and tags (IG, NZ, IR, DC, EU), pp. 194–201.
CHI-2009-ChenGDMG #network #people #recommendation #social: Make new friends, but keep the old: recommending people on social networking sites (JC, WG, CD, MJM, IG), pp. 201–210.
CIKM-2009-CarmelZGOHRUYC #network #personalisation #social: Personalized social search based on the user’s social network (DC, NZ, IG, SOK, NH, IR, EU, SY, SC), pp. 1227–1236.
RecSys-2009-FreyneJGG #recommendation: Increasing engagement through early recommender intervention (JF, MJ, IG, WG), pp. 85–92.
RecSys-2009-GuyZCRUYO #personalisation #recommendation #social: Personalized recommendation of social software items based on social relations (IG, NZ, DC, IR, EU, SY, SOK), pp. 53–60.
SIGIR-2009-RonenSUUYZCGHO #enterprise #network #social: Social networks and discovery in the enterprise (SaND) (IR, ES, SU, EU, SY, NZ, DC, IG, NH, SOK), p. 836.
CHI-2008-GuyJSMSF #network #social: Harvesting with SONAR: the value of aggregating social network information (IG, MJ, ES, NM, VS, SF), pp. 1017–1026.
CSCW-2008-GuyJMRS #email #network #social: Public vs. private: comparing public social network information with email (IG, MJ, NM, IR, ES), pp. 393–402.