Travelled to:1 × Australia
1 × Austria
1 × Chile
1 × China
1 × France
1 × Portugal
1 × Spain
1 × Switzerland
1 × United Kingdom
3 × USA
Collaborated with:L.Rokach M.Taieb-Maimon G.Shani N.Ofek L.N.Dery M.Kalech G.Katz N.D.Betzalel V.Makarenkov A.Ostrikov A.Moskowitz Y.Nemeth O.Moreno V.Maidel P.Shoval A.Shtok O.Kurland E.Chapnik G.Siboni D.Ben-Shimon A.Tsikinovsky M.Friedmann J.Hörle A.Dayan G.Katz N.Biasdi A.Aydin R.Schwaiger R.Fishel
Talks about:recommend (5) wikipedia (3) filter (3) use (3) collabor (2) queri (2) group (2) evalu (2) boost (2) base (2)
Person: Bracha Shapira
DBLP: Shapira:Bracha
Contributed to:
2015
2015201420142013
2013
201220112010200820062004Wrote 14 papers:
- RecSys-2015-Ben-ShimonTFSRH #challenge #dataset
- RecSys Challenge 2015 and the YOOCHOOSE Dataset (DBS, AT, MF, BS, LR, JH), pp. 357–358.
- RecSys-2015-BetzalelSR #exclamation #quote #recommendation
- “Please, Not Now!”: A Model for Timing Recommendations (NDB, BS, LR), pp. 297–300.
- SIGIR-2015-ShapiraOM #information retrieval #wiki
- Exploiting Wikipedia for Information Retrieval Tasks (BS, NO, VM), pp. 1137–1140.
- RecSys-2014-DeryKRS #elicitation #recommendation
- Preference elicitation for narrowing the recommended list for groups (LND, MK, LR, BS), pp. 333–336.
- SIGIR-2014-KatzSKSR #performance #predict #query
- Wikipedia-based query performance prediction (GK, AS, OK, BS, LR), pp. 1235–1238.
- RecSys-2013-OstrikovRS #collaboration #metadata #using
- Using geospatial metadata to boost collaborative filtering (AO, LR, BS), pp. 423–426.
- SAC-2013-RokachSSCS #recommendation
- Recommending insurance riders (LR, GS, BS, EC, GS), pp. 253–260.
- CIKM-2012-MorenoSRS #learning #multi #named
- TALMUD: transfer learning for multiple domains (OM, BS, LR, GS), pp. 425–434.
- RecSys-2011-DayanKBRSASF #benchmark #framework #metric #recommendation
- Recommenders benchmark framework (AD, GK, NB, LR, BS, AA, RS, RF), pp. 353–354.
- RecSys-2011-KatzOSRS #collaboration #using #wiki
- Using Wikipedia to boost collaborative filtering techniques (GK, NO, BS, LR, GS), pp. 285–288.
- RecSys-2010-DeryKRS #nondeterminism #recommendation
- Iterative voting under uncertainty for group recommender systems (LND, MK, LR, BS), pp. 265–268.
- RecSys-2008-MaidelSST #evaluation #personalisation
- Evaluation of an ontology-content based filtering method for a personalized newspaper (VM, PS, BS, MTM), pp. 91–98.
- SAC-2006-ShapiraTM
- Study of the usefulness of known and new implicit indicators and their optimal combination for accurate inference of users interests (BS, MTM, AM), pp. 1118–1119.
- SIGIR-2004-NemethST #automation #evaluation #interactive #query
- Evaluation of the real and perceived value of automatic and interactive query expansion (YN, BS, MTM), pp. 526–527.