Travelled to:
1 × Australia
1 × China
1 × France
6 × USA
Collaborated with:
B.Liu W.Hsu P.S.Yu R.Hankins D.Racz S.Mehrotra Q.Zhong D.Y.Seid S.Chen C.K.Wong S.M.Lee D.Agarwal B.Chen Q.He P.Shivaswamy L.Zhang Z.Hua G.Lebanon H.Tseng J.Yang R.Gupta J.Hartman A.Iyer S.Kolar A.Singh C.T.Butts D.V.Kalashnikov N.Venkatasubramanian K.Altintas R.Hariharan H.Lee A.Meyers J.Wickramasuriya R.Eguchi C.Huyck
Talks about:
associ (4) rule (4) mine (4) discov (3) use (3) framework (2) link (2) feed (2) competitor (1) increment (1)
Person: Yiming Ma
DBLP: Ma:Yiming
Contributed to:
Wrote 13 papers:
- KDD-2015-AgarwalCHHLMSTY #personalisation
- Personalizing LinkedIn Feed (DA, BCC, QH, ZH, GL, YM, PS, HPT, JY, LZ), pp. 1651–1660.
- KDD-2014-AgarwalCGHHIKMSSZ #process #ranking
- Activity ranking in LinkedIn feed (DA, BCC, RG, JH, QH, AI, SK, YM, PS, AS, LZ), pp. 1603–1612.
- CIKM-2009-MaHR #framework #incremental #mobile #named #predict
- iLoc: a framework for incremental location-state acquisition and prediction based on mobile sensors (YM, RH, DR), pp. 1367–1376.
- CIKM-2004-MaZMS #framework #learning #query #similarity #using
- A framework for refining similarity queries using learning techniques (YM, QZ, SM, DYS), pp. 158–159.
- SIGMOD-2004-MehrotraBKVAHLMMWEH #named
- CAMAS: A Citizen Awareness System for Crisis Mitigation (SM, CTB, DVK, NV, KA, RH, HL, YM, AM, JW, RE, CH), pp. 955–956.
- KDD-2001-LiuHM #identification
- Identifying non-actionable association rules (BL, WH, YM), pp. 329–334.
- KDD-2001-LiuHM01a #set
- Discovering the set of fundamental rule changes (BL, WH, YM), pp. 335–340.
- KDD-2001-LiuMY #web
- Discovering unexpected information from your competitors’ web sites (BL, YM, PSY), pp. 144–153.
- KDD-2000-MaLWYL #data mining #mining #student #using
- Targeting the right students using data mining (YM, BL, CKW, PSY, SML), pp. 457–464.
- KDD-1999-LiuHM
- Pruning and Summarizing the Discovered Associations (BL, WH, YM), pp. 125–134.
- KDD-1999-LiuHM99a #mining #multi
- Mining Association Rules with Multiple Minimum Supports (BL, WH, YM), pp. 337–341.
- KDD-1999-LiuHMC #mining #using
- Mining Interesting Knowledge Using DM-II (BL, WH, YM, SC), pp. 430–434.
- KDD-1998-LiuHM #classification #mining
- Integrating Classification and Association Rule Mining (BL, WH, YM), pp. 80–86.