BibSLEIGH — Dong

Travelled to:

1 × Austria
1 × Canada
1 × Germany
1 × Greece
1 × Korea
1 × Norway
2 × China
4 × USA

Collaborated with:

J.Han V.Ganti K.Chakrabarti H.Cheng S.Chaudhuri X.Li X.Yan T.Wu Q.Mei B.Bahmani Y.He K.C.Chang C.Chen T.Cheng P.Zhao X.Shen B.W.Wah C.Zhai S.Agrawal A.C.König J.Lee R.Redder

Talks about:

rank (6) cube (6) pattern (5) queri (5) entiti (4) top (4) framework (2) dimension (2) frequent (2) approxim (2)

Person: Dong Xin

DBLP: Xin:Dong

Contributed to:

2012

2011

2010

2009

2008

2007

2006

2005

2003

Wrote 20 papers:

KDD-2012-ChakrabartiCCX #framework #robust: A framework for robust discovery of entity synonyms (KC, SC, TC, DX), pp. 1384–1392.
SIGMOD-2011-BahmaniCX #performance #personalisation #pipes and filters #rank: Fast personalized PageRank on MapReduce (BB, KC, DX), pp. 973–984.
SIGMOD-2011-ZhaoLXH #graph #multi #network: Graph cube: on warehousing and OLAP multidimensional networks (PZ, XL, DX, JH), pp. 853–864.
SIGMOD-2010-AgrawalCCGKX #generative #query #web: Query portals: dynamically generating portals for entity-oriented web queries (SA, KC, SC, VG, ACK, DX), pp. 1171–1174.
VLDB-2010-XinHG #database #framework #keyword: Keyword++: A Framework to Improve Keyword Search Over Entity Databases (DX, YH, VG), pp. 711–722.
VLDB-2009-ChaudhuriGX #approximate #documentation #mining: Mining Document Collections to Facilitate Accurate Approximate Entity Matching (SC, VG, DX), pp. 395–406.
VLDB-2009-WuXMH #analysis #multi: Promotion Analysis in Multi-Dimensional Space (TW, DX, QM, JH), pp. 109–120.
SIGMOD-2008-ChakrabartiCGX #approximate #performance: An efficient filter for approximate membership checking (KC, SC, VG, DX), pp. 805–818.
SIGMOD-2008-WuXH #named #query #ranking: ARCube: supporting ranking aggregate queries in partially materialized data cubes (TW, DX, JH), pp. 79–92.
SIGMOD-2007-XinHC #ad hoc #ranking: Progressive and selective merge: computing top-k with ad-hoc ranking functions (DX, JH, KCCC), pp. 103–114.
VLDB-2007-WuLXHLR #database #named: DataScope: Viewing Database Contents in Google Maps’ Way (TW, XL, DX, JH, JL, RR), pp. 1314–1317.
KDD-2006-MeiXCHZ #analysis #generative #semantics: Generating semantic annotations for frequent patterns with context analysis (QM, DX, HC, JH, CZ), pp. 337–346.
KDD-2006-XinCYH: Extracting redundancy-aware top-k patterns (DX, HC, XY, JH), pp. 444–453.
KDD-2006-XinSMH #feedback #interactive: Discovering interesting patterns through user’s interactive feedback (DX, XS, QM, JH), pp. 773–778.
SIGMOD-2006-ChakrabartiGHX #ranking: Ranking objects based on relationships (KC, VG, JH, DX), pp. 371–382.
VLDB-2006-XinCH #query #robust #towards: Towards Robust Indexing for Ranked Queries (DX, CC, JH), pp. 235–246.
VLDB-2006-XinHCL #approach #multi #query #ranking: Answering Top-k Queries with Multi-Dimensional Selections: The Ranking Cube Approach (DX, JH, HC, XL), pp. 463–475.
KDD-2005-YanCHX #approach: Summarizing itemset patterns: a profile-based approach (XY, HC, JH, DX), pp. 314–323.
VLDB-2005-XinHYC #mining #set: Mining Compressed Frequent-Pattern Sets (DX, JH, XY, HC), pp. 709–720.
VLDB-2003-XinHLW #bottom-up #integration #named #top-down: Star-Cubing: Computing Iceberg Cubes by Top-Down and Bottom-Up Integration (DX, JH, XL, BWW), pp. 476–487.