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The 2nd International Workshop on Database Technology and Applications (DBTA2010)2 l; y0 Z8 g4 F1 q7 a- q6 n
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第二届IEEE数据库技术与应用国际会议-DBTA2010(DBTA2009已全部EI Compendex检索)3 N( s! U; u# Y# d7 F
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11月27-28,2010,武汉,中国 2 c) l3 T# I, b( x" \. q* A
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http://www.icdbta.org/
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4 F; D( N/ `9 h论文提交日期: 2010年8月18日% u4 @1 |% M& X( A3 ^
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论文录用通知日期: 2010年9月 16 日+ U* j2 I4 Z: @5 E; R
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论文修订版本提交日期: 2010年9月22日
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; z/ @! h! h, O) a* t' b. A; x, v论文注册日期: 2010年9月28日
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论文提交系统: http://www.icdbta.org/dbta2010/submission/
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会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc(只接受英文稿件)
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9 T: s9 Q% a5 r0 k) p9 xIEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc (录用注册后提交)
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7 c7 m V6 k: O( y# R第二届IEEE数据库技术与应用国际会议(DBTA2010)将于2010年11月27-28日在中国-武汉召开。
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第一届IEEE数据库技术与应用国际会议(DBTA2009)全部收录的论文已经被EI Compendex检索。" b$ [5 v$ K' L; W0 ?% D% v! X
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DBTA2010将由美国IEEE出版社出版,收录的论文将全部被ISTP和EI Compendex检索。会议3 F5 a: \. ^, O4 W% k5 @; m- x( [. X
) \+ s0 _% T2 }( v1 r6 Y优秀论文将被推荐选入EI或SCI国际期刊专刊发表。7 \8 v% { m# U ~" _; @
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6 D# {+ n; z9 c( l# o欢迎研究员、工程师、教师和学生踊跃投稿,会议论文主题由以下领域构成,但并不局限于:
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1. Database and Related Issue
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Temporal Data4 N# ^+ e9 k; `' {5 t* i
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Scientific Databases
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Business database software1 w$ _" S' W! h9 W# H1 l
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Computer data processing 6 f5 w2 c$ s- D; u
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Data processing services $ p( d; E7 }/ x. z' x# a( ^) D3 J# u
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Data processing supplies
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Data processing systems" Z/ Y" K5 ?7 b3 r
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Metadata Management
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Mobile Data and Information
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Multimedia Databases B/ X: E2 p: h. T, R. H0 q+ `
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WWW and Databases
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2 t2 t* T% T B9 y# u7 D/ pWorkflow Management and Databases' @0 t& H9 ?3 `
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XML and Databases0 C7 \) b0 [0 u3 z9 O9 t7 ~! B
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Multimedia Databases
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) Y* p: d( }' u1 ? D: _" [Data modeling and architectures
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Data streaming, data provenance and data quality8 |3 K3 b: {1 a! x8 ^+ T
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Data Security, privacy, and data integrity
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Web Data and the Internet
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* V# A2 P8 R1 M, `" _+ y& dXML and databases, web services, L) I. q# `7 `" K
. t2 f4 y' Y+ ?8 v0 CSemi-structured data, metadata4 x" N! C; H y1 B" U
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e-commence9 t" X- ^7 ]4 w1 G; ~# p7 y9 Q* A
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2. Data warehouse and Data mining0 s% v3 k: C. {& k7 ~. b) y
' [* u7 n' Y6 _6 R) f- lGrid/Parallel/distributed data warehousing
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0 j$ O5 t" V5 a" K" f' JWeb/multimedia data warehouses
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3 }( ^/ U: G6 dData warehousing and the semantic web9 z5 y& d* F# J! r( c8 k
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Data warehousing with unstructured data5 x* E+ W) [$ B$ H, m1 q" j a
0 @1 U0 H# [+ a# fIntegration of Data Warehousing
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Data and knowledge representation" ]3 }! m) k# K* Y5 ]3 q
8 P5 c# K( u: A dLanguages and interfaces for data mining
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Data integration and interoperability3 ~$ r5 M# {- t& _
( x+ ?8 K! G# y) X: cData extraction, cleansing, transforming and loading# x/ P! \' b) d
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Data mining and information extraction) z* u( \" T3 Q, _* B
, B3 e2 V' A$ W1 _3 o! p, \$ m0 rKDD Process and Human Interaction2 x3 p- g* l* d$ D5 m9 p7 l
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OLAP and Data Mining. \" b9 B) ]. \7 N: r: J/ A
' d3 f9 Q$ A# v7 w# @& eParallel and Distributed Data Mining' W, x2 X' z* g
& _7 V( F' I; y# r+ ]) R0 V5 X# ?Physical database design and performance evaluation
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Query processing and optimization
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Reliability and Robustness Issues( F; R; F3 f& m$ |5 v. {
7 _. p8 t. Y# V* T! e( lSemantic web and ontology1 R3 Z: C2 U# e2 }
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Software Warehouse and Software Mining8 F4 J! F& D+ f$ ^3 s. }6 @* f; B
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Social and mathematical statistics
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Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) ' u% m3 b5 E" t" ^
, @- Q/ G7 m7 B' h rDeveloping a unifying theory of data mining
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. d: s6 I* H1 N4 c' Y# I' n: xMining sequences and sequential data
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Data pre-processing, data reduction, feature selection, and feature transformation
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Quality assessment, interestingness analysis, and post-processing - y+ ^# G, t1 }. c( F! ]1 ~* T. ^
9 s* O3 E- c$ A& J. TMining unstructured, semi-structured, and structured data5 v- O- y1 W; A; Z) W- r' ^9 C m
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Mining temporal, spatial, spatio-temporal data4 D) H0 L/ b& [4 I$ j
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Mining data streams and sensor data
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4 G/ x# M- t: W, a$ TMining multimedia data5 T+ r/ J4 p, b. l+ f Q
$ @ [: [5 i) |( G& ]Mining social network data
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' V% A+ E6 R9 n* _( Q8 s% X1 Z; xHuman-machine interaction and visual data mining ; p. w" s# k5 m a1 n/ x* O
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Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)& \: y8 Q0 v- @* B7 w* l0 n
- S: y6 k8 m% q }Knowledge Acquisition & Management
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% w3 M, B' {% a& RKnowledge Modeling0 h/ O* o% @: |3 t7 l
0 b9 s1 D' L$ {! b; V6 g" D( v! qKnowledge Processing. d( A! y" b( h
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Integrated KDD applications and systems & r+ t5 s9 L7 m9 W
/ ?- j8 w0 |% ~2 aBusiness Process Intelligence
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: U, h3 \1 e" q7 @/ z) QCluster Analysis and Knowledge Base system
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Information systems technology
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5 M# f, e0 ^! Q2 C% j2 h+ J% yOther related technology about data mining
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3. Computer Science and Related Technology
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& Y5 W: ]. ?0 I, T" nImage and signal processing * _$ e9 W9 m [& Y
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Artificial Intelligence
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8 r0 C) I$ }1 vSoftware engineering
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Systems Engineering 0 d+ T2 V3 E4 ^( n8 A G$ E2 A* P
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Computer Graphics
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Computer Application 5 X- S; Z3 F8 `/ Q6 u
7 e2 }3 o9 W( }Control Technology 5 a- B; W) t% I; n0 r% S
/ y' o, A% G$ o7 l* wNetwork Technology
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) u5 C G( w% o$ ANetwork security
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Numerical and symbolic computation
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0 `; ~" J9 f: O5 \1 FComputer Modeling and Simulation/ I) \9 @ Y& J. g- ?. Y
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Communication Technology 0 X+ [0 N) l2 u& C0 K- Q+ l
1 t }+ z* w* a" C: a4 y# M, cAlgorithms and data structures: F: B" Q4 f! c( g3 y2 n% d/ D
$ y2 }" Q) x! ]+ y2 m' m7 q- a; ?Computer Education, V& \1 Y* ?& O: L6 r% Y7 G
8 G2 L- ?% W( s, _9 i- D* KOther Advanced Technology7 K4 Y- Y8 Y) T0 k7 N: b' ]3 V
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4 E5 e4 ~5 E/ I L1 m* ]* CDBTA2010会议联系秘书处
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3 `# G1 c% u; J6 `邮件: dbta2010@vip.sina.com, info@icdbta.org
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