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The 2nd International Workshop on Database Technology and Applications (DBTA2010)! g3 Q* G2 }. ~+ t/ K: `# b* O
' ~7 i& k: D. D$ f0 T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)2 _" n2 G f' r9 @2 d1 Y
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11月27-28，2010，武汉，中国 N; [9 F: @% V5 J' Z7 l/ N
* @2 h8 ]0 L' L& [2 ]8 yhttp://www.icdbta.org/
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论文提交日期: 2010年8月18日
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3 ]. e' q% h2 o3 e( V, T9 J1 C$ C论文录用通知日期: 2010年9月 16 日5 l- _1 r* }; v
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论文修订版本提交日期: 2010年9月22日- a) x8 M+ v) g! b$ b
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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/. G+ r) |' ^; E# U* K
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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）% ?( j9 ^6 I) w: U9 J
- O$ p$ X1 Q& E) A: S! \, HIEEE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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; r" N8 D6 C$ s$ H( N0 z' y: h, O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。5 K* ?8 k9 h% Y! Z; N
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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。
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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
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4 `# k8 E. q5 d优秀论文将被推荐选入EI或SCI国际期刊专刊发表。
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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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6 D/ o* |# Y0 x$ Z+ ~, y/ H& W) q# |1. Database and Related Issue
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Temporal Data) J) ^ m/ T0 ?& I/ Y. Q7 S
# v& U* ^( ?2 Y1 _* YScientific Databases
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Business database software# o- u7 s {& c% K
$ o4 E) u) G' A7 mComputer data processing ) r! q _2 I9 H& ~+ ^- o6 {
' z! o& i# {8 C4 Y: P( _Data processing services
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Data processing supplies $ v+ a( A5 }' A+ A
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Data processing systems* h7 e* J' F$ y2 _. L4 ]
& s( ~/ H5 D1 rMetadata Management; y* ?% v Q, M
, L0 F+ z3 J. C, l! X5 ]. k" kMobile Data and Information. R! [" G n( m6 ~0 w9 S
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Multimedia Databases
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WWW and Databases
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# [: z, o$ T6 R+ O' [# RWorkflow Management and Databases J" p7 c' Z6 J, S2 C/ p5 i6 b
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XML and Databases
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2 P! ~- `8 a& Y! W' GMultimedia Databases2 i8 ?. n) V6 s z6 `. |% { A
) i. T) i$ |2 {! Z$ R( AData modeling and architectures
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Data streaming, data provenance and data quality2 W/ O" u% n8 j8 O9 G' v* H W
* Z/ @9 P8 S$ K0 M5 zData Security, privacy, and data integrity
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3 T0 {. R+ E4 m% u/ kWeb Data and the Internet& \- `3 _% }% N
7 K( v" r( {! L6 N; O' {9 tXML and databases, web services- n, { u V9 C
0 D/ H+ x0 N( ~- d; A9 ySemi-structured data, metadata' K' d0 y1 d/ t p7 V+ h- |% m
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e-commence
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- V% |# b. Q4 k& o# z! V7 N2. Data warehouse and Data mining. \% w; q. J& s
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Grid/Parallel/distributed data warehousing
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Web/multimedia data warehouses
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Data warehousing and the semantic web% E+ ]8 h& Y F. Z# z
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Data warehousing with unstructured data& D7 Y/ V0 m3 b2 |5 D$ L& Y: U ?
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Integration of Data Warehousing
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$ T9 f3 {1 L, l3 ?9 ?/ l* ^Data and knowledge representation1 H9 A" {3 h" {) @) ~
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Languages and interfaces for data mining" [- O- C) P+ x7 q
: l7 y7 D2 H+ ZData integration and interoperability
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) l% E4 S5 M! N/ d# E$ P7 W: h; HData extraction, cleansing, transforming and loading a& ?8 ]& G' ]* D2 D* H* C
5 _$ l7 [. |' o+ oData mining and information extraction
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7 O) t7 A! f* J6 I' QKDD Process and Human Interaction3 | e: _( x7 v, I8 T: i! g2 D
5 D# u# w! a2 f' o- v9 qOLAP and Data Mining( w2 M$ ]+ \& l9 Z. @. M4 V9 b `8 G
' z( F3 w9 B" ^! G; L+ YParallel and Distributed Data Mining
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' L$ ]& ^: U {0 lPhysical database design and performance evaluation* b" N: m! ~/ g% k
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Query processing and optimization
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" G! J) r# I* b& x' J& C4 z- R2 `Reliability and Robustness Issues
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; D+ L" P/ _# A! ]" p$ oSemantic web and ontology; G& k, K0 }* j) c* i
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Software Warehouse and Software Mining) R' {$ ~' i4 G4 j4 \4 x
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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) / W' M9 x3 L( l! o
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Developing a unifying theory of data mining 0 U& H% z5 |8 S
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Mining sequences and sequential data8 ~ A* d4 G$ f' v7 z' w8 c, ]: m
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Data pre-processing, data reduction, feature selection, and feature transformation
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8 ^ ^( X( {/ l6 {9 ~4 E3 oQuality assessment, interestingness analysis, and post-processing % X4 L, m3 Z( f
) U3 Q( y: |- a" q. C; fMining unstructured, semi-structured, and structured data
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6 a2 |- c h4 x8 t; K9 jMining temporal, spatial, spatio-temporal data1 U' J) _& K) H# B
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Mining data streams and sensor data
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Mining multimedia data
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Mining social network data. ~" {, N7 _1 ?# ?
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Human-machine interaction and visual data mining
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Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)
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Knowledge Acquisition & Management+ j/ f+ c1 V3 v8 x7 d
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Knowledge Modeling
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: P$ a/ X! K$ E0 Q* I2 {Knowledge Processing
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Integrated KDD applications and systems
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- C# m$ x+ d2 Z0 I, V4 |Business Process Intelligence
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4 x- V$ x# H. O' \6 W% [( e HCluster Analysis and Knowledge Base system
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' F, n: Z: s% I, p6 m4 HInformation systems technology
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0 e7 t1 |1 o4 C* x6 K, qOther related technology about data mining, u3 d7 K9 j- p+ I
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+ Q( D1 k6 m2 c& S! C; e; }0 H5 I3. Computer Science and Related Technology 1 f3 U3 E2 v1 V
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Image and signal processing
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Artificial Intelligence
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- y/ o# y7 H$ Y, d/ uSoftware engineering
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: {* N* T. a' e- NSystems Engineering
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Computer Graphics
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Computer Application
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: f7 u/ x& K: B+ l$ ?9 {8 a5 NControl Technology
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: d9 D9 @2 |) }; cNetwork Technology 6 I3 b1 ^/ p: D
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Network security / p0 I1 F% D- [$ R2 l! r
]. i; ^( U% E( {: N, M. ANumerical and symbolic computation ?) @/ c; U( k6 P+ ?* B6 [
$ e- q( f8 \- X& f8 x* G) F& rComputer Modeling and Simulation
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2 o" w5 a2 ~9 f: D: GCommunication Technology
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Algorithms and data structures
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Computer Education' C8 f, ~ p6 U5 T5 ^! g4 H: N
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Other Advanced Technology
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0 }8 ]: t, C3 }) N' R- MDBTA2010会议联系秘书处 L2 \" V% U1 @/ X4 c
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邮件: dbta2010@vip.sina.com, info@icdbta.org
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