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[讨论] 第二届IEEE数据库技术与应用国际会议将于11月在武汉召开

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The 2nd International Workshop on Database Technology and Applications (DBTA2010)
+ h9 l/ H2 H  z0 L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)6 e' S+ _2 o8 h2 B
11月27-28,2010,武汉,中国
  x+ }, d0 G" x6 ]http://www.icdbta.org/dbta2010/
4 N- ~4 X3 `5 w0 x/ _% [  e! }* ]" }
论文提交日期: 2010年8月18日/ ^. b4 r: }& t; o' D3 `
论文录用通知日期: 2010年9月 16 日
8 H5 ~9 O$ [% i论文修订版本提交日期: 2010年9月22日
9 Y3 E  ^3 h1 |9 s% h) k论文注册日期: 2010年9月28日
8 D! H- O/ L! ?论文提交系统: http://www.icdbta.org/dbta2010/submission/( n+ g5 P7 S& M7 R8 u
会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc(只接受英文稿件)
9 o9 s5 ?: Z  b+ b  CIEEE会议论文版权表:http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc(录用注册后提交)                                
; }& @3 m* h% j6 ^! L- X3 z9 ]& B/ c0 [, j8 |/ I4 D
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。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。DBTA2010将由美国IEEE出版社出版,收录的论文将全部被EI Compendex和ISTP检索。会议优秀论文将被推荐选入EI或SCI收录的国际期刊专刊发表。+ b: j0 I" V+ [9 K3 Y- R8 e+ F
9 ]6 L" H5 w& r2 A# G' n3 I8 n9 j
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三个领域构成,但并不局限于:
" q' ^- O$ o1 X' ]$ {$ J1. Database and Related Issue / 数据库与相关领域; d+ k" `+ Z8 ~/ K0 Z
Temporal Data1 J: |/ Z7 D4 K" s) h8 A
Scientific Databases6 L, z6 E( B- r
Business database software0 w5 u' H: W/ G0 M( ]0 f
Computer data processing
5 k, A2 @# o  C. {. e! P+ ^8 R! CData processing services
. N' z2 X) U- d1 N: {Data processing supplies $ o4 Z3 d/ a5 Z; g" s
Data processing systems6 o: v% X5 M# r. S: R
Metadata Management
4 S2 R7 B; C$ @3 V5 BMobile Data and Information6 F. |5 U& Q. f8 ~9 d; ^; _
Multimedia Databases4 `6 l- r9 ^, J' T' X4 X
WWW and Databases" Q) h( h. M4 e8 K
Workflow Management and Databases
! M+ y8 M1 t8 P7 X# u6 _XML and Databases
& M8 E3 o( P. KMultimedia Databases
2 K$ G# @7 O9 K3 R* [Data modelling and architectures
* i$ K  l% J* O/ x/ J, BData streaming, data provenance and data quality
( o5 f8 w9 h0 n* VData Security, privacy, and data integrity
, e3 {2 V0 h' ]- m: wWeb Data and the Internet
+ ]1 O7 F7 j, }) l) }" K4 f* MXML and databases, web services
/ }0 d4 Q4 p7 WSemi-structured data, metadata' U* Q5 ]; h) s
e-commence
3 W# ?( T3 g( y+ W& A
* M2 C9 C! y0 {3 i2. Data warehouse and Data mining /数据仓库和数据挖掘. J: m! M4 L% y* {- |* a7 R. {% V' V
Grid/Parallel/distributed data warehousing- a8 H0 C5 S/ f% u9 e6 W& [
Web/multimedia data warehouses
% V5 O! z5 L0 L+ uData warehousing and the semantic web4 E# J: ]1 i7 J! V8 H# \4 |
Data warehousing with unstructured data- @8 |# b+ k- q: r- [
Integration of Data Warehousing8 O$ N; e& C1 F6 |$ G
Data and knowledge representation7 I* K# Q$ m* r, i: q6 C& t9 r% V
Languages and interfaces for data mining
, H0 U2 B  g1 Q; nData integration and interoperability
5 z# V* o3 A! HData extraction, cleansing, transforming and loading' b2 J* t* K! \- S5 m1 z8 X
Data mining and information extraction
  l, |) F- r' K7 FKDD Process and Human Interaction
4 T: [- ^$ N; p5 COLAP and Data Mining: @7 B, M6 d/ c( @/ ]! z. Z7 K5 L
Parallel and Distributed Data Mining
$ E( O& a$ }- n+ m: OPhysical database design and performance evaluation
% y9 M9 A( F7 S- |% LQuery processing and optimization) c+ v( S' N) ^( Q5 v, v! ~
Reliability and Robustness Issues% M8 _. D; H% y( k; x+ G
Semantic web and ontologies
- I) u& H: C& [8 U$ ~) DSoftware Warehouse and Software Mining: s1 V* W! O0 X9 `$ [
Social and mathematical statistics: ?+ Y) e! [/ I: X" D, v
Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) 4 {8 h$ x$ }- ]& \" m7 A
Developing a unifying theory of data mining % }$ u2 x8 h6 w; |
Mining sequences and sequential data
/ w" r" i3 [  v3 [( R: G0 cData pre-processing, data reduction, feature selection, and feature transformation - X3 D" y" L& L3 W) t! y. [+ B, u
Quality assessment, interestingness analysis, and post-processing
/ s7 o' E+ }& G' G; {Mining unstructured, semi-structured, and structured data
6 A8 p0 x. z) F  [3 p/ ?0 qMining temporal, spatial, spatio-temporal data
' f$ [3 g/ W6 \: L1 {Mining data streams and sensor data
. E  U7 F$ C  h4 [1 ^Mining multimedia data  q9 ^  @9 C# ?/ b5 T
Mining social network data
) |0 \+ s$ M+ cHuman-machine interaction and visual data mining
/ g) A; K8 g( T' f% ~" DData mining applications(bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)
8 s! d3 |9 g* U$ c3 v0 i5 s2 ]6 OKnowledge Acquisition & Management8 a' `1 _# E8 _$ c; |* n
Knowledge Modelling
; ~5 V6 e4 o' g- b8 `8 v0 S. WKnowledge Processing2 W* L4 B7 L- J# n# d* `5 l+ G
Integrated KDD applications and systems : P0 g3 O5 C1 B5 U5 o( b) V( p- r* A0 t
Business Process Intelligence$ B% r2 m& ^7 D! U" ?3 q; }
Cluster Analysis and Knowledge Base system
* x; N0 b! X% pInformation systems technology
: z( n9 n! B, ?2 sOther related technology about data mining- b0 w( I$ Q+ v; D$ {9 V4 i
3. Computer Science and Related Technology /计算机科学和相关技术- o# X: `) Y; g8 m1 m) Q2 v: p
Image and singnal processing
( U8 I% X+ ~) b( B* s$ c! y3 d( ~Artificial Intelligence 0 y: d! R/ b3 l
Software engineering 9 y0 _6 L3 Q# R4 l
Systems Engineering ' d; i, H' O; S0 M$ H9 h4 X+ d4 F
Computer Graphics
% u3 _$ P1 Q8 Z4 r- A% w! |Computer Application , g6 @  o+ m, }' d9 P
Control Technology
' `4 r  l* o* {9 ~Network Technology
3 q6 y% S# u1 T! yNetwork security
+ V1 R, i. y: UNumerical and symbolic computation
* [, {' v1 ?  M$ c+ X+ q3 j. fComputer Modeling and Simulation
- Y. |2 O4 O- d8 l3 F2 N3 Y9 ACommunication Technology ( V# Y4 k1 D3 q# {3 F* A" D
Algorithms and data structures
4 P& u; Q; D% O' i. v4 P( p0 HComputer Education
/ ^0 `4 k2 J4 A8 e3 u7 GOther Advanced Technology  y# j' Z$ `1 t" j" a; [% s" r
======================================- @" `- X! F$ p" V- m
DBTA2010会议联系秘书处
3 m" W0 x8 z( ~) n6 ^( L0 b$ \  i' c3 q- h; _
邮件: info@icdbta.org, dbta2010@vip.sina.com
& q" v" {, c3 a0 o+ s电话: +86-15102769170- W+ H$ a6 \, D: N
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