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The 2nd International Workshop on Database Technology and Applications (DBTA2010)* v# V9 A/ F) a' Y& Z; w
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). P3 W" m/ Z( }0 f/ a! G
11月27-28,2010,武汉,中国
' u. }, `7 h7 N0 |+ ahttp://www.icdbta.org/
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论文提交日期: 2010年8月18日: k/ e8 u# _8 ^8 P: `$ r% T
论文录用通知日期: 2010年9月 16 日' V' q( {. X& r6 V3 l: z
论文修订版本提交日期: 2010年9月22日
" L+ X" F, R5 M# k( m论文注册日期: 2010年9月28日
, V: E8 h9 ?& m3 }5 U# f论文提交系统: http://www.icdbta.org/dbta2010/submission/
- P [& [% k. N0 Q会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc(只接受英文稿件)! u: A3 v: s p5 X& G+ a. h: E
IEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc (录用注册后提交)0 V( q' J. C0 h/ c4 [. T0 D
~2 S5 }7 ]3 F: N- D1 X. w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ISTP和EI Compendex检索。会议优秀论文将被推荐选入EI或SCI国际期刊专刊发表。( G# o8 B, w% p5 O, r2 d- G0 p7 `
# N: u1 |9 t0 r7 R# v5 }: i+ K, K1 G$ q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 " J/ \) l3 V! C; [% U8 S9 B
Temporal Data) n2 Y7 [' f1 x) \
Scientific Databases) _' D# W( `( I4 y
Business database software
& p+ D* m* x8 C0 S0 R1 SComputer data processing
0 s# Z# s/ u6 s; e# X2 T( qData processing services 4 X. Q8 Q' W# s$ n" K
Data processing supplies
/ ~$ H8 r5 K/ CData processing systems0 k" }- P e# N# Y* W* C
Metadata Management
' e Z4 R9 J" I3 K5 p! O$ iMobile Data and Information; Q# y0 A; R! b9 q3 ~
** Databases
, j1 v8 @$ s8 d1 z, \6 rWWW and Databases3 q3 a, u; R9 ?$ l
Workflow Management and Databases8 O# O: v3 [9 H" k
XML and Databases4 e0 Q% n) f% Q% n. [; h* C
** Databases7 f) k! D7 |$ N3 u* _
Data modeling and architectures
1 S l% W: w! e! X; _9 SData streaming, data provenance and data quality7 s/ `5 H# J# u( I/ Q" Q
Data Security, privacy, and data integrity $ m7 ~6 s% w" L {3 e: E
Web Data and the Internet
2 J5 l0 t( ?3 v' l/ y( i0 L H3 pXML and databases, web services; R3 n8 Y+ p( T4 \) _2 f( w1 R
Semi-structured data, metadata3 b; ?2 E0 _( U3 ?; y: X
e-commence
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! B6 g8 s. \: C& a6 N# f6 M) P% b2. Data warehouse and Data mining
2 |* \3 q; e$ T6 u) WGrid/Parallel/distributed data warehousing: @! [& K% Q0 r/ Q
Web/** data warehouses, |% I% m2 c+ J9 O) [4 U
Data warehousing and the semantic web! B+ e5 J& Z* I. |) g
Data warehousing with unstructured data
. T Q6 i/ H6 TIntegration of Data Warehousing: _% y# [( s3 S B) l
Data and knowledge representation& r( Q8 r1 G& p& O4 u" a3 D
Languages and inte**ces for data mining7 W& S+ c8 J0 k" Z' W9 q8 W
Data integration and interoperability
/ L3 u. T: V6 o5 ^- F* }5 I5 n V! ]Data extraction, cleansing, transforming and loading* @8 ~3 P2 P+ J8 j
Data mining and information extraction7 e- s* @; P( A
KDD Process and Human Interaction
8 P+ r* d) z" u1 l2 Z" r/ tOLAP and Data Mining2 `7 ~- I; Q; H* s8 O v9 j
Parallel and Distributed Data Mining9 G+ q% i6 a" }- I/ [8 F
Physical database design and performance evaluation2 C! l9 w- L/ X* e: C7 V
Query processing and optimization
5 Q' E1 A5 I! fReliability and Robustness Issues' \4 B( U, A3 m
Semantic web and ontology
) p \6 r) f2 T/ y ~, X) d: `Software Warehouse and Software Mining% Z: s& t d; O- i5 k
Social and mathematical statistics7 i5 N: N/ U4 K* m5 I$ w1 L
Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) ! | b' C: f2 Y% n1 B0 [
Developing a unifying theory of data mining # I& Z7 D# ~3 Y7 h: k' F5 j
Mining sequences and sequential data. D7 ^' V( j" F0 `. n
Data pre-processing, data reduction, feature selection, and feature transformation " s# Q; S! ~- {9 @+ e) x+ d
Quality assessment, interestingness analysis, and post-processing 5 Q1 u% T% Q% ^3 Z
Mining unstructured, semi-structured, and structured data) p f8 ~! D8 O" k! O5 H( i
Mining temporal, spatial, spatio-temporal data0 d* n: e; n! m: G ]
Mining data streams and sensor data/ U- R4 C+ |$ ~
Mining ** data
& F0 k( w5 d8 i0 @+ B" O& m+ `& rMining social network data4 F2 H( W' X2 T2 w0 A5 r
Human-machine interaction and visual data mining
3 V' @" I; E. N7 j% L: O7 E4 ~Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)( D+ V$ h' N- n" K
Knowledge Acquisition & Management9 _# I; j# f0 g# s# R
Knowledge Modeling
/ u, ^8 [' C6 ~7 \7 EKnowledge Processing& b. U* T# _+ @ E- j% o, j3 m
Integrated KDD applications and systems
" E, H1 `9 X9 e* d" ~' lBusiness Process Intelligence
+ f0 S. S, P. T/ e8 z/ I2 a* e9 K! ?Cluster Analysis and Knowledge Base system
; s* g' C; V' ?( s( zInformation systems technology% m# H$ I1 g6 n3 ]: k, W
Other related technology about data mining
0 m4 ~: h1 s' W4 |" c( ^7 W
$ s$ H7 S0 h; g$ Q3. Computer Science and Related Technology
/ ^7 u6 W( _! A' @Image and signal processing $ I. P1 F0 A K+ W1 l
Artificial Intelligence ! A x1 }9 K5 W7 z. M
Software engineering 7 h% d9 u: Q# k
Systems Engineering
! A) x2 _% s2 j9 h, G) T% u* gComputer Graphics 1 }0 g0 A+ w- }- ]( }4 W) D# m) H
Computer Application 7 I& X/ z+ k- Y# u& ?4 G& t ]
Control Technology ) O+ s6 m% a7 ^0 \0 w0 l
Network Technology
( F! H6 S3 x% F3 s8 ~& L$ n6 M: kNetwork security ) s' Z( a! g3 ?' L3 J! K% _) r
Numerical and symbolic computation
5 Z7 L, ]" d7 p# K* c6 |- u8 L8 `5 GComputer Modeling and Simulation
) B! }, W$ S3 V- f/ C* z& yCommunication Technology 9 b6 s9 Q0 s! Q/ V7 d, K
Algorithms and data structures
3 J. ^8 W; }4 V' zComputer Education" K1 g) s9 [2 f4 X! H3 n
Other Advanced Technology
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5 i% o* ~; n2 W6 A% R' O9 R3 ]======================================, ~4 _ f* X, m& n( A
DBTA2010会议联系秘书处
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邮件: dbta2010@vip.sina.com, info@icdbta.org
$ [5 T- c- i( s" m W0 Z3 H电话: +86-15102769170
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