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The 2nd International Workshop on Database Technology and Applications (DBTA2010)
& o- O" l2 a) y% p% \/ b2 X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), m6 y. o4 Y+ ^ f% m9 |: g% V
11月27-28,2010,武汉,中国
7 x6 ~6 K3 P% z% U) y" T; {; Whttp://www.icdbta.org/
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; y+ ]/ \. ^9 W2 r5 w7 i论文提交日期: 2010年8月18日
( n" a/ |% W9 ]5 z0 ]1 |/ s5 s论文录用通知日期: 2010年9月 16 日5 J4 M" P5 P6 B9 {4 f0 h
论文修订版本提交日期: 2010年9月22日
+ d4 [2 z5 p4 t+ N8 }论文注册日期: 2010年9月28日
, K6 V( s, X9 Z/ ~, L& I8 [论文提交系统: http://www.icdbta.org/dbta2010/submission/
/ d4 ~4 _4 w$ D. L' H# \会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc(只接受英文稿件)- H$ r% F _4 }7 w0 p, H
IEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc (录用注册后提交)
! x- R5 o, j: \# X! n! u. r8 ?/ P4 V5 A' S# Q& D! n3 b
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。
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" v' h" w& p: \! m* r8 p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 3 M# ]5 ?6 A, t' M
Temporal Data- s9 U5 Q4 z0 R. n( S/ Q9 B3 B1 o6 U
Scientific Databases6 O* P5 ^- i- c% U+ {
Business database software% }6 @2 O" n( \7 j& F! C0 S6 s1 @
Computer data processing ) k2 J6 F6 m: v* y5 [
Data processing services
3 s' o: B N, TData processing supplies
: f/ z* S" V- ?5 e" _. K1 XData processing systems/ u; [3 S3 _, T) G6 P
Metadata Management
/ u$ a5 S' R1 I+ A3 fMobile Data and Information
6 d9 q, G/ ^! h; `; Q** Databases
& i [2 I6 R# ~- WWWW and Databases$ C/ y8 ~$ q {7 u
Workflow Management and Databases" F& L8 ?6 E4 {, ^% `* M0 t3 o& e
XML and Databases {. t* S( w y4 X Y! d
** Databases
" g5 S+ G/ j) u4 v0 |; Q; dData modeling and architectures; V9 ?+ |# g. _. z, ?3 i' A! }
Data streaming, data provenance and data quality
! }6 ^: @# J! B9 mData Security, privacy, and data integrity
8 L" c% h5 x5 SWeb Data and the Internet- n" I8 q0 } T, a* J6 g7 |5 q
XML and databases, web services, H/ J/ X! Y" i6 d; E8 Y; n4 Q
Semi-structured data, metadata
& M7 d! O1 X! v; |3 F3 ke-commence. y: C0 \: V5 r) _. @/ |# {
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2. Data warehouse and Data mining
1 j" X& _2 ?' ^1 E0 j+ I5 SGrid/Parallel/distributed data warehousing2 z; ?! m8 L* A5 x/ _" j8 S
Web/** data warehouses7 @: U) Q4 @! C8 q+ Q$ E3 v
Data warehousing and the semantic web' v5 ]$ r8 t8 ~# K3 D
Data warehousing with unstructured data
r/ B7 M- L4 JIntegration of Data Warehousing
6 N+ q+ X( i# n7 {# b9 _6 VData and knowledge representation
( j$ r+ m& i7 K' x. ULanguages and inte**ces for data mining
- ^: p9 ]) _" }, J, p5 v; M5 E6 aData integration and interoperability: P# v# L! F& n: ?) `+ L0 x4 [8 m
Data extraction, cleansing, transforming and loading0 |/ l, {; e% I2 n. ^3 p
Data mining and information extraction1 v8 _% f, q$ I4 ^$ x" J
KDD Process and Human Interaction4 K8 s9 [& I: o @
OLAP and Data Mining
& x( N- x3 B0 E# M- b6 s' BParallel and Distributed Data Mining
3 P6 m1 T* s& o( F3 RPhysical database design and performance evaluation
! D! U6 K7 a+ A' |* VQuery processing and optimization" }; A" q; p9 `- i4 r
Reliability and Robustness Issues1 X& L" o. q4 f3 h* P+ O" n
Semantic web and ontology
' U5 \) `* N& v" M9 Q1 LSoftware Warehouse and Software Mining
. q5 E, U& |* F6 a7 X0 t, ESocial and mathematical statistics
9 A! n! ]3 V! S' O6 MNovel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) % w: q3 O5 }' \/ Z7 a2 @& N: r
Developing a unifying theory of data mining " S7 g0 x9 y p0 j$ Z+ Y
Mining sequences and sequential data
& y& ^/ l1 m6 X; tData pre-processing, data reduction, feature selection, and feature transformation
8 D) B1 x5 O% e( M, rQuality assessment, interestingness analysis, and post-processing 2 L7 W( @0 @( N- B
Mining unstructured, semi-structured, and structured data7 T+ Z: @8 j. \( a" p( k
Mining temporal, spatial, spatio-temporal data
U3 R. d m$ N( W6 j. w5 TMining data streams and sensor data1 I9 W7 h. {/ o: A5 W8 B
Mining ** data8 J V6 f6 |2 U9 ^8 P: {4 B
Mining social network data+ V. h/ H: Q. X# x, i& {
Human-machine interaction and visual data mining ! E0 }7 X8 L E6 s/ y9 v
Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)
& I8 J$ b! |% h( t. u2 iKnowledge Acquisition & Management
/ q# x; A! a4 Z- r8 a8 _( z0 tKnowledge Modeling6 M" Q9 x. y" Y2 {5 J! {
Knowledge Processing
7 x' L8 r8 A# b- Y8 |Integrated KDD applications and systems $ S# n: c6 D* ?1 x! V6 S, q2 g
Business Process Intelligence
, {& T' f K0 B$ c& kCluster Analysis and Knowledge Base system
& M* l% p) [0 P! s+ w* MInformation systems technology
! P) b5 [+ a4 ?Other related technology about data mining
$ w0 B- p1 {( u# {, Y, Q, h
+ h- N% s1 z, I2 A; |7 a7 {3. Computer Science and Related Technology
, _+ \; y& F* y4 b; bImage and signal processing
3 S' N& B1 b% a$ gArtificial Intelligence 0 }+ w' K. h& B& X! Y+ z0 L
Software engineering
7 h& J5 o& Q5 T; p* Q( L2 C5 ASystems Engineering / U' J/ ?% ]* u' u. G+ [
Computer Graphics
9 V4 O* W' t7 J' K5 QComputer Application
% K' u7 z9 @8 X* R# wControl Technology : Y1 h0 E" ?8 g3 J0 f, |: d k
Network Technology ) B( q4 P9 Z( v, A( Z( l( l _
Network security + T: I3 m, y, Y* c" A& G
Numerical and symbolic computation2 ^5 k. K- X1 f
Computer Modeling and Simulation
4 R) D' \) K* Y6 v3 O" fCommunication Technology ) G1 N8 U- u/ v- U: x h
Algorithms and data structures
$ Z$ P3 }" K- j0 A3 ~& C2 t$ Z# }Computer Education
, |; F5 D5 m/ d% F% n0 ROther Advanced Technology
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" j- U9 E( X* }" @4 oDBTA2010会议联系秘书处& y4 Y/ D7 @5 k+ L( V
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邮件: dbta2010@vip.sina.com, info@icdbta.org0 M, \- }0 r0 L( l. [, e/ m3 q
电话: +86-15102769170& A" U. v+ b \, o
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