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The 2nd International Workshop on Database Technology and Applications (DBTA2010)* d5 P& r, R7 X3 z
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 q$ J- m( j$ ^( p0 k
11月27-28,2010,武汉,中国 6 s& V. f6 H$ p. h" k
http://www.icdbta.org/ & R" N( T8 h( _1 s y8 V
5 |( [) W8 v/ T! L. ^ 论文提交日期: 2010年8月18日
/ i. Z- r/ A7 K# T 论文录用通知日期: 2010年9月 16 日5 \7 W# B3 H2 ~) q. ]& h
论文修订版本提交日期: 2010年9月22日6 _$ u; N, [9 o) X8 A! B
论文注册日期: 2010年9月28日
$ X+ G) B& ^+ M) Q$ M7 p2 x 论文提交系统: http://www.icdbta.org/dbta2010/submission/ % u- U1 e& X" ~8 O
会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc (只接受英文稿件)2 u A+ x$ X6 ^. \5 R7 u
IEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc (录用注册后提交)" @& Z# I- e2 I3 \; S- a( A
& t/ Z6 q( j0 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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6 r2 m" a/ i+ f! R/ n# F: 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:( c3 e _$ G, Y6 r
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1. Database and Related Issue
0 s. Q9 e, k1 g1 z3 ` Temporal Data" Q8 f2 m3 t! m( B! [. ^2 w+ |- k( H
Scientific Databases
0 T/ L! S* s' t, ^) \) j+ G Business database software
( `* e. E+ ?; e$ a: ~: H Computer data processing ( b: m2 ]3 Q: w8 f4 k0 _
Data processing services ( F8 W6 _# B2 e% U& v6 ]4 {
Data processing supplies
' i" b1 o( a5 Y. R# R Data processing systems
2 e: i/ I" x+ i3 ~" F Metadata Management
: |6 a+ b* c1 z6 W, ]2 A3 O$ d Mobile Data and Information0 B; @5 N7 ^ y! z1 q% r: m
** Databases
; O4 `9 i, t1 p W9 E/ e; L WWW and Databases) f1 o" B3 x' c" R6 h/ t
Workflow Management and Databases T" n8 x+ ]# v( B" \
XML and Databases
8 a' x2 Y& z6 t% |" L8 I; S5 g5 Y ** Databases
" \2 N2 e& u$ U Data modeling and architectures
" R1 g h: U, Y: o+ N/ R Data streaming, data provenance and data quality% C3 A& W" y) ~8 q$ D/ J
Data Security, privacy, and data integrity ' _- b- Y/ r% ]- f
Web Data and the Internet
( i. @3 ?' F- E9 } XML and databases, web services2 F, o( \+ ~$ e+ V+ ?" b! b" j
Semi-structured data, metadata* D: i+ H6 N! z& E6 W% l
e-commence
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6 W9 x! F3 S1 q 2. Data warehouse and Data mining
* b9 |0 C5 D, D Grid/Parallel/distributed data warehousing
. a! k+ m+ y2 l/ i+ V Web/** data warehouses
2 l2 s# \) @4 u# {, x6 j Data warehousing and the semantic web: x0 Y) \/ N. A6 t; @0 v7 B/ ~
Data warehousing with unstructured data( d# u' @- _: t5 d5 l7 I' T# D( n
Integration of Data Warehousing
' W' ^# H* Z+ V+ [4 Y Data and knowledge representation
7 r j, u" y/ `/ z6 q/ ]8 r Languages and inte**ces for data mining% K0 n. M6 S/ k
Data integration and interoperability: b% D; ?* n' B( W0 r9 \ i
Data extraction, cleansing, transforming and loading! r- Q' ]+ P3 n+ r) l
Data mining and information extraction) o! x3 E1 l+ d+ B
KDD Process and Human Interaction
i& L7 M) z, g OLAP and Data Mining2 s0 X8 h3 b' {5 s
Parallel and Distributed Data Mining
0 O+ c7 f8 N$ ^1 z Physical database design and performance evaluation
! y8 S+ ?/ @- r8 ]4 { Query processing and optimization, W! L# P5 Y1 R2 h" m
Reliability and Robustness Issues
$ P" {$ Y/ K7 x8 i; J4 g! X {2 n Semantic web and ontology
' j P6 J/ _* ^; n( X: q) y4 m Software Warehouse and Software Mining9 m% V) U& q- w5 A+ w# d
Social and mathematical statistics
' Y# Q9 A& ^' {, v8 R Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) ; n5 k' [0 z# s5 P$ O5 s7 F
Developing a unifying theory of data mining
0 ` ^6 y4 s0 B' V$ L Mining sequences and sequential data( V( y8 M# X0 W0 U; ~0 q2 l
Data pre-processing, data reduction, feature selection, and feature transformation 9 U7 M9 S! S# {
Quality assessment, interestingness analysis, and post-processing
$ G7 y' G: u+ N& { Mining unstructured, semi-structured, and structured data! R) a# Q6 s' ~; h' Z* N
Mining temporal, spatial, spatio-temporal data9 U3 x3 x! t2 S8 k8 n: W
Mining data streams and sensor data
) A$ z J) V# \+ @% [3 O/ k Mining ** data( H+ q$ h( J$ J/ ]+ Y
Mining social network data
% b- G4 d" t/ I2 O$ M( d6 ^/ T Human-machine interaction and visual data mining 1 W! H0 u9 r2 q; P. g
Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)
. n; x/ H+ N3 @" W Knowledge Acquisition & Management
+ a5 o) m/ S3 q, z, }9 H Knowledge Modeling! M* O& B! {$ {& A3 M! R2 \: j
Knowledge Processing
" q/ T: }6 I/ _* d Integrated KDD applications and systems
' m \ }4 w, g; C1 F& m1 O$ d Business Process Intelligence
s$ T% U+ E) D C. Z6 N) t Cluster Analysis and Knowledge Base system
' ^* L8 X) C% g Information systems technology
* E# J0 t' |; o! P: x7 t Other related technology about data mining$ n' @4 Y- b$ }; U
) W8 a8 r- d- E$ A1 H/ L4 N 3. Computer Science and Related Technology
/ y- P2 ^1 f% ?2 T1 |9 [. F Image and signal processing 9 [+ o: b+ a. L& @( {
Artificial Intelligence
# P( m: V0 S; a. O" s) @4 C% ]9 \* u Software engineering
6 ^1 A [ Q, v( ~0 C* g1 K Systems Engineering t2 c3 c+ ]0 s8 B
Computer Graphics
' s {" p: S* c% N Computer Application
( {+ C z; k7 G. R- e! L Control Technology " W' u+ F; ?! q* L- J7 i8 T
Network Technology , X& Y5 \& l" `& s5 a3 T! g
Network security 5 B. l y% t" s& w( f
Numerical and symbolic computation5 M7 O7 C6 n$ T: R+ Q4 B' B# o6 G
Computer Modeling and Simulation
( c$ B& S0 C- ~/ e Communication Technology
; R; t) U3 s' K4 {4 q5 G8 K0 @ Algorithms and data structures4 ^( [- \' b9 _5 u; a& ~0 _6 o- Y
Computer Education
6 A% P) p; [# v Other Advanced Technology6 v7 n5 D2 \0 B l6 Z
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- U( L7 j; B( E, W DBTA2010会议联系秘书处
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! Q# x, {0 `# X) b- S, \1 L- M 邮件: dbta2010@vip.sina.com , info@icdbta.org
0 K0 ]* C) b9 h7 _# \ 电话: +86-151027691707 o# s _) |, T8 G. }7 w
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