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The 2nd International Workshop on Database Technology and Applications (DBTA2010)
) M( G, L3 W- r8 p6 m/ e1 K7 {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)
/ B6 w3 f; b9 z11月27-28,2010,武汉,中国 / ~1 i; u. { B" b6 L& ~
http://www.icdbta.org/2 [2 U X* h7 U0 ~: m
2 R" ~9 e, t' c0 M9 N" {1 k ^论文提交日期: 2010年8月18日: S) `, C* }9 N# g* ^" n
论文录用通知日期: 2010年9月 16 日
6 U' T2 u$ N9 `9 b- x7 v论文修订版本提交日期: 2010年9月22日& c. J3 M2 i9 a
论文注册日期: 2010年9月28日& o" z/ F5 o3 v
论文提交系统: http://www.icdbta.org/dbta2010/submission/
5 I6 M% u6 z3 i8 U1 C, A# F会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc(只接受英文稿件)0 N, B4 y" t9 W6 ^& o
IEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc (录用注册后提交)
% h' F/ l% M+ V* y7 n3 C: \
' W( S1 A* g* {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。
" ], l, l. |! n+ D; G
6 I7 Y9 w+ ?& Z& T; j/ ^- w8 f% e) {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:
& X- x. I' t. ~8 Y3 {
9 {" B% i; I" ]5 M" ^1 k& c1. Database and Related Issue 3 J: D* b5 i3 h/ Y5 |
Temporal Data
5 P$ n- S" Y/ F1 iScientific Databases
. S" k3 V7 [% s/ d9 t9 PBusiness database software
9 x8 s$ e/ Z2 Y8 F0 dComputer data processing 6 K& q# `/ v- r- u3 f" }7 M, [$ t* f
Data processing services
, R( a- S( N4 N$ X) F) v2 TData processing supplies a6 ] v5 x5 C0 z$ n- O- j
Data processing systems
- d$ h1 x9 u2 e7 cMetadata Management8 b7 B5 {4 n* w/ A, Z
Mobile Data and Information+ D3 |. T8 d% W" q8 m3 r
** Databases4 i# S6 p0 _$ r6 S- ?& h
WWW and Databases/ U8 d/ U1 _7 @8 p* _6 B0 \) H9 W
Workflow Management and Databases
) \: a( Y) A* [3 z8 j# l! KXML and Databases
) T! S0 M8 s" h9 e** Databases
+ B1 i- G* Z7 {/ i' gData modeling and architectures
' L! y) \0 ^. b- n; HData streaming, data provenance and data quality
, u8 i5 s1 z# A$ d: D9 u* MData Security, privacy, and data integrity 4 _' f% L8 b. x% G
Web Data and the Internet) S$ {$ F" h3 Q& C
XML and databases, web services$ [" ?2 z' m# O
Semi-structured data, metadata
4 _' p! W' K6 u0 J( T( f8 L% a8 ?e-commence8 T: \7 D0 R% n! Z
K6 t4 i# I+ |& r- R2 ?# x
2. Data warehouse and Data mining0 }# C5 S# s8 R% T3 e
Grid/Parallel/distributed data warehousing
% e" v E& t4 G8 x0 P/ C' XWeb/** data warehouses" d0 n% O' N G
Data warehousing and the semantic web
7 @: a0 u8 @2 W+ H' e* [9 n H: z0 lData warehousing with unstructured data
4 L+ e; [" B. dIntegration of Data Warehousing0 g* T* S% h9 f( d& O
Data and knowledge representation; Y6 Q+ p: b" v( ?2 z! i) g
Languages and inte**ces for data mining
/ o* v4 c% F4 k$ a/ Z+ C4 ?Data integration and interoperability x; w9 T& v& _2 j- |3 v7 A
Data extraction, cleansing, transforming and loading8 b7 r) O" @0 C& m( e
Data mining and information extraction9 T0 _) q6 b" h
KDD Process and Human Interaction7 i! ^6 [, w; N2 o
OLAP and Data Mining
# a: n/ ^4 U* J. y6 rParallel and Distributed Data Mining$ E* m4 `4 e& Q) O; [4 P8 v
Physical database design and performance evaluation
" K5 E' Z1 R6 Q1 j! Y8 b M# Y/ l( S$ eQuery processing and optimization
` u, J: S- |3 a0 SReliability and Robustness Issues( E O& ^, s. ]# O7 q3 k
Semantic web and ontology: }/ R8 F# X; U1 R
Software Warehouse and Software Mining% z. M B7 r% i0 q
Social and mathematical statistics
5 m$ _& n0 w3 }) ?% O, yNovel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) + @. E$ w1 `1 W b3 l% {7 [
Developing a unifying theory of data mining 2 ~, _8 ~% t* @, q! `% d
Mining sequences and sequential data/ Y+ ]3 Z$ k( S+ x" W
Data pre-processing, data reduction, feature selection, and feature transformation & q: J8 ?2 x7 K& l
Quality assessment, interestingness analysis, and post-processing
3 t; V6 u( U0 q, V2 iMining unstructured, semi-structured, and structured data
, T2 Z. R; P! J! X" x; LMining temporal, spatial, spatio-temporal data: F9 a" r: {. I! P
Mining data streams and sensor data2 [/ I7 j2 T* k9 _" i7 u! L
Mining ** data
9 e3 ~ o; x( cMining social network data
% [+ k1 q' q) t. DHuman-machine interaction and visual data mining
$ W$ f2 O. T3 b8 G: x% T6 ~Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)
2 |5 d& M( P/ o4 vKnowledge Acquisition & Management
4 R, x# z+ v" B8 z: NKnowledge Modeling' M4 {% i7 L$ g+ n
Knowledge Processing2 _# r q: a, w2 D
Integrated KDD applications and systems
( Y) y( K4 D- M% \0 j: PBusiness Process Intelligence
7 u: r$ ~. C- |) [9 HCluster Analysis and Knowledge Base system# Z+ V- Z" v8 i4 c: L: y2 L
Information systems technology" u3 a/ j0 v" b3 N5 N
Other related technology about data mining. F( z1 P+ B. v* O
" z; e* h2 M) ?3. Computer Science and Related Technology % ^# n/ h, I. K, ]+ c- V6 _
Image and signal processing 9 k* n1 M3 N) u/ b. F* S
Artificial Intelligence
% Z" T- ^! Y j- Q5 }+ |Software engineering ! Q) S( R+ F$ [1 V& q# b: E9 d$ e
Systems Engineering ) e; y2 D6 g( s/ u; M; T
Computer Graphics 9 T" @, ~6 p7 e4 m
Computer Application 5 l4 d$ c# t3 k; {# A
Control Technology
% W3 D7 K9 n& N: iNetwork Technology 8 c4 X" z1 V$ K- v% t
Network security ) H" H6 K z" Q) f$ [' K
Numerical and symbolic computation
$ q3 w( C- ~* Y0 xComputer Modeling and Simulation9 e0 l. v5 b0 e5 @" X# Y
Communication Technology + p8 v9 `) `# z) _- h& \- ]/ O' F! b
Algorithms and data structures+ j/ G" c @3 V- T! w9 a
Computer Education
4 j1 h9 K- Z) {- j _1 oOther Advanced Technology; f) z8 q* `( ^8 C/ G' l5 N3 n
& S0 ]+ _) r: y, v T; p( Y
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DBTA2010会议联系秘书处
I1 A. Z, ], b
$ t! F. W' b% i0 D4 e邮件: dbta2010@vip.sina.com, info@icdbta.org
5 Z7 h4 M( @8 U5 C" n电话: +86-15102769170
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