The 2nd International Workshop on Database Technology and Applications (DBTA2010); }. k3 G1 g7 x& X+ E( t" @
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): C; A; H9 v( w4 ^$ p! K
11月27-28，2010，武汉，中国 . I X, a( J% lhttp://www.icdbta.org/4 W7 n1 d u/ `; x/ J
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论文提交日期: 2010年8月18日8 ?! q5 ^+ R2 g/ \+ i( s
论文录用通知日期: 2010年9月 16 日 " @8 Z( A; ?$ p6 E9 l论文修订版本提交日期: 2010年9月22日 ! |- x. M6 w" k% z2 }: c论文注册日期: 2010年9月28日( J+ @9 N F4 r
论文提交系统: http://www.icdbta.org/dbta2010/submission/! B1 Y; t+ l, N% ~4 ~
会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc（只接受英文稿件）8 E e: d8 |" ^% N( P
IEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc （录用注册后提交） : C# } z% X. X& l7 H1 p( e8 z8 H# d0 k6 f5 l1 {* Z7 Z3 U
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。- A! [2 M& m% l7 f& T4 F4 q( g" ~6 l1 H
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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：& K6 ^2 \/ d7 I& i
) K# c" ?) y9 n8 x8 U& c+ W4 _6 j1. Database and Related Issue ! j1 d* B4 u1 j( |; A
Temporal Data 5 H" ] v1 p+ kScientific Databases2 u. A/ {* ?" o/ @8 k" u
Business database software . K/ ^0 } c9 P/ w7 V$ EComputer data processing + m( t3 d6 ^/ f2 q! E6 S- W7 ?Data processing services * m& T% E j/ C; _0 A2 M* V( T
Data processing supplies , r, F7 z6 a* s8 B0 k% U' `4 |
Data processing systems, ~# s" T6 X/ V* L2 O2 z4 u& o, U
Metadata Management% k) h, [ o4 L& D
Mobile Data and Information( C I6 @5 J, ]$ A
** Databases* x2 M$ E/ ]: P2 L
WWW and Databases! N4 F* T) \: G! s5 Z7 @. e
Workflow Management and Databases # E4 ^" i9 `1 r5 c/ |8 M# k8 dXML and Databases4 U. X k! j' X, I- i+ U
** Databases0 B8 T @5 |9 r% D+ r( H
Data modeling and architectures 8 h0 t; A1 v3 F) t# i2 e: ^Data streaming, data provenance and data quality3 ?3 f3 | S) a1 ^4 B# y
Data Security, privacy, and data integrity 1 m, T( R5 l f6 SWeb Data and the Internet 2 N1 _$ F2 H4 I2 JXML and databases, web services + Z' Y( X! L/ B6 GSemi-structured data, metadata 9 ~3 s0 e4 |! {+ fe-commence' \" |6 n0 L/ J& n/ {- G6 I
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2. Data warehouse and Data mining & Q- z+ L2 E) k1 z+ rGrid/Parallel/distributed data warehousing 5 \: a* E9 |8 y1 gWeb/** data warehouses- ^3 R( g+ [/ `0 e: `3 v
Data warehousing and the semantic web * b j$ N" _' u. z( dData warehousing with unstructured data! I4 s) w: m' a( f' C1 i" M' j
Integration of Data Warehousing r G9 L. A- ~1 t( f- AData and knowledge representation5 h+ x& o& Z$ C' D9 y; |1 z# m- C
Languages and inte**ces for data mining) T$ V* u8 c2 n. ^) ?& \- q, s0 j' p
Data integration and interoperability - W ]5 b% i" s1 h/ C! ~Data extraction, cleansing, transforming and loading 3 g5 |6 g, J1 s9 G& C: ~Data mining and information extraction 6 ]# E" H1 K' w. y% Y" V0 r; |7 v) lKDD Process and Human Interaction / E5 u' O4 e9 v2 MOLAP and Data Mining ; P* ?# m0 Z( S# Y5 u# RParallel and Distributed Data Mining3 b, s! F4 G$ H4 }0 |- v
Physical database design and performance evaluation $ n* a2 t# X2 ~) DQuery processing and optimization- ?1 k( J. a& y/ C6 y
Reliability and Robustness Issues : k a$ e0 m, D1 I4 oSemantic web and ontology ( d3 y; S; X! k3 W2 \Software Warehouse and Software Mining ; z3 l& A: o( ~7 K+ g/ L7 PSocial and mathematical statistics7 D9 k9 s" p( m& b. n
Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) # z7 N1 U& y6 j" G$ J* rDeveloping a unifying theory of data mining 3 t6 x; S* c) I9 k( AMining sequences and sequential data ; n. `6 z( A2 K7 [1 NData pre-processing, data reduction, feature selection, and feature transformation + q' m: X+ q$ d/ p: H4 I
Quality assessment, interestingness analysis, and post-processing 6 v# a/ }# d8 m2 \9 h
Mining unstructured, semi-structured, and structured data6 A! z: a) b# R
Mining temporal, spatial, spatio-temporal data/ d7 D8 O9 Q% _. i& ?% Y
Mining data streams and sensor data# n/ `1 w2 _: g% N
Mining ** data ) C5 v: s" I' AMining social network data ; t; i( H$ ^: q& S" `4 Q |Human-machine interaction and visual data mining % D' o9 E+ Q. Z; `) y3 Z
Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc) p2 t: O% a# Z \4 h) WKnowledge Acquisition & Management: G0 M0 ~1 U( Z* T) U/ `* f/ M
Knowledge Modeling / f* S3 c8 F( i* v3 q5 E; RKnowledge Processing ) ?' c- D9 k: L: c a$ vIntegrated KDD applications and systems / Q$ a( s7 r, w
Business Process Intelligence6 Y8 _1 A. j. F4 M; j2 p
Cluster Analysis and Knowledge Base system- o8 f+ g7 i; a, }; Q
Information systems technology - v0 ?4 y3 L' R6 G8 fOther related technology about data mining; z6 ]* J o& c Q5 [" G/ `
# g# B% Z: K6 v, D3 S3. Computer Science and Related Technology 8 n4 C; I: m, S4 I! AImage and signal processing U) a+ x% T$ Q! f0 Z* \Artificial Intelligence ! _; J/ B9 ]$ M: Q9 XSoftware engineering $ t; `6 T+ q0 ^% W$ X& X! vSystems Engineering 0 i5 P: `) j8 G% `
Computer Graphics + N8 L5 l3 S) d
Computer Application 4 i+ _0 \, ]1 m! K% x9 h4 i. GControl Technology f, m' G" o' tNetwork Technology 2 R" V1 f( [* E8 b6 ]2 U5 _1 B+ PNetwork security ( O! X& T X2 W
Numerical and symbolic computation- U' M% g5 ]* s( J* a
Computer Modeling and Simulation G: |3 ~/ J3 U8 O5 x: PCommunication Technology 4 l) j0 h3 ~5 O6 D6 a% BAlgorithms and data structures $ e4 J8 o. j/ x* k0 n/ hComputer Education# Q3 c, j" t4 r' k
Other Advanced Technology- @! ^7 ^4 v) E$ T2 Q
( z* E' K* Z. ?8 \====================================== , q O0 f7 ^' u3 X1 V. @0 R4 h MDBTA2010会议联系秘书处 $ x) T0 I2 O1 ^7 d6 A9 z4 V# r2 q; d; N0 {, H, e
邮件: dbta2010@vip.sina.com, info@icdbta.org 0 `* R1 V$ \0 R6 r X+ a电话: +86-15102769170* d1 J' c/ m, G9 b/ r& e$ u
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