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[英文期刊] 第二届IEEE数据库技术与应用国际会议-DBTA2010

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发表于 2010-5-12 16:42 |只看该作者 |倒序浏览
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The 2nd International Workshop on Database Technology and Applications (DBTA2010)2 Z$ l1 W3 d; t: Y$ R2 h9 n
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)
2 p' |1 k$ |$ l7 t( g11月27-28,2010,武汉,中国 0 j) P2 y' }6 j- e  ~
http://www.icdbta.org/* s  k; k% h$ o1 Y! v- J9 J
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论文提交日期: 2010年8月18日* c- u/ r) k4 P
论文录用通知日期: 2010年9月 16 日
: l0 l6 B( D7 N$ V3 Z: k6 N' s论文修订版本提交日期: 2010年9月22日2 @9 ]' u& d/ G( y8 p
论文注册日期: 2010年9月28日
2 J0 ]' V2 v5 V2 l& ~论文提交系统: http://www.icdbta.org/dbta2010/submission/8 e* c( t* |( v# }  J
会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc(只接受英文稿件)
. @9 P/ e$ P; sIEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc (录用注册后提交)
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5 T: s2 M: v; 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。
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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:6 P& G* c; M3 I, K

) K8 A3 k& _4 s! Z& L0 p1. Database and Related Issue
7 q9 J- r1 b6 Y( Z3 {; I6 FTemporal Data
" A' x  A5 h6 P% YScientific Databases* V1 s" O/ S3 B: ^; M% w  M- h
Business database software
# q  [$ W% l6 \2 eComputer data processing ' ]6 U# f% s8 j6 F; B( @3 j2 y
Data processing services
) @. q1 u0 C  aData processing supplies
% ?& u; y5 w" L  X* ZData processing systems
& g0 d: P& ~3 }/ H+ \1 e4 @2 g4 JMetadata Management5 [8 h: R' H$ A
Mobile Data and Information/ f" y2 z3 l- a! a
** Databases
) R& n  `" ~" V: z! l2 QWWW and Databases8 f; A0 F" K! r( ]% O5 w
Workflow Management and Databases
* c$ c+ R- T# VXML and Databases
1 ?$ W! O2 _( @9 D& Q** Databases
/ ]1 B# a% V8 `3 K- C7 C; i9 uData modeling and architectures
  ^! {. f" Z* x& uData streaming, data provenance and data quality
: g# Y4 q, R2 s8 {; _0 C; YData Security, privacy, and data integrity
  @& H0 B; V% g5 S5 OWeb Data and the Internet: ^6 g; d9 R: C9 p
XML and databases, web services
' p3 b) I1 }8 @Semi-structured data, metadata% H( |7 Q; o! w
e-commence
9 k& v; x4 |1 O  r) ^$ w) @* }+ K4 }$ m: u1 |
2. Data warehouse and Data mining
  b/ o! j1 Q$ h$ Z' G- h+ }8 r' O0 QGrid/Parallel/distributed data warehousing
" w& \- G; C* k7 Z& ]" e  h; V0 rWeb/** data warehouses
+ `- {# V# V* q  {1 hData warehousing and the semantic web
5 Z+ @; d& w4 G* j+ m" _& L" y" [Data warehousing with unstructured data* m" q% ?7 z& y$ L/ j" q' A
Integration of Data Warehousing
( q9 n$ Z5 [1 z# _Data and knowledge representation: ^9 }, y- Q3 T, h% a
Languages and inte**ces for data mining
. C% `* W& k: h9 E2 DData integration and interoperability! r5 P. Y6 h3 _
Data extraction, cleansing, transforming and loading
8 F' h% _8 T6 J- L& N  yData mining and information extraction8 N% l' X# _, g( p
KDD Process and Human Interaction
, V7 \2 B$ d  u4 ~8 aOLAP and Data Mining
; D3 t3 N! t. g) Q2 n# J  C" ?6 \9 ?Parallel and Distributed Data Mining
$ e8 P1 t" F9 U, ZPhysical database design and performance evaluation2 I, T' T( d* u) Y! E# o+ h# s
Query processing and optimization  c$ C6 \& M' ^* c  q0 ^
Reliability and Robustness Issues
1 @2 v: g5 T, v3 W% f7 z5 n% S1 ZSemantic web and ontology. q  H8 n% K( a& C% a4 K( P* [; w
Software Warehouse and Software Mining
+ ]3 |8 c5 W7 w- vSocial and mathematical statistics* U9 {  h* U- q) {2 r  Q6 n
Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) 2 D6 {  g* g2 M; ?/ h0 |" E
Developing a unifying theory of data mining
( r5 K. i. p$ ^9 e1 ]" l; i" `Mining sequences and sequential data
* I0 X5 c5 i& a- o! VData pre-processing, data reduction, feature selection, and feature transformation * b! P/ f& e9 p
Quality assessment, interestingness analysis, and post-processing # `' S3 ~; u) }
Mining unstructured, semi-structured, and structured data
, b/ V  R) {! {/ A% d( KMining temporal, spatial, spatio-temporal data
; {) A0 F- ?5 r/ }7 T8 tMining data streams and sensor data8 l4 |7 w  I4 f4 W
Mining ** data4 x; F1 W. U* Z# N
Mining social network data' G4 l7 I2 E0 V1 Q% }( w7 B. U
Human-machine interaction and visual data mining
& Z/ d+ v2 Q, I2 ^' }Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)6 F8 s6 O0 v% f3 |
Knowledge Acquisition & Management( E3 c4 E- P- ?3 j% [3 ]* x
Knowledge Modeling
7 ]( q3 I' R! oKnowledge Processing! f; D, U7 p3 G. Y8 c* z
Integrated KDD applications and systems $ _( [7 ^+ @0 d, `7 H
Business Process Intelligence6 g0 K( _9 C$ H  A3 e
Cluster Analysis and Knowledge Base system
2 b+ c! H% T( J! KInformation systems technology
* F9 i- \/ c8 V, hOther related technology about data mining) q3 z$ s- Q) E( L4 D/ r! N- i8 V+ `
8 |9 R! `; |7 C3 B/ i( B/ i
3. Computer Science and Related Technology : s* a  V$ Q% B  X  l
Image and signal processing ; ^% A  G/ Z' ~/ u1 }6 `
Artificial Intelligence 7 Q8 `; V! T( S# S3 C
Software engineering
# k' Y" D+ l8 x# x" fSystems Engineering ' _1 F9 R4 Z& g" s' P
Computer Graphics
) J8 ~% w4 c3 v) E7 yComputer Application , m  @$ v( v7 a7 t
Control Technology
, R8 m2 Y) V* ~: M: `* JNetwork Technology 4 e& t8 c2 n# r
Network security
% U8 J! a, V- H( a; g: a* ~) g! BNumerical and symbolic computation
+ K2 b7 o9 o) E) t4 P) ]% E- @Computer Modeling and Simulation
  @" }# P: |! w2 s7 Q; A, gCommunication Technology
+ Q% G( E. f& c6 `: dAlgorithms and data structures; T, Q) @% E9 K
Computer Education
1 @! w2 E5 _5 U! COther Advanced Technology& O- d$ x: d0 [8 d1 M$ @

/ h. N8 b, c7 \9 _1 I3 [% @======================================* D2 a! p& O8 w
DBTA2010会议联系秘书处
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邮件: dbta2010@vip.sina.com, info@icdbta.org5 T# v, }6 \; A& |( Y! d! H
电话: +86-15102769170) @& Z3 Z5 [3 |4 @1 ^: N
======================================
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