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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)
4 t$ d9 A& Z; B* n. d$ J* b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)- e4 v6 N" j" j1 f6 {
11月27-28,2010,武汉,中国 / w7 Z% e: z/ S* V+ G5 K8 j6 o7 S( R
http://www.icdbta.org/
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论文提交日期: 2010年8月18日5 n3 O% ]: C) O4 I6 J" t8 [
论文录用通知日期: 2010年9月 16 日" m- t8 c2 C: ?4 Z! Q
论文修订版本提交日期: 2010年9月22日5 ]& P2 S' N+ d: f& [
论文注册日期: 2010年9月28日" h' W) Y7 q4 s& c, f) W
论文提交系统: http://www.icdbta.org/dbta2010/submission/
( F. R! w  e/ B会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc(只接受英文稿件)
0 F( x. J; z2 J" Z" i* ?IEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc (录用注册后提交)
: U6 m7 r& ]9 e* p4 t. D/ e/ G( ]* n. B3 q$ N
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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. b' |; {6 ]4 B. R- 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:: F$ c& D5 }. Q1 Y3 @

# ?  p- X$ G8 h4 H1. Database and Related Issue
6 J0 F0 h# t$ m) N* T7 Y/ Y- _Temporal Data
2 J& e+ }7 y0 S3 Y4 u/ r; yScientific Databases
5 N. J, ]1 e  O! {. U+ J( mBusiness database software+ t1 o, ^9 i% j1 R+ N
Computer data processing % Q! M8 r' g( t3 l
Data processing services
1 M$ l. g5 b; b: }4 CData processing supplies
  n& G4 Q" s/ M# y. tData processing systems
/ z; w! i# f/ h3 pMetadata Management4 G  d1 L5 X( ?. w( \1 {( Q
Mobile Data and Information5 a) e# P% m2 o4 j  g  n4 O/ l
** Databases2 M2 S! H) e, R) J# c
WWW and Databases! Y, O, t' f2 c% z/ \
Workflow Management and Databases/ T, j8 T9 M) m, p" l4 B0 q
XML and Databases& K2 C8 |/ [# m3 Y/ e4 W5 ]
** Databases
% w2 Z) c0 {9 E& U% n7 VData modeling and architectures
- F4 A; g& C$ FData streaming, data provenance and data quality
  \/ i" b: @0 W& oData Security, privacy, and data integrity
# P$ s" m# U$ m, w# W9 h& RWeb Data and the Internet
  w& o6 G, ?( |) [3 RXML and databases, web services
/ y$ j. e7 k+ w  U9 g$ TSemi-structured data, metadata
. G3 }: s8 n8 G$ N) Je-commence: s, X1 ~9 G. V9 g! a, e
: M* ^7 d" o, ^/ u8 ~
2. Data warehouse and Data mining
3 c( @& m% [9 U( W! m& jGrid/Parallel/distributed data warehousing* v( P, v" \8 v- e. A# P5 z, {# o
Web/** data warehouses9 B9 d7 w4 x( s$ h) l4 ]1 Q& q
Data warehousing and the semantic web! o( b5 g! f1 ~( b1 I& }
Data warehousing with unstructured data
* M# e! a6 w7 O4 i# x- r1 FIntegration of Data Warehousing( u% X0 }8 V" ^4 m
Data and knowledge representation5 _+ ]; _: q+ [0 V/ V$ C
Languages and inte**ces for data mining
9 X( m3 T- C/ h* h% {- i2 M% o8 [Data integration and interoperability* D% I: z7 b( o1 ^; l  ^3 R
Data extraction, cleansing, transforming and loading; _# M7 E+ A6 f! G4 }  h
Data mining and information extraction
1 Z, Y) @. J$ d* V+ P- g+ yKDD Process and Human Interaction/ `8 v' ?; |# p- D+ F* P
OLAP and Data Mining
9 y. T1 I7 r( QParallel and Distributed Data Mining  B1 l! c3 m* b7 S9 Y* H% j8 l
Physical database design and performance evaluation
8 I3 Q7 i/ M2 \9 }6 t! O  J  vQuery processing and optimization
0 o/ w1 m; \3 n+ FReliability and Robustness Issues6 e  B( k( K! S, s  y" [
Semantic web and ontology
2 B$ c- A1 s0 F1 VSoftware Warehouse and Software Mining) y5 i/ A3 i. P/ R: d: i- B
Social and mathematical statistics
9 {$ ~5 [  A2 F) U; Z% mNovel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) ! t, D! ^7 ]5 Y$ l4 Y% R0 `
Developing a unifying theory of data mining ( |( L6 z3 R! @4 b8 K7 _
Mining sequences and sequential data
7 }4 s+ v0 v- Y6 \6 o1 VData pre-processing, data reduction, feature selection, and feature transformation + c( h8 a5 W, k0 p) E* e0 z$ T
Quality assessment, interestingness analysis, and post-processing
" @; L% X$ q+ j+ ]* H9 MMining unstructured, semi-structured, and structured data
- n& u# a. k8 sMining temporal, spatial, spatio-temporal data1 Z1 B; Q% Y6 H$ ]
Mining data streams and sensor data1 [; Z; f6 o' _  \. P
Mining ** data! r. c& H3 }+ v, l- S" c; b
Mining social network data
0 O) ?/ G7 |& \+ RHuman-machine interaction and visual data mining
9 Y) {% V1 f3 U0 J$ J- d) Y: R1 {Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc): ~5 F! J( c* a
Knowledge Acquisition & Management( ]% K! Y2 i( ?* y6 A2 C
Knowledge Modeling
4 h# r  }9 j3 Z2 bKnowledge Processing
/ F1 g9 ^) c, pIntegrated KDD applications and systems
, A& D4 U9 F4 t3 }! b# t( ZBusiness Process Intelligence0 k4 R' X" X0 L4 b7 b3 B" i
Cluster Analysis and Knowledge Base system
+ ?$ f- m* R2 u& u( H* G* qInformation systems technology' p9 d6 Y6 ]2 M- e; O
Other related technology about data mining
* B( [6 |0 ~' ]3 ~
4 K7 {/ e) z) v/ E# g) h& T3. Computer Science and Related Technology
1 j3 M7 z& F; N' ^& cImage and signal processing
" k/ e, J3 `) RArtificial Intelligence
7 Z) F  r! Z$ H3 W8 [6 {' z" rSoftware engineering
  q/ L: s1 y8 s- R& l  [5 @8 tSystems Engineering ; h+ j2 r/ Q( j# P; q
Computer Graphics
& c1 e2 G4 [: u' Q3 ~Computer Application
8 c& T3 s  j4 T; d: `Control Technology 1 m/ w/ j/ i/ g/ h3 C* p- u
Network Technology
; P5 M6 o0 Y8 v8 K9 P( S7 u. gNetwork security ; T' N# Q' g. N0 y' j
Numerical and symbolic computation
. y4 c  q7 F+ f4 _$ O1 gComputer Modeling and Simulation0 M: v4 q1 L$ z
Communication Technology
- _6 M$ _9 Z0 t$ p2 F* zAlgorithms and data structures
+ {/ x; B: T9 R$ b( k% l' _# C3 BComputer Education: D. T; C+ J* B4 u" w2 ~5 i5 \% ~
Other Advanced Technology
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======================================
- U8 y$ C, c+ w; c; ]* _/ BDBTA2010会议联系秘书处5 [( J6 ^  x. [- r3 n1 i0 ?

  @! U0 v+ H0 |( k2 r" P3 o邮件: dbta2010@vip.sina.com, info@icdbta.org
1 k, x" g% T0 E; G+ Y) \2 W# s电话: +86-15102769170
  |9 }9 d! p5 ?======================================
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