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The 2nd International Workshop on Database Technology and Applications (DBTA2010)
7 G: Y' z- Z- O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+ ?' f3 c$ e3 d* j* B11月27-28,2010,武汉,中国 ( P _1 M7 M: W- @. ?: U
http://www.icdbta.org/
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论文提交日期: 2010年8月18日
+ ~$ W0 _1 ~: K. \4 Q1 J论文录用通知日期: 2010年9月 16 日
' P/ R6 F# z- h/ v5 p6 A. X2 i- |/ j$ R论文修订版本提交日期: 2010年9月22日8 M* `9 z% s: b* B5 s& ~; U7 @
论文注册日期: 2010年9月28日
% Y) ~: s- ?/ l4 Y论文提交系统: http://www.icdbta.org/dbta2010/submission/, x. ?1 q6 y. p A0 }
会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc(只接受英文稿件)
4 P0 n! v) S$ q/ E3 L4 E1 RIEEE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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3 _6 J( m/ O- C) @5 A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:$ r5 `9 F2 |, o, r0 y
# o* ~' @- r; X) S! X4 e1. Database and Related Issue
1 L/ D: r4 U& U5 e" W7 q! [- z ^Temporal Data
3 `- }; J% w/ }3 h; n2 l5 e3 ~Scientific Databases
$ d; l6 L- U8 B/ P8 J$ |0 iBusiness database software
* h5 @/ A5 O3 b7 b& jComputer data processing 5 G0 p1 Z% e3 W1 O% u2 g) \+ J+ M4 o
Data processing services / ~2 u) z) Q. t' |- d) h% d
Data processing supplies
+ d& N8 a3 ^5 l$ g. G7 V( j. SData processing systems0 Y) k3 N; A3 S# |
Metadata Management5 ~! B; s% I) U6 h4 M2 T$ Y3 }
Mobile Data and Information+ E H. [/ |6 B1 J5 s' M2 D2 G
** Databases" B; C. s. ^, p* [8 d7 A9 Q
WWW and Databases! W I1 l) {9 g" Y
Workflow Management and Databases
- W3 {( U4 f4 O7 o$ @) q& H" _XML and Databases
l- z, q( b: y( l1 Q5 n3 l6 a** Databases" ^' X0 B" \9 {" u
Data modeling and architectures
7 ~) Y) t [* J, W6 V' y VData streaming, data provenance and data quality8 w' ~' e/ T6 {2 D2 |
Data Security, privacy, and data integrity 9 n# s( {* E. p: `
Web Data and the Internet
9 `0 u% t2 @- o6 a5 B/ bXML and databases, web services1 b! P2 f: t7 _& L$ x
Semi-structured data, metadata# q" Z) N, Y* d% e( U) j
e-commence# V4 Q2 f1 R. S
7 ]- s! o8 o: `; B$ V, E2. Data warehouse and Data mining
' A% J: g" p. C/ G2 gGrid/Parallel/distributed data warehousing
) j3 W" N O" X6 aWeb/** data warehouses4 A5 e8 A' g8 g2 k9 i6 l
Data warehousing and the semantic web$ W! J. _ L9 Q
Data warehousing with unstructured data1 U$ F p! t9 l+ d5 ]
Integration of Data Warehousing' i) J$ ?8 a# D1 ] o& i
Data and knowledge representation1 r5 K4 a8 E/ @! S
Languages and inte**ces for data mining2 T8 l4 k+ q1 o& { X* G
Data integration and interoperability; Q$ n2 E& F/ ]0 y* m: c
Data extraction, cleansing, transforming and loading) a2 t+ \/ d. |* N) q$ x* l9 \
Data mining and information extraction' r5 b; {7 Q7 |( Y
KDD Process and Human Interaction
) I& g' F" `& ~OLAP and Data Mining
/ }/ T) g- f* u" p; @# ]Parallel and Distributed Data Mining
1 Z% B8 j% T8 a8 l7 V8 T' v" lPhysical database design and performance evaluation
9 W) }7 X5 u1 T+ f) u/ k! @8 ?% qQuery processing and optimization
; C/ \' S T ^7 s, d/ c, {2 D" `; lReliability and Robustness Issues/ m$ i+ T, v0 X4 j. K1 M; L
Semantic web and ontology7 O, }+ J1 o2 _0 R3 U
Software Warehouse and Software Mining( @/ m3 ~9 a; u+ j. K6 s2 s9 o
Social and mathematical statistics
( [% l# L/ a. B& f) N+ ENovel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis)
7 C( q3 P8 Y. Y# {* J1 I# H) M, _) dDeveloping a unifying theory of data mining 8 c' o. q6 b* i7 a* u5 m3 }; L
Mining sequences and sequential data, A/ T* j/ K. S0 [
Data pre-processing, data reduction, feature selection, and feature transformation
5 ]% I+ D$ Q6 ^6 t$ X J9 }Quality assessment, interestingness analysis, and post-processing
$ ] h, q" X: }8 V3 CMining unstructured, semi-structured, and structured data
, V( n7 D% `6 u7 ~Mining temporal, spatial, spatio-temporal data
2 h6 X# ~7 G, ?Mining data streams and sensor data6 r, ?5 N7 u1 K- `) U- \$ W
Mining ** data8 H5 k0 e* l2 m' ?0 t
Mining social network data. o6 _9 T' S9 U% d2 W4 E. u
Human-machine interaction and visual data mining
) L2 _3 J2 l0 h& }& R6 v0 B6 \Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)5 P( S7 T. k. f0 p! a3 \/ s( @( M
Knowledge Acquisition & Management
( k6 i. G, [' ]% f! e) w+ O- E+ JKnowledge Modeling
. S Y. v& D0 w1 XKnowledge Processing
" X2 Z X3 I# Z& @/ M; w- e* DIntegrated KDD applications and systems ; g: U8 @. d# p( E0 o
Business Process Intelligence
3 f! ]* I2 q# [0 o- C- |6 zCluster Analysis and Knowledge Base system
# x, O \1 P% jInformation systems technology) b1 V8 B8 X) e5 g5 ?6 L
Other related technology about data mining
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0 U& ~7 z( v$ z5 ~3. Computer Science and Related Technology
$ j' o4 ~3 w/ V$ ~! ~. ?Image and signal processing / A1 E% N& L1 I) a/ R5 Y6 C
Artificial Intelligence 9 a& J; H4 w6 {7 w$ N8 d7 G
Software engineering
. g ]; P. V! g% C- {Systems Engineering
7 P, X; B F; D* K% V) KComputer Graphics 4 ?& }8 K7 Z3 [: i2 i+ b+ C
Computer Application
, ~9 N4 ]' ?1 v7 [; k2 q" a+ RControl Technology
1 _9 n/ K; ]3 ~; m6 B$ [$ yNetwork Technology ) ]: U- F: R" h$ u# _; c
Network security / f0 ]9 }& K! z W4 z9 ?
Numerical and symbolic computation
, G$ x6 H j! ~& ^! N2 @Computer Modeling and Simulation
# f% Q2 n- h0 Z$ d7 u+ S. I4 LCommunication Technology
: |. D# H3 S3 WAlgorithms and data structures
; o. x, O; t: M* C0 h0 `; L/ `Computer Education: {, J1 U d7 D S9 \
Other Advanced Technology
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4 S: Y o' f( C" N7 b. f2 ZDBTA2010会议联系秘书处8 F1 \8 L2 e5 n$ t, A
# O8 {0 e% g* G3 |6 ~1 x7 Y- `* Z邮件: dbta2010@vip.sina.com, info@icdbta.org0 A3 o' w5 C9 F# k
电话: +86-15102769170' |: X6 _( ~5 O. F" |4 {1 `
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