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The 2nd International Workshop on Database Technology and Applications (DBTA2010)- @ a0 {. P0 X& {
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)1 X, A* q$ o; R0 X; } ?
11月27-28,2010,武汉,中国
7 o# K5 o2 C/ n5 r" D; \$ D7 @http://www.icdbta.org/4 M0 o: K3 c4 e5 B
( k* X, j- L5 r5 s8 T论文提交日期: 2010年8月18日" f* y. W0 W3 `& j( G2 F
论文录用通知日期: 2010年9月 16 日
* y- n/ S( n4 H! w论文修订版本提交日期: 2010年9月22日
% Z. U8 l3 H0 t; }4 _9 n论文注册日期: 2010年9月28日/ y- k6 `$ H, B
论文提交系统: http://www.icdbta.org/dbta2010/submission/& m2 P8 b. s' m) v/ P- R0 x5 P
会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc(只接受英文稿件)& J; F- h) ^9 {% ]) R, m
IEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc (录用注册后提交)" ~/ Z$ a4 |4 Z
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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。3 D* p9 H; C- i* d; S1 ?
1 V" [$ i8 Q: k( W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:
4 A# r- V% @" g% E7 I
# T: D; U! J- c) `) J; z1. Database and Related Issue 4 O, |9 A7 V. G* V
Temporal Data
+ l2 v. z# r5 Q$ Y: c6 WScientific Databases
0 c; V5 y0 u3 b7 J9 X. @Business database software
" G8 ~" x/ I* I1 D1 G8 g$ IComputer data processing 7 Y Z1 R" V: P! P1 {" V) G8 c/ y
Data processing services & p/ D d1 t5 @- a
Data processing supplies
& h- Q( M. X7 U5 `+ l1 P6 zData processing systems
+ B! B6 o8 P( z6 [% dMetadata Management
& F( h+ w8 A) X6 ^6 sMobile Data and Information% g0 u( d- _* @/ |: e. _2 n
** Databases, o, t( s& m9 c; P5 p
WWW and Databases
! V6 e4 T/ F) r5 B6 U) ZWorkflow Management and Databases" w6 f8 V# k& L9 q' x
XML and Databases# \& Q$ ^0 X) T& V; k3 v7 G5 {
** Databases3 W! _9 z3 d/ t" M$ }
Data modeling and architectures
) M; j( R4 g% v# K$ l. O- _" V/ ]Data streaming, data provenance and data quality
( o/ A5 }4 ~9 d! kData Security, privacy, and data integrity * ^/ [( u3 W+ x# N2 o3 T
Web Data and the Internet
: ?# K/ }& g' F5 r6 R1 sXML and databases, web services
7 @2 e* D, a/ V( \! m X- H! J/ DSemi-structured data, metadata( Q- F7 r. k2 Y3 N. H' U, {
e-commence4 s! K% a7 y5 Z0 S# I: I( \% \
% ^# t! V% }. {& |2 d6 z, e$ c
2. Data warehouse and Data mining
9 |. h' Y' Y/ t, RGrid/Parallel/distributed data warehousing/ l& v* u" h' R2 \# @: x$ H% t3 M
Web/** data warehouses$ x6 T. W4 P# u& `; F
Data warehousing and the semantic web
* [. n, [8 w5 I, Z& [! q ]% IData warehousing with unstructured data1 |4 w2 l S5 h0 p! ]: M0 S: R
Integration of Data Warehousing0 ~" j' s8 t; l( ^3 B
Data and knowledge representation' ?& i" j7 ^7 G M* }
Languages and inte**ces for data mining
$ ^2 Z3 z" t% U Q/ eData integration and interoperability
+ o$ q# g0 a& s* [5 d/ a9 ~9 GData extraction, cleansing, transforming and loading
2 b/ H d' U5 b& X/ `1 p: tData mining and information extraction
2 G- K& D/ D/ aKDD Process and Human Interaction
; F: z; H8 {5 R5 hOLAP and Data Mining
5 `/ e, g, @8 D: l2 i! sParallel and Distributed Data Mining0 y3 h8 r6 D- G1 {: F" }
Physical database design and performance evaluation( p f3 `* b" }0 B% ^6 V: A
Query processing and optimization; ~% b$ Y' [+ ~! t) c3 Q$ j
Reliability and Robustness Issues0 C1 F5 ~7 I. R9 {' d
Semantic web and ontology
- t! }: `3 c0 P0 V6 MSoftware Warehouse and Software Mining
+ g6 v- f; F7 H ^2 `1 E* Y/ |Social and mathematical statistics
5 l3 E$ I: |5 X/ ^Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) \9 m/ m) y# q
Developing a unifying theory of data mining 8 t) W6 v% e* W4 t
Mining sequences and sequential data8 D+ m a* ^- b, N
Data pre-processing, data reduction, feature selection, and feature transformation 1 }. c/ W. t3 r8 J: M0 {7 G
Quality assessment, interestingness analysis, and post-processing 6 C3 T+ U5 B- V6 M* L
Mining unstructured, semi-structured, and structured data
* Q7 V7 {$ i7 } SMining temporal, spatial, spatio-temporal data% S1 c- Z+ W+ e1 L/ m- |/ @
Mining data streams and sensor data
$ j6 g! w2 W2 _: l7 J, W0 E/ eMining ** data4 d, ?+ |+ \" H$ m+ @6 G- R
Mining social network data2 m6 @6 N, O7 {
Human-machine interaction and visual data mining
* F; V0 L3 l% P0 @/ r) m: F! cData mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)
( e5 [ f4 |6 E, ^4 U w) rKnowledge Acquisition & Management
% G* U$ Q) k- NKnowledge Modeling2 ~0 `8 |1 `! G9 L9 F S
Knowledge Processing, {2 B( a6 J" @( V0 n: d2 D3 k
Integrated KDD applications and systems
& ~+ Q0 L0 S; e& L/ P# VBusiness Process Intelligence. e9 a( S$ F+ m% f5 n. b! T
Cluster Analysis and Knowledge Base system
5 r% q4 d% C( w) N1 bInformation systems technology
3 @: k2 P: a# j6 qOther related technology about data mining6 O5 @/ l0 y" c- x, v
' O, t9 x) Z. A- d: y3. Computer Science and Related Technology 3 s J: w2 a6 R- l7 A8 `) {
Image and signal processing
( l' N5 k7 Z3 L Y+ \# Y9 eArtificial Intelligence
k$ O4 y# l; OSoftware engineering % i8 p7 e" W8 \( J; u0 x3 ^
Systems Engineering
3 H4 `# D2 W" IComputer Graphics # q6 `& X! j% X* l' o) I
Computer Application
7 s% B6 l1 _5 j2 ?- ]; V) HControl Technology 0 A- T I3 j) F/ x T
Network Technology
8 ~# i4 G$ b4 ]: h% ]6 n8 x B" }Network security % p/ _" ]' v: s6 H; h9 X }/ Y- C
Numerical and symbolic computation
2 c S5 ]5 T2 b3 \7 @Computer Modeling and Simulation0 C% T8 O7 @3 F! P3 n
Communication Technology 8 ~. L9 L& f; k' e: x9 N
Algorithms and data structures+ B" l# o" |+ f3 R8 l- r
Computer Education
- E4 o8 i2 M3 j) |4 i$ COther Advanced Technology9 F* t5 x! h! x! ~ G. D! _2 `5 u
\. R% i( G; u. I# J
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& _ t2 W% i2 `: \% BDBTA2010会议联系秘书处& j$ }( Q9 e# N1 g" P
7 m& K @' ?/ M' o0 @
邮件: dbta2010@vip.sina.com, info@icdbta.org
6 Z6 g) ^( f7 y7 D4 S9 Z/ v, C电话: +86-15102769170
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