The 2nd International Workshop on Database Technology and Applications (DBTA2010) V( Q- W! f) N4 ~
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) ) A' U; a* C3 ^. M% h8 C$ r11月27-28，2010，武汉，中国 9 h p6 W w" g% @' nhttp://www.icdbta.org/6 h- E+ s$ j* M7 D" `: R0 ?
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论文提交日期: 2010年8月18日 + j5 y: i7 J! ~8 i4 k论文录用通知日期: 2010年9月 16 日8 j5 y' Y+ X' X* f
论文修订版本提交日期: 2010年9月22日1 D. ~* K- K% z5 l
论文注册日期: 2010年9月28日5 ~/ T5 z. ~/ N! s
论文提交系统: http://www.icdbta.org/dbta2010/submission/9 x% Z' U% c, B3 ^; \
会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc（只接受英文稿件） ( `) o% J+ \+ j, OIEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc （录用注册后提交） / x7 ] s. d. k8 c1 D5 ] 4 ^4 M$ r/ | |3 t& U o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。9 U2 h% y% E" }4 A! `# C1 _. S
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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： 1 G9 H; z$ N( a3 r0 l3 m1 e: r/ b' e" `1 E
1. Database and Related Issue ( o- }' H! K5 U/ n! e; _Temporal Data( Y: f: q! B G
Scientific Databases) }3 `! u$ g- n1 Q6 Z" S
Business database software , }5 q" j" P! H VComputer data processing 4 N; n @3 L. _7 F. e2 UData processing services 0 A, w& l M) F7 q* }4 JData processing supplies ; N p4 U# o& c4 ^% Z6 l
Data processing systems, c, `8 d8 m. L
Metadata Management T' r. H: W& H$ n$ c
Mobile Data and Information% C4 Z; d" b3 M) s! u
** Databases / ~* t% k r9 A" a0 }WWW and Databases% N q+ x4 S" y8 y/ C2 w) `
Workflow Management and Databases 1 S' [1 a/ Y) Y: v$ S8 zXML and Databases4 M% P1 b2 P% m% ~+ s
** Databases: v( P+ X8 x& x& |
Data modeling and architectures; W( i" |6 S4 O/ ~- E2 g# K6 v
Data streaming, data provenance and data quality ) m. W8 V' \/ A: I1 x8 YData Security, privacy, and data integrity % a# z! U# B; k( i( S: {+ S
Web Data and the Internet. f+ D1 W9 i, U5 ?% m$ u
XML and databases, web services! c9 K6 n0 e+ C
Semi-structured data, metadata 8 i" N( }$ S: R7 \) Je-commence1 q+ Q+ G4 F& J! `; G
# o, ^' p4 D9 ]9 u/ t: K" X D" i
2. Data warehouse and Data mining # H; m. S' Y8 D9 U& @: z# F+ NGrid/Parallel/distributed data warehousing 5 g# d% T, k2 Y% K+ A: PWeb/** data warehouses 2 e7 }% P9 F6 i3 o) m6 A; m; XData warehousing and the semantic web; V9 G& l J, @4 h
Data warehousing with unstructured data8 z% K/ O" U, ~- g
Integration of Data Warehousing, f" S$ c4 K: n6 A W5 g
Data and knowledge representation s" E3 K; n+ p+ m1 z, A/ f$ N
Languages and inte**ces for data mining 3 Z& u0 f* O3 z% xData integration and interoperability ; S7 G6 Q- C2 n; SData extraction, cleansing, transforming and loading - T W) N8 j3 c L- rData mining and information extraction 9 C" T. L/ C* t- o* S/ OKDD Process and Human Interaction; _$ A8 D3 J J I7 L' Z: X# F5 j7 h4 b
OLAP and Data Mining3 T# r0 Y8 l% J; b8 _
Parallel and Distributed Data Mining a! { e/ z: R; T o' A& N
Physical database design and performance evaluation( K% F3 c' f- q( t7 R6 P! V i
Query processing and optimization7 I% V; V$ n) ^& M% |! ~
Reliability and Robustness Issues2 r4 _/ v; ]( u: \) U i
Semantic web and ontology: F. g& Y) Q! y, q
Software Warehouse and Software Mining . v2 k. Z" V( k6 ]Social and mathematical statistics , {- x2 S$ ?& B# Y( J4 G4 dNovel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) 8 z8 Q. J* h# f! l
Developing a unifying theory of data mining 3 K$ n- J8 d/ j! O! V$ N
Mining sequences and sequential data + G) s/ n9 N M( nData pre-processing, data reduction, feature selection, and feature transformation - K. q' y* r* D! x# F& H% M/ ~1 B ~
Quality assessment, interestingness analysis, and post-processing / L7 j8 j4 _; `0 c, } e: T
Mining unstructured, semi-structured, and structured data 5 x; M( ~) {4 o- I3 p% m+ [; `5 ]Mining temporal, spatial, spatio-temporal data 9 r6 H0 O- i! V9 j$ h, SMining data streams and sensor data + J0 c. C3 i' X! q: ?+ r' DMining ** data* U* R- ]3 s; Z( m
Mining social network data * g6 c1 h" E8 s& j' I8 wHuman-machine interaction and visual data mining ' [6 W1 N- C# JData mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)- M/ W; ~) v' Y2 a
Knowledge Acquisition & Management0 q" N! p( w; c+ j3 Y2 R! d% k
Knowledge Modeling " U3 Q* Q& C) ^3 B# e3 l; l2 x& IKnowledge Processing 3 v6 r7 y7 F/ l- q$ w- |Integrated KDD applications and systems % q8 [8 g" c9 r! O
Business Process Intelligence 8 E: m& ~% O4 T3 N/ q* E6 vCluster Analysis and Knowledge Base system 0 R& f" L* `7 {9 I# \* c% l- MInformation systems technology, V$ n. ]% J. Y
Other related technology about data mining ( e0 P/ d# z4 w( c9 |# n' Q2 t: D R$ b; x/ h
3. Computer Science and Related Technology : k/ r; ?+ r5 i4 r* Q( j7 [
Image and signal processing 8 T3 L' `) i# O& _( T% S8 P, d8 [
Artificial Intelligence ; m" c+ p. E' \8 W: V
Software engineering / P4 p- F' b( c! \: r+ E' G. _& g
Systems Engineering 0 o* B- @. N. L7 d& T8 I$ t
Computer Graphics [' r* w# M! e$ ?: wComputer Application - P9 Y2 D$ f. d6 ?$ d! e* t
Control Technology 4 {; I: p! v9 z. A {7 c. hNetwork Technology 3 @( x; R% o) h
Network security - n6 D5 E% a6 Z/ i
Numerical and symbolic computation0 B% |; z7 k0 ~; d
Computer Modeling and Simulation6 Y3 g: b' z( H8 j6 Z: l
Communication Technology ! c/ M# |& q1 b7 P% C4 jAlgorithms and data structures 6 M9 M0 k7 Q! J& k( R! K& EComputer Education m. }: w5 |* N! M4 _
Other Advanced Technology8 d1 W" G3 o, \! g/ u7 f5 W- H
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====================================== : s' P) C8 v9 ODBTA2010会议联系秘书处# P- d. u5 c2 ^- Z
: Z6 N6 a0 b/ t: S# G' O. n邮件: dbta2010@vip.sina.com, info@icdbta.org U. G3 X6 P# c: l% E* m9 b5 g
电话: +86-151027691709 X- I) _1 ~8 P3 M5 p: f5 V
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