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The 2nd International Workshop on Database Technology and Applications (DBTA2010)
, N$ Q+ W/ m3 ?0 E8 w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)
9 N9 p0 S+ P8 t4 p* r" Q11月27-28,2010,武汉,中国
4 y2 i }( K4 f6 r. K% N1 \9 @http://www.icdbta.org/
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论文提交日期: 2010年8月18日# H9 ^4 }, y) ]! u" s5 E3 E
论文录用通知日期: 2010年9月 16 日
) H4 H1 G8 u$ `, U7 T4 V论文修订版本提交日期: 2010年9月22日! E- I2 h3 o& K* ^& y
论文注册日期: 2010年9月28日6 h" y) P0 E- f U& R! J- Q, \
论文提交系统: http://www.icdbta.org/dbta2010/submission/
) w' E; W" a2 U' n: O" k! t会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc(只接受英文稿件); {* F5 _" ^) M1 J5 E& u/ H
IEEE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 B/ A( Y' j! _, i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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/ C3 W; [9 O7 |+ T! e- 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:. \' F M! K/ }+ E0 M
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1. Database and Related Issue 6 l. J& F' S" Y% b* ~6 |' L* w
Temporal Data3 n9 b' r3 L5 f5 y0 ]! O8 W
Scientific Databases
' t0 M; B4 [" F3 v0 x3 `+ _* Q0 ^Business database software
! U6 i! Z8 d# d* T5 C( eComputer data processing . p2 K- f& D. x+ ]# r- H
Data processing services
8 `0 b8 [- ?7 V1 lData processing supplies 9 U/ Q% `/ z" x, F
Data processing systems
. U" h- b$ z4 H5 Z# ?2 RMetadata Management
7 C( ?* b; R4 Q7 z5 i4 gMobile Data and Information
4 _- H- k; m; w! }, m* L( F% R** Databases: \+ V" H* p Y0 F" ^. A
WWW and Databases
/ S9 I" ]3 r4 S: n( Q, U5 C# ]Workflow Management and Databases( }+ ^" T" p# ?- }$ y
XML and Databases
; |8 ]5 d% n6 _- B** Databases) ^& m0 U8 B3 y2 T8 N* r, s
Data modeling and architectures8 [6 @5 y0 R; @! @( [
Data streaming, data provenance and data quality5 [7 A2 M" b% B, \* e7 K
Data Security, privacy, and data integrity ) [0 h4 V3 [& f+ b* |- a- _
Web Data and the Internet( J t# R2 J9 C6 N& c6 n
XML and databases, web services
3 B' V9 ]7 k4 e. b2 y4 W' S! |Semi-structured data, metadata ] V! y c: w3 U% k, h
e-commence- m$ Z J1 \- a* H0 _$ Z" w
# t1 {7 K7 H+ d; o' T7 a, ~+ j
2. Data warehouse and Data mining
t" S: _5 f2 \# r! e( W p3 gGrid/Parallel/distributed data warehousing+ p) {8 |; V7 C& `5 f, a
Web/** data warehouses
8 X( s9 h, D" Q! e L6 qData warehousing and the semantic web& I% {6 l6 ?3 }
Data warehousing with unstructured data
p& a5 c# w' q8 z4 t/ H0 |' GIntegration of Data Warehousing* A+ w8 c/ M x# h
Data and knowledge representation" r% @9 e# |& u2 g6 h9 N7 z7 W4 a
Languages and inte**ces for data mining
8 q! c) Y |0 q' ^3 s' V# a( tData integration and interoperability
, u9 s, I0 K9 v$ G5 `6 X/ fData extraction, cleansing, transforming and loading
7 t6 n+ N5 Y1 P# z: P' Q4 IData mining and information extraction. h% _4 C; f; Y' K
KDD Process and Human Interaction
; N) S6 Z& X% XOLAP and Data Mining
4 T* z9 D4 |$ @: j" n3 lParallel and Distributed Data Mining
* P5 f, M E: J! q( s' cPhysical database design and performance evaluation# E' e6 f5 z- h8 Z) z% S4 d) Y: S0 d
Query processing and optimization
7 x8 t- X. h; x" WReliability and Robustness Issues; _ _7 \$ E; d# c5 o
Semantic web and ontology
, S# U5 Z& w. e' D+ M" l2 Y( S1 XSoftware Warehouse and Software Mining" R9 N2 f6 w' U
Social and mathematical statistics0 [2 x3 L3 M) C2 k& [6 K
Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis)
. `3 l7 }) E( Z5 TDeveloping a unifying theory of data mining
% y5 s* o2 N l7 a0 t% YMining sequences and sequential data; T5 l3 a, K4 v7 A) Z1 n
Data pre-processing, data reduction, feature selection, and feature transformation . ~# v, T" _, C- J7 j" W1 s$ E
Quality assessment, interestingness analysis, and post-processing
. M) e9 ?$ e- P1 W5 @' dMining unstructured, semi-structured, and structured data
# r2 m, t' t- dMining temporal, spatial, spatio-temporal data
* N) o' P9 P, q4 w# r% |Mining data streams and sensor data2 p2 D" ^. G4 m- Z" J/ d; }) A
Mining ** data( r+ l$ k& ~' ?8 x' P
Mining social network data' _) |" n/ B- a; j' X$ B
Human-machine interaction and visual data mining
z% [1 o3 l9 W* C% `Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)/ e1 W1 D' e% d1 ?# s, _* ~
Knowledge Acquisition & Management, Y: s7 U# c5 P% ~6 }1 B) q+ q( Z
Knowledge Modeling# q# \+ `1 T5 q' X$ O2 Y T9 a5 Q4 f
Knowledge Processing1 t V9 L, `2 d; D U1 ~9 G! y1 y1 e5 i
Integrated KDD applications and systems
7 _" i9 T3 `* D. EBusiness Process Intelligence# T3 p+ y+ r" p- t
Cluster Analysis and Knowledge Base system6 }8 L/ `# ]& l Z
Information systems technology% r6 j. i5 G( G( `) g
Other related technology about data mining
1 ?4 p8 t9 ~) W* R# i& e
. j9 a: q4 h r3. Computer Science and Related Technology
8 i$ y% o0 H% M! g- e9 }! VImage and signal processing
, M" G7 E9 z: } {) T( mArtificial Intelligence ' F ^ s% p3 e9 {$ X! c2 @
Software engineering / M" o9 E5 F- {( e
Systems Engineering 8 k1 f3 k# {, ]) j# H
Computer Graphics " p0 F" @( c2 q
Computer Application 1 n$ {. T- Y! |
Control Technology . y1 v L0 w. e1 x
Network Technology
8 Y7 G6 e( j/ e" \( @Network security 5 T$ B. |2 }, }1 ^
Numerical and symbolic computation6 Y, F8 T1 X! h/ I7 N4 l! @
Computer Modeling and Simulation
! j( W3 l1 p/ f' _ ?8 sCommunication Technology
+ _- x# N" s4 g- ]Algorithms and data structures
4 f. b% f) c' _8 i% u5 _Computer Education4 X" }! G* T, j
Other Advanced Technology! Q( u6 \" [7 |7 f
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DBTA2010会议联系秘书处) ?7 a2 D2 S& g* d8 u/ _
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邮件: dbta2010@vip.sina.com, info@icdbta.org
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