The 2nd International Workshop on Database Technology and Applications (DBTA2010)7 a7 }- W2 w& B5 C
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) . M* N" _0 Y) B) c* t11月27-28,2010,武汉,中国 . i( |6 U7 { F' r7 j/ C http://www.icdbta.org/ 9 ]5 t1 l0 |4 w1 G; x; W, _2 c, W( O+ w. C/ Z. T
论文提交日期: 2010年8月18日 0 m, N% _& f* L. M/ \论文录用通知日期: 2010年9月 16 日 ! f" b2 Y# U7 `1 J/ n6 x论文修订版本提交日期: 2010年9月22日% {( f; r! C2 ]4 v0 s7 F7 x
论文注册日期: 2010年9月28日 " F5 ]3 z/ C5 E% K, W2 h论文提交系统: http://www.icdbta.org/dbta2010/submission/ $ {6 o. C1 _3 `会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc(只接受英文稿件) ( u) u: U* f% X, w, nIEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc (录用注册后提交)# m" ~* p- M2 ], {0 N0 k
$ ]* ]/ F% P6 d( a+ h5 M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。; A- |2 {7 A, g _; Y5 d+ n
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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: \% e" @. o. q$ ~0 V* J! w$ R! i: p! ~6 x5 @
1. Database and Related Issue * B5 F1 N% I' ETemporal Data 5 V; C$ Z( B! ?) l" nScientific Databases9 F7 y1 E. C- S V) u: H: g' Y3 u; e
Business database software$ k6 I8 A; @/ q- q* Y, w
Computer data processing 8 I& _; H( x6 T* P
Data processing services / o4 ^+ O; T( B' E; k9 R6 ^+ D
Data processing supplies ) H7 j" { `1 `! x: v4 M) p0 c
Data processing systems E# b. }- b- S5 w
Metadata Management* R: i9 T# |* Y {7 b7 A
Mobile Data and Information / v+ h1 g3 Z6 V* C0 \** Databases {- [; n) m8 y8 W& ?+ xWWW and Databases, H. d" G9 O1 ^% u
Workflow Management and Databases / c j+ V& c) U$ M8 e8 bXML and Databases7 r* o. t( a# \6 B6 o) w* R
** Databases 8 j' `& \% G8 x) P$ BData modeling and architectures9 B4 q6 i3 i( ^2 F
Data streaming, data provenance and data quality) I4 N& ^7 X! }* K( J$ K( L0 P# q
Data Security, privacy, and data integrity 7 P* }+ s( y5 c$ m( ~
Web Data and the Internet' [8 {0 b" Q2 D! E( _! K
XML and databases, web services' B# K% m9 ]! v) y/ _# n) ]: c& b
Semi-structured data, metadata $ l" ?% P9 `4 j" Y6 Ye-commence ' O2 |% a) z( t& F7 C0 k" {) q3 x4 K9 W$ R( [- N
2. Data warehouse and Data mining 7 o5 s: N2 \4 m7 o' pGrid/Parallel/distributed data warehousing! E4 Q( z$ f4 M3 X: y& i/ X& _
Web/** data warehouses + l& }4 P- e4 w6 v+ P: ]; f5 J |0 p( n: XData warehousing and the semantic web $ K0 Y( `, a1 k9 L mData warehousing with unstructured data 5 `( w( l% c8 a. U9 `, l) DIntegration of Data Warehousing2 Q8 u/ \/ [, D! f7 i" o x
Data and knowledge representation % ]1 w' q, s7 {Languages and inte**ces for data mining8 V- A( b* j" Y! Z, b( N
Data integration and interoperability* N5 H9 _/ A! M$ X$ z
Data extraction, cleansing, transforming and loading 5 D5 j( z7 Z) e4 s1 j1 s; `$ oData mining and information extraction ( q9 S7 Z/ U8 F7 bKDD Process and Human Interaction 7 F% a# d, g0 t! IOLAP and Data Mining & Z5 E- Q0 W; S' hParallel and Distributed Data Mining , Z. S5 I* r9 K( v: m% N: y0 nPhysical database design and performance evaluation; \$ ?+ D& p& `6 x; R0 N5 j+ y
Query processing and optimization2 M9 N' c Y, n9 s4 z
Reliability and Robustness Issues # C& ^. i7 n: _$ |Semantic web and ontology: B* {8 O1 |" T- B" i3 Q. P8 {
Software Warehouse and Software Mining6 C: r3 f) c9 d2 K
Social and mathematical statistics ; b; D& R/ e( f9 t; \" vNovel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) 9 j1 `9 y5 x! L; wDeveloping a unifying theory of data mining - A) y& `: r l& a9 X
Mining sequences and sequential data / E( c; ], e: [" \Data pre-processing, data reduction, feature selection, and feature transformation / m% ?' j2 O* u5 w" `! eQuality assessment, interestingness analysis, and post-processing ) g0 Z2 r, q k: W
Mining unstructured, semi-structured, and structured data0 E1 T1 \# T$ ~ D
Mining temporal, spatial, spatio-temporal data: W, k2 X) G! r" y' k% Y% l
Mining data streams and sensor data1 t+ g6 E# D8 n: [8 h5 `* ?$ r
Mining ** data- H& S% W2 G# p" S8 t
Mining social network data2 ~5 G ~$ S& K% a6 c5 R
Human-machine interaction and visual data mining 5 j& s6 j K3 U9 jData mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc) ) L N% O# W( zKnowledge Acquisition & Management 1 H' i9 G3 ^& s7 A5 O$ AKnowledge Modeling, J6 i3 q. x9 J O' J
Knowledge Processing ( Z& a6 {8 l; R. fIntegrated KDD applications and systems / q! j1 b( O6 x1 _! C6 n
Business Process Intelligence7 f' |8 z% y$ A- ^, P1 X4 a
Cluster Analysis and Knowledge Base system! l+ V* L+ x$ \ `
Information systems technology s" |( |# O/ N: L; a; z) y
Other related technology about data mining0 H4 r% S; _9 f
" y, n) f* C* y6 A9 e3. Computer Science and Related Technology 6 g: I, I; p. K5 k7 n) C
Image and signal processing 0 D. ~9 p$ y, ^% i$ b* aArtificial Intelligence : o# @& \' J$ f- \. ]: HSoftware engineering / l6 t( P& o5 O- @* b& CSystems Engineering + {1 G: ?1 m3 [) K- w+ \( l+ P
Computer Graphics ' U( N0 u3 o9 \2 ~) C( ^Computer Application 2 S8 J; o E- e. U+ N
Control Technology $ n" V" X, z @& lNetwork Technology 0 U$ \. G7 C; @" E) N" S5 t ^Network security ! I' {: `. b3 A, o7 D1 cNumerical and symbolic computation ' r5 e$ ^' d$ {4 |Computer Modeling and Simulation ( E) V$ N# t: W. v s$ BCommunication Technology 5 i$ C2 v5 f0 i+ R m( ]
Algorithms and data structures; Y+ r& Y& U+ b2 |! Q
Computer Education / W8 C0 U; _* t8 f% }Other Advanced Technology. ]6 S$ @) {* [" V/ J
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====================================== 1 o3 M6 H# `9 V1 E2 K* {DBTA2010会议联系秘书处 % C8 |+ K, y: s% t J2 ^' l8 m( v" f1 A# h3 p1 T
邮件: dbta2010@vip.sina.com, info@icdbta.org & U& P# j; J* F& y: n电话: +86-15102769170 7 D% A( ^2 F5 F$ F======================================