The 2nd International Workshop on Database Technology and Applications (DBTA2010) + c, H n+ E' w0 V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) N2 f4 A& y' C/ Z& w$ H
11月27-28,2010,武汉,中国 . b# e- q, |8 J( h% b1 chttp://www.icdbta.org/ - B; s* ]* O+ x$ f8 P2 f* \0 l' i; X3 T0 _" M$ P4 @0 D( [- S
论文提交日期: 2010年8月18日 # A! m' h% U" |论文录用通知日期: 2010年9月 16 日 + Z7 n, Y# C) m; U) `论文修订版本提交日期: 2010年9月22日 3 b8 O! a0 e2 r/ |3 j( s7 S论文注册日期: 2010年9月28日 9 M" w, T- M) g2 Y1 Q, N论文提交系统: http://www.icdbta.org/dbta2010/submission/2 n- o* N. P5 Q3 A8 x
会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc(只接受英文稿件)2 |# [* B( v* p7 C
IEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc (录用注册后提交), J d; u5 n3 S2 Z* u
3 ?) H0 y' f. W h h4 E: W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 U* n" o4 \0 N" A! }+ S/ M Z
* b) ~8 u u1 U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: - y; B5 _1 a) ?- M( c4 C5 _- ]& Y9 [" f( n, i. l$ v
1. Database and Related Issue ; g7 ?& Y1 F2 {$ Z# h
Temporal Data0 J5 f- r0 c% Y& F) I
Scientific Databases- }( a6 h$ H3 a6 j/ A \
Business database software0 F% N% [/ ?( k: e; y9 U
Computer data processing " {$ H( R0 K$ t# Y- [
Data processing services / L1 P- h0 ]( k X9 l: h4 C- OData processing supplies . X; K, z' q4 g$ e2 [
Data processing systems9 I9 r( J4 T7 ^# D; f5 v" z- P
Metadata Management' N/ s+ p; \8 l+ d: u0 B: H; N
Mobile Data and Information / @7 @, K/ U4 l** Databases) q! W/ f d; k/ t, v( M P0 F
WWW and Databases 3 y: ^& O, B$ j; e' j2 q- \2 x, `Workflow Management and Databases 0 J, Z5 t# q+ J5 G8 QXML and Databases ; [- V7 S; A( n& z4 e** Databases ) T c8 p6 e/ O& U7 {Data modeling and architectures 5 T% h5 Q/ c" a4 H5 c" lData streaming, data provenance and data quality6 t$ }; K+ s% ?8 j) \% H
Data Security, privacy, and data integrity " w, p7 [5 p- ?Web Data and the Internet$ ]! ]( b. S! A; m
XML and databases, web services ( Y7 D8 x- k- X1 u8 U) RSemi-structured data, metadata1 D" j4 a) K1 ~- P
e-commence ) J7 {7 d6 N$ ?6 ?4 |0 D- z$ _3 b. f: y) X7 j: m
2. Data warehouse and Data mining ' c* F( T! ^5 P P5 ZGrid/Parallel/distributed data warehousing 4 E: |, z0 D4 D+ F+ W2 E% w. F- b3 WWeb/** data warehouses; K4 D1 L. P7 Q" @! u+ L
Data warehousing and the semantic web8 `; V; q) ^+ o3 @! U6 c( e
Data warehousing with unstructured data % A; o: G: X3 s/ @+ rIntegration of Data Warehousing 7 |- E: ~- Z4 x: bData and knowledge representation , d: l" |3 B. g0 u8 F. ~Languages and inte**ces for data mining8 y8 u& @0 b' t2 ^- S8 g: K! r2 @/ K
Data integration and interoperability6 l$ g. D- n% m- M% q
Data extraction, cleansing, transforming and loading q/ Q" T! e/ \+ H
Data mining and information extraction( g3 O+ N i/ ~) ~+ B
KDD Process and Human Interaction % l* U! q( J9 R& BOLAP and Data Mining& g) b/ `6 V5 \5 L+ l
Parallel and Distributed Data Mining. E4 U8 O( i5 ~* T) o
Physical database design and performance evaluation+ ^, N% H% j$ i! `
Query processing and optimization' u% k3 y$ h" X# Q9 z
Reliability and Robustness Issues! |9 ?! `7 l$ Z. X* e
Semantic web and ontology ! P% b0 |( b; pSoftware Warehouse and Software Mining, f+ R( \& D' S$ P; s8 ~8 u
Social and mathematical statistics 4 W+ ^. [1 {0 s- X2 C, _Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) + V0 U8 Z4 S# p9 C4 BDeveloping a unifying theory of data mining " r9 A# |* L3 }" |) q$ QMining sequences and sequential data , C. `* n o9 c1 xData pre-processing, data reduction, feature selection, and feature transformation " x0 L9 y9 \ R# L* q$ ~
Quality assessment, interestingness analysis, and post-processing ! A# g5 {, ]% D; {Mining unstructured, semi-structured, and structured data0 M [3 `! H: v# m
Mining temporal, spatial, spatio-temporal data 1 D; o5 A4 o# s0 ~5 D" OMining data streams and sensor data; o* g2 I# c! M
Mining ** data. v! H2 S+ {* `
Mining social network data # u2 H i5 X+ y/ ?9 S$ cHuman-machine interaction and visual data mining ! {4 G1 y" M8 i/ B
Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)1 U6 F( a2 v$ T7 K* r
Knowledge Acquisition & Management , ]1 K7 ~) ^+ R; W* n! o# JKnowledge Modeling + i8 T1 h5 ^& S9 wKnowledge Processing. d+ u' Z+ p, I& q0 I0 R
Integrated KDD applications and systems ' W$ a# E* J" D! yBusiness Process Intelligence 8 G$ o" B0 M; j0 W. @* {4 PCluster Analysis and Knowledge Base system8 z% @' m% @1 C7 R6 E$ {
Information systems technology! P! o: t& {4 y/ o' Y/ P5 Q
Other related technology about data mining : r% v4 k3 u. w# p0 j# {2 b ( I" S& k' ^( ~8 l ]( r3. Computer Science and Related Technology 3 F$ B: N5 E1 w# h$ q3 s: xImage and signal processing ( c* Q, `3 J0 {# I0 b) Q& O+ gArtificial Intelligence 1 w6 H N" \; uSoftware engineering 1 r: C% g5 @9 p1 Q! \. ^/ I/ L% vSystems Engineering + [( e+ c6 W" B2 |9 gComputer Graphics ) z9 Q2 ], j/ T P" v- D0 b
Computer Application % V; e* [6 `! {' G% s$ C
Control Technology 3 M0 X, p: Z- S/ w( gNetwork Technology 6 u8 ^9 U- k" X# f/ ` J
Network security 9 i, O# H6 w3 D: j; a. ^
Numerical and symbolic computation3 y& u5 k$ z; ]/ d* t
Computer Modeling and Simulation 3 R: w2 Z/ o K1 f! G8 jCommunication Technology 2 n# E& f* ^3 {4 M. } BAlgorithms and data structures " v( B @& c z+ y: [Computer Education 5 g1 z6 A, j6 F: d" C3 X, D" ?6 ]Other Advanced Technology % q% q# t: d. h 5 g# M2 t) L; P====================================== 1 G K. j9 K% vDBTA2010会议联系秘书处 2 I( j4 q! g! Z; w) p* c# P0 c - V. I, g; g5 i邮件: dbta2010@vip.sina.com, info@icdbta.org ) J2 |" X, z0 p& Q电话: +86-151027691708 B$ t, v2 y+ t- i5 [7 Q% p, V
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