标题: 第二届IEEE数据库技术与应用国际会议-DBTA2010 [打印本页] 作者: power2010 时间: 2010-5-12 16:42 标题: 第二届IEEE数据库技术与应用国际会议-DBTA2010 The 2nd International Workshop on Database Technology and Applications (DBTA2010). E1 S4 c& |( o5 S2 I0 f
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) 6 R3 `3 E4 B) r& [11月27-28，2010，武汉，中国 9 c7 N$ j# y% {. p http://www.icdbta.org/$ G+ a8 k& B; z2 a" H; d
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论文提交日期: 2010年8月18日0 w6 {, n# K' n* E* T+ n
论文录用通知日期: 2010年9月 16 日 # i: Y- ^& V* c论文修订版本提交日期: 2010年9月22日. P. h! V6 k E$ h$ L9 f! O
论文注册日期: 2010年9月28日* {& I, Q C+ f9 ^6 f9 `
论文提交系统: http://www.icdbta.org/dbta2010/submission/ 7 g7 K# q! c# Z' p' y会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc（只接受英文稿件）; [: Q; \( _! h- @# R1 Y2 g/ l
IEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc （录用注册后提交）1 d }4 ^# O+ n0 o6 `2 R# D5 ]
- M- R1 ?5 \0 `1 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。9 {7 |4 a& o$ C6 ~/ t+ q* O }; x% 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： % k4 b6 s4 ~; Q& {$ M, u0 _; C2 a! d; w
1. Database and Related Issue 6 J; [/ @0 [* Z/ Q9 T5 I+ m' [
Temporal Data % _+ c5 l2 f% ~" ]' G, k# LScientific Databases, ?# B: C; W: }/ i3 g' H, ^/ Z4 I
Business database software + @( k. I0 n: j3 D0 g) VComputer data processing ! T/ v7 `, C H# k$ t6 IData processing services $ k" c2 a4 N$ g8 ]3 o$ D) Z' _
Data processing supplies . R- ^1 r1 k9 h/ i' H
Data processing systems; S& n' j; j# d
Metadata Management . C4 ^7 S+ ?& }; S MMobile Data and Information 8 s& ^2 s5 x* A4 d& T** Databases / h; v, C) q) R9 [WWW and Databases+ j% {* C# ]" C+ @" ^, `$ O
Workflow Management and Databases # O1 R' i6 {& U; nXML and Databases 2 z7 f1 F+ `* v3 Q' K* ]) J** Databases ' S$ @+ A" @7 V1 x! SData modeling and architectures 9 f; n" d" c5 o# y, pData streaming, data provenance and data quality0 C1 J4 O' e0 J M
Data Security, privacy, and data integrity $ s; s/ D1 M. |! a1 E& R
Web Data and the Internet 9 b, K* k" U( d7 p' G/ p) [XML and databases, web services 0 s! F9 }3 h/ }- I) E8 `0 USemi-structured data, metadata # {/ s3 G/ x# w- i% Ee-commence5 m, M0 ^+ w f1 s s
- v' w* k4 X' k8 h/ s4 Y i6 ~) h2. Data warehouse and Data mining9 T( v: _+ b8 w5 }( I8 [
Grid/Parallel/distributed data warehousing " O, {; I8 t1 ?0 lWeb/** data warehouses ( z6 p. D, x/ N% M) B- DData warehousing and the semantic web 7 E) S/ L0 h: _Data warehousing with unstructured data " |& V! a8 z0 o" t6 i9 ^Integration of Data Warehousing% P$ c; _" Y! ^) k
Data and knowledge representation6 R, f/ G3 k! t
Languages and inte**ces for data mining) V- |2 C; }- u2 e1 E& X+ [' Z& R
Data integration and interoperability 6 ?8 j7 Y. d6 I& d0 WData extraction, cleansing, transforming and loading % f3 F9 i8 _& t5 [, K. p8 dData mining and information extraction& q8 O! m3 I8 E
KDD Process and Human Interaction ) z/ P/ Z$ J2 J- c- `+ e: ~OLAP and Data Mining + O: W. i; {: @* m0 P% m8 w: hParallel and Distributed Data Mining 8 T; k* u; J% N! G7 SPhysical database design and performance evaluation ( b4 S# g2 Y; o* j! p) fQuery processing and optimization! d- a. \# g* b- G W
Reliability and Robustness Issues2 ^# G- q( \; o& g$ K8 Z
Semantic web and ontology; }9 Y9 M [: I, [4 X& Y
Software Warehouse and Software Mining ! |0 m P$ q; ]$ d0 jSocial and mathematical statistics, |( g E* F* H; H6 s
Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) + h7 ]# J2 S7 ?, W/ n- s
Developing a unifying theory of data mining % X% H5 L+ X* J9 A! j" s
Mining sequences and sequential data% J* k5 ?; H% w
Data pre-processing, data reduction, feature selection, and feature transformation # _, o4 V( q! [- @) nQuality assessment, interestingness analysis, and post-processing : @8 D4 e; p- `2 {
Mining unstructured, semi-structured, and structured data ) d+ e' ~: Y. J/ ~Mining temporal, spatial, spatio-temporal data : q g& U1 R6 s% p7 D3 G1 l0 cMining data streams and sensor data 8 g# E8 `' `1 t) v: ]4 RMining ** data8 h E3 c S" h$ a1 n% O
Mining social network data& W* {, b9 Y: |3 U, d3 @
Human-machine interaction and visual data mining - `7 G6 v, I7 {$ W6 Z
Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)" L: p/ ~: i& ~) ]3 k# B
Knowledge Acquisition & Management* M' \: k, q1 s
Knowledge Modeling# b& p5 t. k) G9 z$ l: c6 T+ P
Knowledge Processing % Q$ D9 F a! X& I8 uIntegrated KDD applications and systems 5 M: _: l/ O; t2 x6 k$ r
Business Process Intelligence& k% C" ^" p1 Q, k3 c, `
Cluster Analysis and Knowledge Base system; Z% |; X c) d F1 L1 v' J
Information systems technology, W3 d0 t! E. C* T" C
Other related technology about data mining( J$ p8 e" K1 n k z3 ^( Q
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3. Computer Science and Related Technology " e& y6 @2 O% {* F4 h; c- k9 Z$ M
Image and signal processing 7 `$ Z' p% M0 O2 s7 d7 t
Artificial Intelligence d. ?6 W9 v; @- e1 |3 g
Software engineering % s2 E: f- w; @4 u3 c, lSystems Engineering " l, J5 c9 F# z$ h8 V' }# _7 n
Computer Graphics * x2 Q) I9 Y% l8 j: N1 E! r, V
Computer Application 7 L, Q- t$ i; P
Control Technology : n, g/ i' Y1 Z6 a D) V- M1 A# H
Network Technology * }5 @# _0 B. ^' Q& R' T/ SNetwork security : Q! i# G8 U6 K" {Numerical and symbolic computation 7 m+ m; }- B1 C% U. u1 l- GComputer Modeling and Simulation 2 Y6 Y X) ^: v1 r7 fCommunication Technology 8 U) a" l; U6 i* ~Algorithms and data structures 3 G& F7 ~% A2 v1 wComputer Education$ T" F }* B5 v: R, K
Other Advanced Technology # J) j4 H! d- B6 k8 n! Z 3 {; a3 G) J4 a+ M! @+ @) `2 T% N====================================== 6 W: Q- ^& z Y$ f( w9 s cDBTA2010会议联系秘书处4 N" e2 j. V/ u/ p