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[英文期刊] 第二届IEEE数据库技术与应用国际会议-DBTA2010

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发表于 2010-5-12 16:42 |只看该作者 |倒序浏览
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The 2nd International Workshop on Database Technology and Applications (DBTA2010)( I0 b% K. B( v# p1 q1 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)
7 A" z  ]5 ]% H) d: |11月27-28,2010,武汉,中国
4 i7 o) b3 m4 uhttp://www.icdbta.org/
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% z! u0 p/ P1 U3 _论文提交日期: 2010年8月18日3 K( }; Q5 k" v" e/ c
论文录用通知日期: 2010年9月 16 日
$ b6 `! z2 r) w- d( s+ W/ k/ a论文修订版本提交日期: 2010年9月22日3 T, F, q& V, ]. \9 M$ [
论文注册日期: 2010年9月28日( A0 A, B. ]$ `* K2 c: ~
论文提交系统: http://www.icdbta.org/dbta2010/submission/
" n& \9 i( d1 G1 f8 z会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc(只接受英文稿件)
4 r. C1 J. @; i' T6 r# @0 @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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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。: r& H4 F; N* B
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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:: _# ]' a9 s' t
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1. Database and Related Issue ; L5 y9 ?9 V4 v9 T
Temporal Data6 t& Y/ H0 x# I+ P( U( w
Scientific Databases$ m) F/ L- ^; m& B
Business database software) u2 k: L  P& s
Computer data processing ; `2 v2 q, Y$ G1 T& [$ {
Data processing services
, y% b3 d2 C- j* K' F! jData processing supplies
/ o& B2 A: t8 J. _8 l: p* IData processing systems' S" f7 `* T9 D% @  E, t
Metadata Management
! ]" @3 @9 p3 i* B" I6 VMobile Data and Information
" t5 Q$ F* F9 |4 D! o/ ?, K** Databases
. B0 F% K4 {& f% zWWW and Databases
/ f) r) D; M! Z5 A3 K) lWorkflow Management and Databases
8 q2 S  W/ g7 m# N# m6 s! b0 j9 f* XXML and Databases
4 N9 f. o% q( P3 \** Databases: `3 D' N9 V" V9 u5 ]- @
Data modeling and architectures- j2 ~0 }7 q& h  E: g
Data streaming, data provenance and data quality
2 ^5 S7 `+ `6 w* z) Q  |! gData Security, privacy, and data integrity 5 c% z+ ]& X, s6 B
Web Data and the Internet
* U/ k2 `) y4 B2 C- zXML and databases, web services4 N" B- P. X. L! \5 Q: E
Semi-structured data, metadata, S6 D: d/ j$ P" t4 H
e-commence
! i; m$ f4 d! U! L: X8 a# E* G/ E
2. Data warehouse and Data mining, \6 W. q( |& z7 ~) O
Grid/Parallel/distributed data warehousing% J. M/ L; M! X) K
Web/** data warehouses
) Y7 g  `/ r" ]: g2 @4 pData warehousing and the semantic web3 \8 e: K; r7 M2 S1 a: l
Data warehousing with unstructured data# a7 R  D, H% {( Q" {0 G
Integration of Data Warehousing7 T$ K7 S+ s( E9 B, @' N
Data and knowledge representation
6 R; k; c5 m& V6 z4 s  Z/ OLanguages and inte**ces for data mining. ?$ j# V" x. u1 |& }  @! k
Data integration and interoperability
' I; a1 C2 ^! I# vData extraction, cleansing, transforming and loading
$ X# }( {% a+ PData mining and information extraction
: x# Y' A. h" p5 Z* P8 yKDD Process and Human Interaction4 A5 v& f3 q1 F! y0 p
OLAP and Data Mining. H+ a5 D4 r! k# L7 n( |$ ?
Parallel and Distributed Data Mining
% r- i$ h0 |8 Z& T# x: C0 `! VPhysical database design and performance evaluation
4 ~7 N" W7 L+ y1 K5 ]7 EQuery processing and optimization/ ^% r2 j# J* i
Reliability and Robustness Issues
9 }1 F3 \; n8 G% x3 ]7 P. [Semantic web and ontology
$ u9 T# u+ p  s& ?Software Warehouse and Software Mining
$ ]+ v4 p& D$ d$ ZSocial and mathematical statistics, \% x# h8 |2 }5 Y( ]  Z+ f
Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) " ]7 R" W9 b8 U; F" q
Developing a unifying theory of data mining
' L4 \% c" s7 F& `; s* z% U9 IMining sequences and sequential data, l$ @. {  h3 |3 K
Data pre-processing, data reduction, feature selection, and feature transformation
3 E! U, C3 C% g8 j! YQuality assessment, interestingness analysis, and post-processing 1 v6 V- e9 T1 M4 x  A3 P
Mining unstructured, semi-structured, and structured data
* u! H, d! @  R, J# Z+ t- AMining temporal, spatial, spatio-temporal data
8 P9 A8 b4 b1 [5 D: uMining data streams and sensor data# v# m" j/ Z0 C  R1 T, u
Mining ** data
$ [3 Z- s0 a4 J- I9 X- c9 eMining social network data
( R: b# R) V1 Y1 D& t! d; ?! @Human-machine interaction and visual data mining . I  W% ^7 y. L6 l5 u1 Q0 a
Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc)
9 }/ ^1 m, ^, t2 E+ Y- fKnowledge Acquisition & Management
: I: V& |  n& C5 T" kKnowledge Modeling9 p6 _4 H  \/ l" @- D
Knowledge Processing- R- s4 F/ r% R9 s
Integrated KDD applications and systems 9 ^7 c) R' M; d
Business Process Intelligence
" a1 H, ~  ~! KCluster Analysis and Knowledge Base system
5 I6 m% @* _, h" n: p3 ZInformation systems technology6 k6 H  E8 }# }) s. a: M
Other related technology about data mining
/ Z4 k. s% p9 P
- H! A; f. w  ]1 D! E3. Computer Science and Related Technology , A) @+ q4 z/ r3 e! I
Image and signal processing
0 z/ [" b  w$ [4 iArtificial Intelligence 9 E( U- i4 ]+ _% x
Software engineering
6 }/ I2 ^2 h' J1 X) K' dSystems Engineering / F8 _: i  e4 L5 q. j
Computer Graphics $ L2 w1 w9 ~2 ?! ^( p8 b8 Z
Computer Application
; n( L5 ]1 F) O5 D' }6 j  LControl Technology
7 I3 z2 {& n. h7 HNetwork Technology & Q- s7 f0 V. W# b8 M+ I& v
Network security
, x  ]  u9 q$ ~, C  t0 ^Numerical and symbolic computation
/ `% n* j, O2 O$ w+ A; m/ BComputer Modeling and Simulation
0 w- d1 d: o/ @Communication Technology " o* @5 r5 j% v8 \) x9 o% f
Algorithms and data structures
6 R% b8 g  T& z! D5 I( IComputer Education
8 e' a0 z4 p( H& nOther Advanced Technology  x8 N9 E3 H& o0 l4 `
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======================================
0 o2 b. b5 z& H; O7 ?, M# o5 QDBTA2010会议联系秘书处
$ n' z9 E/ q% g1 J$ k0 {- D7 u, ]( t% p2 H
邮件: dbta2010@vip.sina.com, info@icdbta.org
$ e- b$ s! @) q电话: +86-15102769170
* j1 K2 l% Z" Y" v======================================
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