The 2nd International Workshop on Database Technology and Applications (DBTA2010) 1 o3 L2 d/ {( O( ?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)# [4 \( C" X' Z3 b9 v
11月27-28，2010，武汉，中国 ) ^0 T; Y7 `; e7 K4 e6 j http://www.icdbta.org/8 R* G s, A3 T3 L4 _$ S1 |% F1 U. I
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论文提交日期: 2010年8月18日/ v; y7 L4 V* [1 A+ X1 `" I! m
论文录用通知日期: 2010年9月 16 日 ; f$ V; Z& h" E! }( r) w论文修订版本提交日期: 2010年9月22日 * \0 d9 p8 p9 s+ t论文注册日期: 2010年9月28日: z) q$ M% q/ V9 H
论文提交系统: http://www.icdbta.org/dbta2010/submission/ 1 h# Z" |" R( N会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc（只接受英文稿件） B: j( T7 o' J' M1 K k2 l1 m2 m# D: mIEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc （录用注册后提交）/ p& M a- h) ^% w3 @: R' P
+ T: n* S. z# b# n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。 ( V, H7 U( K5 W1 y# D' `% E - Q! M% P. f% E ^; D; x$ S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：2 @% p, D( }0 w+ A# s
" ~7 T2 |; D7 p/ f, h- i1. Database and Related Issue 2 V# m2 F1 A& `9 a/ w7 ]1 pTemporal Data 5 x4 e4 h8 P( L8 H8 @) g& EScientific Databases) N' }) Z& E" F) c; w1 I9 \
Business database software$ a# A% P1 a) H; H8 u* P
Computer data processing ) U5 I9 ^- O( C4 n& @8 ]- k5 p) n A
Data processing services 6 x* }' a6 ?! T3 d2 f8 H2 `Data processing supplies & t& ]: T0 a P5 U. q/ Q. Q) }
Data processing systems : G3 y. e& I3 _" gMetadata Management ! Q* I9 L3 Y/ dMobile Data and Information2 K9 z& b: |! G# a+ \8 i5 H0 Q
** Databases ) m3 e: P* d' ?4 J2 a* ]/ yWWW and Databases 7 @* \/ n" @2 t# `" r6 c# C. ~6 `0 A wWorkflow Management and Databases 6 C9 q5 d/ k/ ?& k- y/ _, \9 ^' @: wXML and Databases. A! M" a0 E4 o9 m; d
** Databases6 r% i- D" g' V' f1 }$ M+ r
Data modeling and architectures3 Q0 _6 B8 b, \' t- M. D
Data streaming, data provenance and data quality8 Z, z: ^5 s5 o8 Q% p4 q% o( p
Data Security, privacy, and data integrity 9 X5 b0 w' ]. G4 s/ {( w
Web Data and the Internet, \, N2 P+ E; I) u6 Q+ L
XML and databases, web services 4 M. {, J( D4 M& ~Semi-structured data, metadata / h) [8 }: s# c) ~ qe-commence: v0 O, P, x5 S P! G
# X- Y6 F) A1 V% N7 o2. Data warehouse and Data mining5 v6 h% K' T' I1 j9 ]
Grid/Parallel/distributed data warehousing! T7 C# E! i) ]& T
Web/** data warehouses: O" p& @6 y* K* f$ y
Data warehousing and the semantic web/ C2 y% X1 ^4 t' R' q p
Data warehousing with unstructured data - z8 O, C- D; M0 W8 G7 yIntegration of Data Warehousing) L9 L% p) e W
Data and knowledge representation4 A6 U( @5 V. P* {, }# t
Languages and inte**ces for data mining / v+ s5 ?) j# S- Y3 KData integration and interoperability ( o, ]+ m0 p X2 M; S1 Y- sData extraction, cleansing, transforming and loading ' h$ N+ C/ r3 R8 y7 Q6 w/ G! oData mining and information extraction" u5 c8 _0 \% D3 r
KDD Process and Human Interaction ( J# C0 Z' F5 l. h. h1 x4 s" XOLAP and Data Mining : h# W3 v- }& D m$ BParallel and Distributed Data Mining 5 o5 Y$ [" M$ i, KPhysical database design and performance evaluation# ]. N8 A' ?: {
Query processing and optimization 2 b' l- G! T1 K, j# u4 w. [0 ]# CReliability and Robustness Issues- J! I- P8 G; T1 L
Semantic web and ontology 5 Y, F! u3 y0 r8 j$ x8 w) ]Software Warehouse and Software Mining 9 F+ }6 d* m+ sSocial and mathematical statistics8 S- W* S, }" m. d
Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) ' d8 I! e3 V+ k2 [; F, ADeveloping a unifying theory of data mining 7 _4 [ W( H4 I( s& r3 BMining sequences and sequential data# v& Q) l4 u: s+ e8 F8 k7 K! |
Data pre-processing, data reduction, feature selection, and feature transformation |% x0 J- |+ p U' D! K l" b
Quality assessment, interestingness analysis, and post-processing : J- h4 X! U3 x( J1 D
Mining unstructured, semi-structured, and structured data7 K. \2 Z- Z3 a0 n) X4 R5 ?
Mining temporal, spatial, spatio-temporal data 8 e# L8 j0 _8 G4 L3 [& c) O6 xMining data streams and sensor data- N |3 G& }; Y2 f, o4 h" o3 B
Mining ** data; j d/ x; x" c6 @
Mining social network data ' {3 N5 P+ S3 p9 v3 sHuman-machine interaction and visual data mining ! ^& ?$ _! p2 `Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc) $ c% Z" s" e! V3 \& [* \Knowledge Acquisition & Management9 _8 F" g6 a. p) F- \9 O8 q
Knowledge Modeling7 \- D& h+ m+ `' W5 U
Knowledge Processing ' m- _& i7 L) W3 L4 U$ {7 WIntegrated KDD applications and systems 5 W Y7 P7 ]9 f4 i' T/ L RBusiness Process Intelligence * o- C" V# ~4 ~: z$ j0 MCluster Analysis and Knowledge Base system% Q; N. U7 [; _
Information systems technology - s( k2 D: Q4 ]5 B6 qOther related technology about data mining 7 y1 ]/ C1 ?0 A2 |9 G# j$ X: k, ~% u
3. Computer Science and Related Technology A2 ~% ^) W$ M( W% WImage and signal processing 4 s1 ^- [" b: @/ a0 I
Artificial Intelligence 9 p g' u% r$ H8 x% `Software engineering ) |/ s+ P8 I7 B6 S: S" B/ hSystems Engineering , K) [" L+ S) ~' @# X
Computer Graphics . Z+ |- I5 M2 `5 y
Computer Application 9 F% `. s3 f! S" o, `Control Technology % ?6 P( Q, F# U4 E: F* D- S9 G: ~Network Technology - B+ `* s5 W" w& Z! ~3 G
Network security " i9 U/ x3 r/ N% sNumerical and symbolic computation 8 }7 _ l$ _9 d( e0 |: p! U4 gComputer Modeling and Simulation + Q" D# G+ h W# j$ lCommunication Technology 5 p/ _' s4 ^ \
Algorithms and data structures 8 G( G$ R/ e; {3 Q7 N. s. WComputer Education- V, @" V2 Z+ k3 A$ y# q% f) O' }5 w
Other Advanced Technology ' n" J! y5 |4 x# {: I9 q& Q4 J ( B' a9 }0 L7 p+ ~1 L5 i$ I====================================== % H$ n5 r ]$ Y% LDBTA2010会议联系秘书处# O, j- P) A2 R* R# H
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