The 2nd International Workshop on Database Technology and Applications (DBTA2010) ' a7 e. c9 u3 |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)/ m8 Z. f7 y. A' n( `* w, o
11月27-28，2010，武汉，中国 4 q& n- n8 g7 K0 ihttp://www.icdbta.org// `; v" _2 f V2 c7 ]8 k
+ ]; o3 V; Y3 ^" }论文提交日期: 2010年8月18日4 i; T$ B+ q- N" g2 ]% A5 w4 K- l* y
论文录用通知日期: 2010年9月 16 日9 A; x6 j$ @; E! h
论文修订版本提交日期: 2010年9月22日 - A! H" M# L; b论文注册日期: 2010年9月28日+ V' |" \4 u c; o$ I* o
论文提交系统: http://www.icdbta.org/dbta2010/submission/ 8 ^3 S- N; r- M会议论文模版: http://www.icdbta.org/dbta2010/instruct8.5x11.doc（只接受英文稿件）' _+ X8 W: i! a9 c
IEEE会议论文版权表: http://www.icdbta.org/dbta2010/IEEECopyrightForm.doc （录用注册后提交）9 r. m+ x& d1 [( ]- `: s3 U- ^
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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。 1 ^" P7 s& T8 B- H# X- e+ J: l2 N) ]5 R: Y/ B
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：: U0 u2 g2 M/ b; d0 H
. y8 K8 H3 B' a! A1. Database and Related Issue - F* s! s. Q3 \$ F& ]4 P+ R/ A$ I
Temporal Data * t% Q6 m: o g0 c' ~9 XScientific Databases & P. H/ y8 r# ^6 e9 F+ IBusiness database software/ |$ h( o. R: l2 n/ L$ j5 T
Computer data processing + T q% b/ D/ W8 d4 aData processing services 5 T r; e5 s. cData processing supplies " a; B& t' T* B
Data processing systems% Q7 j) ?( ]3 ? D7 k- {
Metadata Management% R z3 c* y1 g- G1 {
Mobile Data and Information3 l' X; [) i( l; T9 e; p
** Databases t& h+ X6 e0 _+ r0 ?WWW and Databases 5 @+ B9 C# Q9 I8 t3 rWorkflow Management and Databases / I/ I' a- t( t+ L$ u# HXML and Databases ; e, D# s; ?3 H** Databases 9 a3 j" \' O$ tData modeling and architectures . W0 n% t- m! SData streaming, data provenance and data quality 5 c5 F. h1 d1 l! OData Security, privacy, and data integrity 1 w; v4 C! p; V3 Z3 y+ |Web Data and the Internet / r& \) o3 Z9 U# A6 }- KXML and databases, web services$ U( H# i& A2 ^- p7 H$ x" \: f. M
Semi-structured data, metadata1 k M- ?% z& R: y+ V- k0 }6 k
e-commence x: D5 ]; L. L2 m$ ~$ l1 F2 p- l; @7 T2 e# F4 _
2. Data warehouse and Data mining: \( n x1 T! }
Grid/Parallel/distributed data warehousing ; K0 e' p8 l, ^! rWeb/** data warehouses & s! I4 X+ t, {8 L+ ZData warehousing and the semantic web: l5 H" J# }; b- _8 G+ \
Data warehousing with unstructured data 0 K' A2 a5 b3 r; ]2 w/ rIntegration of Data Warehousing O* }$ x! A; ]+ YData and knowledge representation& ]7 E' P6 c! Z9 w4 G5 c/ M1 B
Languages and inte**ces for data mining! m. Q' J7 {1 m( ]1 L$ t
Data integration and interoperability9 g/ Z% O3 s1 y/ `% @; [' C
Data extraction, cleansing, transforming and loading 5 a c& o$ k' _2 ^, oData mining and information extraction 2 r k' N- k* o" _KDD Process and Human Interaction) u5 |- V: v# B7 T5 C
OLAP and Data Mining6 _5 f8 U! @- v! U9 F' @
Parallel and Distributed Data Mining: @% x6 f2 F3 x
Physical database design and performance evaluation0 t6 d9 S8 L! L* [7 o7 M
Query processing and optimization7 U0 u; n' \; m4 e$ u
Reliability and Robustness Issues 8 P. C$ E/ O# H$ v+ bSemantic web and ontology5 L" n8 T4 O7 @0 D4 d2 C. M
Software Warehouse and Software Mining( b. k/ }- ?, Q4 m1 L$ U
Social and mathematical statistics , F+ w9 G" I+ a+ y4 ?+ N" G; w! eNovel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) 7 D" h+ D; _2 H; c" `2 I8 L
Developing a unifying theory of data mining 8 F9 h0 a5 x" l
Mining sequences and sequential data- a, {/ x$ |3 P# g' {
Data pre-processing, data reduction, feature selection, and feature transformation % m% p" v: n" u9 f; s6 p5 kQuality assessment, interestingness analysis, and post-processing & l- Z" Z% H7 h0 C6 @. sMining unstructured, semi-structured, and structured data; n1 l4 G, N; l3 x1 @0 w
Mining temporal, spatial, spatio-temporal data ! W7 W3 Z$ ^& T7 SMining data streams and sensor data# S) N, o7 ]: }; d# U
Mining ** data 4 O# h' ] O% B7 iMining social network data # v P7 p9 d; `Human-machine interaction and visual data mining % \& p) y# L9 g6 P1 r2 E* W
Data mining applications (bioinformatics, E-commerce, Web, intrusion/fraud detection, finance, healthcare, marketing, telecommunications, etc) ; V |9 S& U& J B, L8 ?( KKnowledge Acquisition & Management; O7 |* a5 R6 B/ M5 w
Knowledge Modeling 7 h/ O1 i% d2 I2 e1 sKnowledge Processing, f2 m$ o- m( |- E
Integrated KDD applications and systems 3 z0 k' v1 [' s* q
Business Process Intelligence! ]2 o+ R8 X& z
Cluster Analysis and Knowledge Base system+ ?: D! V" P5 X3 n
Information systems technology! J8 G o0 R5 p) ]* { D) |
Other related technology about data mining 5 y* V J2 k, `. T7 R L, E+ Z8 `& ?( y+ q* X0 b
3. Computer Science and Related Technology ' T3 C, R: T6 B+ D( }1 A8 ~Image and signal processing 0 i) r8 ^ ]/ `+ W. z' p% y% h6 V1 SArtificial Intelligence # P. f$ {) W# j$ L v( XSoftware engineering 4 d& b" X& z' i8 w4 A
Systems Engineering ; t+ L3 `7 y, U4 t" SComputer Graphics , r4 F) | r- l8 }, }" h
Computer Application , @1 w1 A: N) s
Control Technology 2 f- F6 z2 M' z8 a8 W% y
Network Technology $ C' u1 b3 D6 W/ f# L/ ]
Network security * @3 M8 l$ I `; w
Numerical and symbolic computation8 T/ {- f2 e5 }
Computer Modeling and Simulation/ r6 j" L3 B. h% u; a
Communication Technology 6 h: B- i0 G* f# d( A4 V5 @! T" S
Algorithms and data structures# l5 y+ h+ P; O! n, R
Computer Education' p) h. t/ \& k2 }) `$ h
Other Advanced Technology J, i" G5 @) r
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发表于 2010-5-4 16:05
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发表于 2010-5-9 13:35
