Mining complex data ECML/PKDD 2007 third international workshop, MCD 2007, Warsaw, Poland, September 17-21, 2007 : revised selected papers /
This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007. The 20 revised full papers presented were carefully reviewed and selected; they present original results...
Corporate Authors: | MCD 2007 Warsaw, Poland) |
---|---|
Other Authors: | MCD 2007, Raś, Zbigniew., Tsumoto, Shusaku, 1963-, Zighed, Djamel A., 1955-, SpringerLink (Online service), ECML PKDD (Conference) |
Format: | eBook |
Language: | English |
Published: |
Berlin ; New York :
Springer,
2008.
Berlin ; New York : 2008. |
Physical Description: |
1 online resource (x, 264 pages) : illustrations. |
Series: |
Lecture notes in computer science ;
4944. Lecture notes in computer science. Lecture notes in artificial intelligence. LNCS sublibrary. Artificial intelligence. |
Subjects: |
LEADER | 07526cam a2201177 a 4500 | ||
---|---|---|---|
001 | 272309738 | ||
003 | OCoLC | ||
005 | 20240223121953.0 | ||
006 | m o d | ||
007 | cr ||||||||||| | ||
008 | 081117s2008 gw a ob 101 0 eng d | ||
019 | |a 232648554 |a 234257661 |a 488388877 |a 488862332 |a 781540566 |a 785781631 |a 964889364 |a 1035701760 |a 1051443739 |a 1084838670 |a 1167303484 | ||
020 | |a 9783540684169 | ||
020 | |a 3540684166 | ||
020 | |z 9783540684152 |q (print) | ||
020 | |z 3540684158 |q (print) | ||
035 | |a (OCoLC)272309738 |z (OCoLC)232648554 |z (OCoLC)234257661 |z (OCoLC)488388877 |z (OCoLC)488862332 |z (OCoLC)781540566 |z (OCoLC)785781631 |z (OCoLC)964889364 |z (OCoLC)1035701760 |z (OCoLC)1051443739 |z (OCoLC)1084838670 |z (OCoLC)1167303484 | ||
040 | |a GW5XE |b eng |e pn |c GW5XE |d CUS |d WAU |d CEF |d OCLCQ |d NJR |d STF |d BUF |d E7B |d LEAUB |d OCLCO |d OCLCQ |d A7U |d OCLCQ |d OCLCO |d OCLCA |d OCLCF |d BEDGE |d OHS |d OCLCQ |d OCLCO |d YDXCP |d IDEBK |d NUI |d OCLCQ |d OCLCO |d OCL |d OCLCO |d EBLCP |d OCLCQ |d OCLCO |d OCLCQ |d DGU |d OCLCQ |d UAB |d ESU |d OCLCQ |d VT2 |d OCLCA |d MERER |d OCLCQ |d QE2 |d U3W |d OCLCQ |d OCLCA |d WYU |d CNTRU |d OCLCO |d OL$ |d OCLCQ |d OCLCA |d ERF |d OCLCQ |d OCLCO |d OCLCQ |d OCL |d OCLCQ |d OCLCO |d OCLCL | ||
049 | |a COM6 | ||
050 | 4 | |a QA76.9.D343 | |
055 | 3 | |a QA75 |b .L38 no.4944 | |
060 | 4 | |a QA 76.9.D343 | |
082 | 0 | 4 | |a 004 |2 22 |
084 | |a 54.74 |2 bcl | ||
111 | 2 | |a MCD 2007 |d (2007 : |c Warsaw, Poland) | |
245 | 1 | 0 | |a Mining complex data : |b ECML/PKDD 2007 third international workshop, MCD 2007, Warsaw, Poland, September 17-21, 2007 : revised selected papers / |c Zbigniew W. Raś, Shusaku Tsumoto, Djamel Zighed (eds.). |
246 | 3 | 0 | |a ECML/PKDD 2007. |
246 | 3 | 0 | |a MCD 2007. |
260 | |a Berlin ; |a New York : |b Springer, |c 2008. | ||
264 | 1 | |a Berlin ; |a New York : |b Springer, |c 2008. | |
300 | |a 1 online resource (x, 264 pages) : |b illustrations. | ||
336 | |a text |b txt |2 rdacontent. | ||
337 | |a computer |b c |2 rdamedia. | ||
338 | |a online resource |b cr |2 rdacarrier. | ||
490 | 1 | |a Lecture notes in computer science, |x 0302-9743 ; |v 4944. |a Lecture notes in artificial intelligence. | |
490 | 1 | |a LNCS sublibrary. SL 7, Artificial intelligence. | |
504 | |a Includes bibliographical references and index. | ||
505 | 0 | |a Session A1 -- Using Text Mining and Link Analysis for Software Mining -- Generalization-Based Similarity for Conceptual Clustering -- Trajectory Analysis of Laboratory Tests as Medical Complex Data Mining -- Session A2 -- Conceptual Clustering Applied to Ontologies -- Feature Selection: Near Set Approach -- Evaluating Accuracies of a Trading Rule Mining Method Based on Temporal Pattern Extraction -- Session A3 -- Discovering Word Meanings Based on Frequent Termsets -- Quality of Musical Instrument Sound Identification for Various Levels of Accompanying Sounds -- Discriminant Feature Analysis for Music Timbre Recognition and Automatic Indexing -- Session A4 -- Contextual Adaptive Clustering of Web and Text Documents with Personalization -- Improving Boosting by Exploiting Former Assumptions -- Discovery of Frequent Graph Patterns that Consist of the Vertices with the Complex Structures -- Session B1 -- Finding Composite Episodes -- Ordinal Classification with Decision Rules -- Data Mining of Multi-categorized Data -- ARAS: Action Rules Discovery Based on Agglomerative Strategy -- Session B2 -- Learning to Order: A Relational Approach -- Using Semantic Distance in a Content-Based Heterogeneous Information Retrieval System -- Using Secondary Knowledge to Support Decision Tree Classification of Retrospective Clinical Data -- POM Centric Multi-aspect Data Analysis for Investigating Human Problem Solving Function. | |
520 | |a This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007. The 20 revised full papers presented were carefully reviewed and selected; they present original results on knowledge discovery from complex data. In contrast to the typical tabular data, complex data can consist of heterogenous data types, can come from different sources, or live in high dimensional spaces. All these specificities call for new data mining strategies. | ||
650 | 0 | |a Data mining |v Congresses. | |
650 | 0 | |a Database searching |v Congresses. | |
650 | 0 | |a Machine learning |v Congresses. | |
650 | 0 | |a Data mining. | |
650 | 0 | |a Artificial intelligence. | |
650 | 2 | |a Data Mining. | |
650 | 2 | |a Information Storage and Retrieval. | |
650 | 2 | |a Artificial Intelligence. | |
650 | 6 | |a Exploration de données (Informatique) |v Congrès. | |
650 | 6 | |a Bases de données |x Interrogation |v Congrès. | |
650 | 6 | |a Apprentissage automatique |v Congrès. | |
650 | 6 | |a Exploration de données (Informatique) | |
650 | 6 | |a Intelligence artificielle. | |
650 | 7 | |a artificial intelligence. |2 aat. | |
650 | 7 | |a Informatique. |2 eclas. | |
650 | 7 | |a Artificial intelligence. |2 fast. | |
650 | 7 | |a Data mining. |2 fast. | |
650 | 7 | |a Database searching. |2 fast. | |
650 | 7 | |a Machine learning. |2 fast. | |
655 | 2 | |a Congress. | |
655 | 7 | |a proceedings (reports) |2 aat. | |
655 | 7 | |a Conference papers and proceedings. |2 fast. | |
655 | 7 | |a Conference papers and proceedings. |2 lcgft. | |
655 | 7 | |a Actes de congrès. |2 rvmgf. | |
700 | 1 | |a Raś, Zbigniew. | |
700 | 1 | |a Tsumoto, Shusaku, |d 1963- |1 https://id.oclc.org/worldcat/entity/E39PCjH3T9Gg9Y4633fJ7MKbFq. | |
700 | 1 | |a Zighed, Djamel A., |d 1955- |1 https://id.oclc.org/worldcat/entity/E39PCjCChDj4HhJYhbCKj868BX. | |
710 | 2 | |a SpringerLink (Online service) | |
711 | 2 | |a ECML PKDD (Conference) |d (2007 : |c Warsaw, Poland) | |
776 | 0 | 8 | |i Print version: |a MCD 2007 (2007 : Warsaw, Poland). |t Mining complex data. |d Berlin ; New York : Springer, 2008 |z 9783540684152 |w (DLC) 2008926861 |w (OCoLC)227032535. |
830 | 0 | |a Lecture notes in computer science ; |v 4944. | |
830 | 0 | |a Lecture notes in computer science. |p Lecture notes in artificial intelligence. | |
830 | 0 | |a LNCS sublibrary. |n SL 7, |p Artificial intelligence. | |
907 | |a .b29611106 |b multi |c - |d 100215 |e 240320 | ||
998 | |a (3)cue |a cu |b 240227 |c m |d z |e - |f eng |g gw |h 0 |i 2 | ||
948 | |a MARCIVE Overnight, in 2024.03 | ||
948 | |a MARCIVE Comp, in 2022.12 | ||
948 | |a MARCIVE Over, 07/2021 | ||
948 | |a MARCIVE Comp, 2018.12 | ||
948 | |a MARCIVE Comp, 2018.05 | ||
948 | |a MARCIVE Comp, 2018.03 | ||
948 | |a MARCIVE Comp, 2017.10 | ||
948 | |a MARCIVE August, 2017 | ||
948 | |a MARCIVE extract Aug 5, 2017 | ||
994 | |a 92 |b COM | ||
995 | |a Loaded with m2btab.ltiac in 2024.03 | ||
995 | |a Loaded with m2btab.elec in 2024.02 | ||
995 | |a Loaded with m2btab.ltiac in 2022.12 | ||
995 | |a Loaded with m2btab.ltiac in 2021.07 | ||
995 | |a Loaded with m2btab.elec in 2021.06 | ||
995 | |a Loaded with m2btab.ltiac in 2018.12 | ||
995 | |a Loaded with m2btab.ltiac in 2018.06 | ||
995 | |a Loaded with m2btab.ltiac in 2018.03 | ||
995 | |a Loaded with m2btab.ltiac in 2017.10 | ||
995 | |a Loaded with m2btab.ltiac in 2017.08 | ||
995 | |a Loaded with m2btab.elec in 2016 | ||
995 | |a Loaded with m2btab.elec in 2016 | ||
995 | |a Loaded with m2btab.ltiac in 2016 | ||
995 | |a OCLC offline update by CMU | ||
999 | |e z | ||
999 | |a cue | ||
989 | |d cueme |e - - |f - - |g - |h 0 |i 0 |j 200 |k 240227 |l $0.00 |m |n - - |o - |p 0 |q 0 |t 0 |x 0 |w SpringerLink |1 .i150209174 |u http://ezproxy.coloradomesa.edu/login?url=https://link.springer.com/10.1007/978-3-540-68416-9 |3 SpringerLink |z Click here for access |