Approaching Process Mining with Sequence Clustering

Oct 07, 2012

300 likes | 454 Vues

Share Presentation

Embed Code

Link

anne

Télécharger la présentation

Approaching Process Mining with Sequence Clustering

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

Data Mining: Clustering

Data Mining: Clustering. Cluster Analysis. What is Cluster Analysis? Types of Data in Cluster Analysis A Categorization of Major Clustering Methods Partitioning Methods Hierarchical Methods Grid-Based Methods Model-Based Clustering Methods Outlier Analysis Summary .

1.25k views • 45 slides

Process mining

Process mining. Prof.dr.ir. Wil van der Aalst Eindhoven University of Technology, Department of Information Systems, P.O. Box 513, 5600 MB Eindhoven, The Netherlands w.m.p.v.d.aalst@tm.tue.nl. from languages and systems to analysis .

1.13k views • 32 slides

Data Mining Techniques Clustering

Data Mining Techniques Clustering. Purpose. In clustering analysis, there is no pre-classified data Instead, clustering analysis is a process where a set of objects is partitioned into several clusters

506 views • 22 slides

Clustering in Data Mining

What is Data Clustering. Classification of objects into different groups.Objects in each subset share some common trait.Useful technique for Data Analysis and Data Mining.. Clustering Examples. Biology: clustering is used to group homologous (similar) DNA sequences into gene families. Market Re

467 views • 12 slides

Data Mining: Multivariate clustering & classification with R

Data Mining: Multivariate clustering & classification with R. Eric Feigelson Penn State. Summer School in Astrostatistics for Astronomers XII May 2016. Astronomical context. Astronomers have constructed classifications of celestial objects for centuries:

122 views • 8 slides

Process Mining

Process Mining. Thodoros Topaloglou Daniele Barone. Faculty/Presenter Disclosure. Faculty: Thodoros Topaloglou Relationships with commercial interests: Grants/Research Support: NSERC Discovery Grant (2006-12), PI

1.28k views • 23 slides

Data Mining: Multivariate clustering & classification with R

Data Mining: Multivariate clustering & classification with R. Eric Feigelson Penn State. 2014 Summer School in Statistics for Astronomers. Astronomical context. Astronomers have constructed classifications of celestial objects for centuries:

209 views • 8 slides

Sequence Clustering

Sequence Clustering. Reducing Search S pace in Protein and DNA /RNA S equence A nalysis Denis Kaznadzey, GBP. MGM Workshop September 26, 2011. Sequence clustering. To deal with a huge variety of individual ‘objects’:. Classify into groups of essentially similar objects

578 views • 27 slides

Sequence in Mining

Sequence in Mining. It Takes A Team. Jeff Price Cliffs Natural Resources United Taconite LLC Eveleth, MN. Objective.

338 views • 14 slides

7. Sequence Mining

7. Sequence Mining. Sequences and Strings Recognition with Strings MM & HMM Sequence Association Rules. Sequences and Strings. A sequence x is an ordered list of discrete items, such as a sequence of letters or a gene sequence Sequences and strings are often used interchangeably

288 views • 14 slides

Data Clustering and Mining

Data Clustering and Mining. Dexin Zhou – Bard College (Presenter) Ralph Abbey – North Carolina State U. Jeremy Diepenbrock – Washington U. at St. Louis Project Advisor: Dr. Carl Meyer Additional Advising: Dr. Amy Langville Graduate Assistant: Shaina Race. What is Data Clustering?.

435 views • 27 slides

Data Mining: Multivariate clustering & classification with R

Data Mining: Multivariate clustering & classification with R. Eric Feigelson Penn State. SCCC21 May 2014. Astronomical context. Astronomers have constructed classifications of celestial objects for centuries: Asteros (fixed stars) vs. planetos (roving stars) [Greece, >2Kyr ago]

272 views • 8 slides

Sequence Clustering

Sequence Clustering. COMP 790-90 Research Seminar Spring 2011. CLUSEQ. The primary structures of many biological (macro)molecules are â€œletterâ€ sequences despite their 3D structures. Protein has 20 amino acids. DNA has an alphabet of four bases {A, T, G, C} RNA has an alphabet {A, U, G, C}

464 views • 31 slides

Sequence Clustering

Sequence Clustering. Reducing Search S pace in Protein and DNA /RNA S equence A nalysis Denis Kaznadzey, Prokaryotic Super Program. MGM Workshop May 14, 2012. Sequence Clustering Outline. Classification of Sequences General Problem of Clustering Distance Measures

702 views • 43 slides

7. Sequence Mining

381 views • 23 slides

Sequence Clustering

Sequence Clustering. Reducing Search S pace in Protein and DNA /RNA S equence A nalysis Denis Kaznadzey, Prokaryotic Super Program. MGM Workshop January 30, 2011. Sequence Clustering Outline. Classification of Sequences General Problem of Clustering Distance Measures

726 views • 43 slides

Mining Sequence Data

Mining Sequence Data. Object. Timestamp. Events. A. 10. 2, 3, 5. A. 20. 6, 1. A. 23. 1. B. 11. 4, 5, 6. B. 17. 2. B. 21. 7, 8, 1, 2. B. 28. 1, 6. C. 14. 1, 8, 7. Sequence Data. Sequence Database:. Examples of Sequence Data. Element (Transaction). Event (Item).

632 views • 21 slides

DATA MINING WITH CLUSTERING AND CLASSIFICATION

DATA MINING WITH CLUSTERING AND CLASSIFICATION. Spring 2007, SJSU Benjamin Lam. Overview. Definition of Clustering Existing clustering methods Clustering examples Classification Classification examples Conclusion. Definition.

681 views • 49 slides

Data Mining: Multivariate clustering & classification with R

Data Mining: Multivariate clustering & classification with R. Eric Feigelson Penn State. Arcetri Observatory, April 2014. Astronomical context. Astronomers have constructed classifications of celestial objects for centuries:

197 views • 8 slides

Process mining

Process mining. At Rabobank. Frank van Geffen 19-9-2013. Outline. Introduction. Outline. Introduction My experience with process mining at Rabobank. Outline. Introduction My experience with process mining at Rabobank Paradigm shift of working with process mining. Outline.

559 views • 34 slides

Sequence Clustering

Sequence Clustering. COMP 790-90 Research Seminar Spring 2011. ApproxMAP. Sequential Pattern Mining Support Framework Multiple Alignment Framework Evaluation Conclusion. Inherent Problems. Exact match

191 views • 17 slides

More Related

Approaching Process Mining with Sequence Clustering

Approaching Process Mining with Sequence Clustering

Presentation Transcript

Data Mining: Clustering

Process mining

Data Mining Techniques Clustering

Clustering in Data Mining

Data Mining: Multivariate clustering &amp; classification with R

Process Mining

Data Mining: Multivariate clustering &amp; classification with R

Sequence Clustering

Sequence in Mining

7. Sequence Mining

Data Clustering and Mining

Data Mining: Multivariate clustering &amp; classification with R

Sequence Clustering

Sequence Clustering

7. Sequence Mining

Sequence Clustering

Mining Sequence Data

DATA MINING WITH CLUSTERING AND CLASSIFICATION

Data Mining: Multivariate clustering &amp; classification with R

Process mining

Sequence Clustering

Data Mining: Multivariate clustering & classification with R

Data Mining: Multivariate clustering & classification with R

Data Mining: Multivariate clustering & classification with R

Data Mining: Multivariate clustering & classification with R