'Relational learning' diaporamas de présentation

Seminar: Statistical NLP

1.14k views • 89 slides

Seminar: Statistical NLP

904 views • 89 slides

Linking RFT to the Hexaflex: How basic principles apply to clinical issues and ACT techniques

803 views • 68 slides

Plain Text Information Extraction (based on Machine Learning )

Plain Text Information Extraction (based on Machine Learning ). Chia-Hui Chang Department of Computer Science & Information Engineering National Central University chia@csie.ncu.edu.tw 9/24/2002. Introduction. Plain Text Information Extraction

745 views • 60 slides

Mirrors and Crystal Balls A Personal Perspective on Data Mining

704 views • 60 slides

Plain Text Information Extraction (based on Machine Learning )

Plain Text Information Extraction (based on Machine Learning ). Chia-Hui Chang Department of Computer Science & Information Engineering National Central University chia@csie.ncu.edu.tw 9/24/2002. Introduction. Plain Text Information Extraction

606 views • 60 slides

Anna Atramentov Major: Computer Science Program of Study Committee:

481 views • 40 slides

2014 Curriculum

2014 Curriculum. ICD-10-CM Train the Trainer (for CPC-Is)

348 views • 34 slides

Mathematics Presentation

412 views • 17 slides

Predictive Semantic Social Media Analysis David A. Ostrowski

Predictive Semantic Social Media Analysis David A. Ostrowski System Analytics and Environmental Sciences Research and Advanced Engineering Ford Motor Company. Social media. Influential Sample of the web News driven CRM Real-time Less biased Unique opportunities for analytics.

248 views • 16 slides

Machine Learning for Information Extraction

Machine Learning for Information Extraction. Li Xu. Objective. Learn how to apply the machine learning concept to the application Learn how to improve the performance of the existed application by applying the machine learning algorithms. Introduction.

265 views • 15 slides

Conclusions

Conclusions. overview and survey from a logical / ILP perspective Distinction between Model-based: BN, PLPs, PRMs,BLPs,... vs. proof-based: SCFGs, SLPs, PRISM, ... Learning Settings: Learning from interpretations: PLPs,PRMs,BLPs Learning from entailment: SLPs, PRISM

172 views • 8 slides