Weakly supervised named entity classification Edouard Grave EECS Department UC Berkeley

Source URL: www.akbc.ws

• Statistical classification
• Learning
• Natural language processing
• Semi-supervised learning
• Supervised learning
• Information extraction
• Support vector machine
• Linear classifier
• Entity-relationship model
• Machine learning
• Statistics
• Artificial intelligence

K-CAP The 8th International Conference on Knowledge Capture October 7-10, 2015, Palisades, NY, USA 2

Source URL: www.k-cap2015.org

• Ontology
• Knowledge extraction
• Linked data
• Knowledge management
• Information
• Knowledge engineering
• Ethology
• Semantic Web
• Knowledge
• Information systems

A Scalable Data Transformation Platform – The Example of Data Anonymization Xiufeng Liu, Postdoc. Department of Engineering Management, DTU

Source URL: smart-cities-centre.org

• Formal sciences
• Data warehousing
• Business intelligence
• Database theory
• Extract
• transform
• load
• Data warehouse
• Database
• Data extraction
• Analytics
• Data management
• Technology
• Information technology management

Physica A – 300 www.elsevier.com/locate/physa Dictionary-based methods for information extraction

Source URL: samarcanda.phys.uniroma1.it

• Sequence
• Code
• Linguistics
• Notation
• Mathematics
• LZ77 and LZ78
• String

Rule-based Entity Recognition and Coverage of SNOMED CT in Swedish Clinical Text Maria Skeppstedt1 , Maria Kvist1,2 , Hercules Dalianis1 1 Dept. 2 Dept.

Source URL: lrec.elra.info

• Science
• SNOMED CT
• Systematized Nomenclature of Medicine
• International Health Terminology Standards Development Organisation
• Unified Medical Language System
• Named-entity recognition
• International Statistical Classification of Diseases and Related Health Problems
• Diagnosis codes
• Information extraction
• Medicine
• Medical classification
• Health

RLIMS-P Rule-Patterns Originate: January 24, 2005 _http://pir.georgetown.edu/iprolink/_ The following patterns are used in the rule-based phosphorylation information extraction system RLIMS-P (Rule-based LIterature Mi

Source URL: pir.georgetown.edu

Inside YAGO2s: A Transparent Information Extraction Architecture Joanna Biega, Erdal Kuzey, Fabian M. Suchanek Max Planck Institute for Informatics, Saarbrücken, Germany ABSTRACT

Source URL: resources.mpi-inf.mpg.de

• Information science
• Computational linguistics
• Knowledge representation
• Natural language processing
• Technical communication
• YAGO
• Extractor
• WordNet
• Information extraction
• Science
• Semantic Web
• Artificial intelligence

Paper Title (use style: paper title)

Source URL: www.aviarampatzis.com

• Text Retrieval Conference
• Search engine indexing
• XML-Retrieval
• Information extraction
• Precision and recall
• Relevance
• Tf*idf
• Query expansion
• Learning to rank
• Information science
• Information retrieval
• Science

Querying Probabilistic Information Extraction Daisy Zhe Wang∗ , Michael J. Franklin∗ , Minos Garofalakis† , and Joseph M. Hellerstein∗ ∗ University of California, Berkeley

Source URL: www.cise.ufl.edu

Preface This volume contains the papers presented at LD4IE2014: Linked Data for Information Extraction, held on October 20, 2014 in Riva Del Garda, in conjunction with the 13th International Semantic Web Conference (ISWC

Source URL: ceur-ws.org