Ontology generation for large email collections

Authors:
Hui Yang;Jamie Callan
Affiliations:
Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA
Venue:
dg.o '08 Proceedings of the 2008 international conference on Digital government research
Year:
2008

Citing 10
Cited 6

Deriving concept hierarchies from text

Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Language processing technologies for electronic rulemaking: a project highlight

dg.o '05 Proceedings of the 2005 national conference on Digital government research
Building automatically a business registration ontology

dg.o '02 Proceedings of the 2002 annual national conference on Digital government research
Next steps in near-duplicate detection for eRulemaking

dg.o '06 Proceedings of the 2006 international conference on Digital government research
Near-duplicate detection by instance-level constrained clustering

SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Semi-automatic, data-driven construction of multimedia ontologies

ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
A bootstrapping approach for identifying stakeholders in public-comment corpora

dg.o '07 Proceedings of the 8th annual international conference on Digital government research: bridging disciplines & domains
Modular Ontology Design Using Canonical Building Blocks in the Biochemistry Domain

Proceedings of the 2006 conference on Formal Ontology in Information Systems: Proceedings of the Fourth International Conference (FOIS 2006)
Text2Onto: a framework for ontology learning and data-driven change discovery

NLDB'05 Proceedings of the 10th international conference on Natural Language Processing and Information Systems
Fully automatic construction of enterprise ontologies using design patterns: initial method and first experiences

OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, COA, and ODBASE - Volume Part II

Metric-based ontology learning

Proceedings of the 2nd international workshop on Ontologies and information systems for the semantic web
Creating tag hierarchies for effective navigation in social media

Proceedings of the 2008 ACM workshop on Search in social media
Abordagem não supervisionada para extração de conceitos a partir de textos

Companion Proceedings of the XIV Brazilian Symposium on Multimedia and the Web
Navigating within news collections using tag-flakes

Journal of Visual Languages and Computing
Constructing task-specific taxonomies for document collection browsing

EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Semantic relation extraction from legislative text using generalized syntactic dependencies and support vector machines

RuleML'13 Proceedings of the 7th international conference on Theory, Practice, and Applications of Rules on the Web

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a new approach to identifying concepts expressed in a collection of email messages, and organizing them into an ontology or taxonomy for browsing. It incorporates techniques from text mining, information retrieval, natural language processing and machine learning to generate a concept ontology. Nominal N-gram mining is used to identify candidate concepts. Wordnet and surface text pattern matching are used to identify relationships among the concepts. A supervised clustering algorithm is then used to further cluster the concepts. The experiments show that the approach is effective.