Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
WordNet: a lexical database for English
Communications of the ACM
Text mining: finding nuggets in mountains of textual data
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Ontology Learning for the Semantic Web
Ontology Learning for the Semantic Web
Multipass algorithms for mining association rules in text databases
Knowledge and Information Systems
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Knowledge Discovery and Measures of Interest
Knowledge Discovery and Measures of Interest
OntoSeek: Content-Based Access to the Web
IEEE Intelligent Systems
Text Mining at Detail Level Using Conceptual Graphs
ICCS '02 Proceedings of the 10th International Conference on Conceptual Structures: Integration and Interfaces
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Mining Generalized Association Rules
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Sampling Large Databases for Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Selecting the right interestingness measure for association patterns
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
From a children's first dictionary to a lexical knowledge base of conceptual graphs
From a children's first dictionary to a lexical knowledge base of conceptual graphs
CLOSET+: searching for the best strategies for mining frequent closed itemsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
A simple rule-based part of speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
A new statistical parser based on bigram lexical dependencies
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Mining Generalized Substructures from a Set of Labeled Graphs
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Automatic construction of a hypernym-labeled noun hierarchy from text
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
DILS '08 Proceedings of the 5th international workshop on Data Integration in the Life Sciences
An Intelligent System for Semantic Information Retrieval Information from Textual Web Documents
IWCF '08 Proceedings of the 2nd international workshop on Computational Forensics
Acquiring Semantic Relations Using the Web for Constructing Lightweight Ontologies
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Building associated semantic overlay for discovering associated services
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Ontology learning from text: A look back and into the future
ACM Computing Surveys (CSUR)
A distributed recommender system architecture
International Journal of Web Engineering and Technology
Mining Frequent Generalized Patterns for Web Personalization in the Presence of Taxonomies
International Journal of Data Warehousing and Mining
Learning a Lightweight Ontology for Semantic Retrieval in Patient-Centered Information Systems
International Journal of Knowledge Management
Discovering interesting information with advances in web technology
ACM SIGKDD Explorations Newsletter
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Traditional text mining techniques transform free text into flat bags of words representation, which does not preserve sufficient semantics for the purpose of knowledge discovery. In this paper, we present a two-step procedure to mine generalized associations of semantic relations conveyed by the textual content of Web documents. First, RDF (Resource Description Framework) metadata representing semantic relations are extracted from raw text using a myriad of natural language processing techniques. The relation extraction process also creates a term taxonomy in the form of a sense hierarchy inferred from WordNet. Then, a novel generalized association pattern mining algorithm (GP-Close) is applied to discover the underlying relation association patterns on RDF metadata. For pruning the large number of redundant overgeneralized patterns in relation pattern search space, the GP-Close algorithm adopts the notion of generalization closure for systematic overgeneralization reduction. The efficacy of our approach is demonstrated through empirical experiments conducted on an online database of terrorist activities.