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Discovery of emerging design patterns in ontologies using tree mining
2018
Semantic Web Journal
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To the best of our knowledge, this is the first method for automatic discovery of emerging design patterns in ontologies. ...
We describe our tree-mining method for identifying the emerging design patterns. ...
This work is also supported in part by grants GM086587 and GM103316 from the US National Institutes of Health. ...
doi:10.3233/sw-170280
pmid:30505251
pmcid:PMC6261490
fatcat:fayk77sxmbdobbiere7i42ke34
Editorial for the special issue of knowledge discovery and management in engineering design and manufacturing
2008
Journal of Intelligent Manufacturing
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Knowledge discovery and management using various advanced techniques, e.g. data\text\web\multimedia mining, computational neuroscience, ontology, and corporate search engine, in engineering design and ...
This Special Issue is therefore dedicated to innovative, state-of-the-art research, technology development and applications of knowledge discovery and management in the broad context of design and manufacturing ...
"A Product Design Ontology for Enhancing Shape Processing in Design Workflows" by Catalano, Camossi, Ferrandes, Cheutet and Sevilmis, describes their efforts in building and using a product design ontology ...
doi:10.1007/s10845-008-0209-y
fatcat:q6elkxqu2rfgdeupwj3qn4jole
Mining Substructures in Protein Data
2006
Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)
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This has given rise to the development of many tree mining algorithms which can aid in structural comparisons, association rule discovery and in general mining of tree structured knowledge representations ...
Mining frequent substructures from tree databases is an important task and it has gained a considerable amount of interest in areas such as XML mining, Bioinformatics, Web mining etc. ...
Many powerful tree mining algorithms have been developed to aid in structural comparisons, association rule discovery and in general, for mining of tree structured knowledge representations. ...
doi:10.1109/icdmw.2006.114
dblp:conf/icdm/HadzicDSCT06
fatcat:7ebzkdbbnvg2pd7uiqhxhbbqai
Mining Patterns with Domain Knowledge: A Case Study on Multi-language Data
2012
2012 IEEE/ACIS 11th International Conference on Computer and Information Science
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This paper proposes a new method for mining patterns over multi-language data, through the use of the D 2 FP-Growth algorithm and a language constraint, both defined in the context of the referred framework ...
Multi-language data impairs the application of mining techniques in a generalized form, since language remains an impenetrable barrier. ...
In particular, the D 2 PM (Domain Driven Pattern Mining) framework [1] introduces domain knowledge into the mining process through an ontology and makes use of constraints to focus the discovery according ...
doi:10.1109/icis.2012.70
dblp:conf/ACISicis/AntunesB12
fatcat:yhnmalwdp5hmbb4neikxtvhd5i
Data Mining, a Tool for Systems Biology or a Systems Biology Tool
2009
Journal of computer science and systems biology
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Furthermore, ontological resources are not designed to support text mining solutions, in the sense that ontological terms fit the demands of a natural language processing system. ...
The growth is noticeable after 2002, in particular, where the words "systems biology", "networks" and "gene ontology" emerge in the top ten most-used keywords. ...
doi:10.4172/jcsb.1000034e
fatcat:it7fvvc5zjbsvaz5io7dp2fy74
Ontology-Based Meta-Mining of Knowledge Discovery Workflows
[chapter]
2011
Studies in Computational Intelligence
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Section 3 gives a detailed description of dmop, while Section 4 introduces a novel method for ontology-based discovery of generalized patterns from data mining workflows. ...
of data miners embodied in the data mining ontology and knowledge base. ...
The advent of ontology languages and tools for the Semantic Web gave rise to a new generation of data mining ontologies, the majority of which are aimed at the construction of workflows for knowledge discovery ...
doi:10.1007/978-3-642-20980-2_9
fatcat:lhhpaisl5jhwjkqc5xdtpwskci
Word Sense Disambiguation for Ontology Learning
2013
Americas Conference on Information Systems
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Motivated by the large volume and richness of user-generated content in social media, this research explores the role of social media in ontology learning. ...
The research is in progress toward conducting a formal evaluation of the social media based method for WSD, and plans to incorporate the WSD routine into an ontology learning system in the future. ...
Data mining approaches are also utilized in relationship discovery. ...
dblp:conf/amcis/WimmerZ13
fatcat:nrcti3262ndd7hxp4qi2k76kyi
Automatic Extraction of Structurally Coherent Mini-Taxonomies
[chapter]
2008
Lecture Notes in Computer Science
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In this paper we demonstrate an automatic approach for emergent semantics modeling of ontologies. ...
We consider large sets of domain specific schemas as trees and apply frequent sub-tree mining for extracting common hierarchical patterns. ...
To further benefit from tree mining, we are going to use the automatically extracted mini-taxonomies for the discovery of n:m complex mappings in context of research described in [8] . ...
doi:10.1007/978-3-540-87877-3_25
fatcat:mowyc77zizh6nmpkyvkq3xnbae
Semantics and knowledge grids: building the next-generation grid
2004
IEEE Intelligent Systems
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We attempt to forecast the evolution of computational grids into what we call the next-generation grid, with a particular focus on the use of semantics and knowledge discovery techniques and services. ...
Although we can imagine larger and more powerful databases and data warehouses in which to store data, humans or programs will access only a small portion of it. ...
We thank those working in the knowledge grid research team: Carmela Comito, Antonio Congiusta, Carlo Mastroianni, Andrea Pugliese, Paolo Trunfio, and Pierangelo Veltri. ...
doi:10.1109/mis.2004.1265886
fatcat:m27hc2bn4bagrgbjcepiqiv3dm
MS-Analyzer: preprocessing and data mining services for proteomics applications on the Grid
2007
Concurrency and Computation
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In Section 4 we describe the architecture and functions of the proposed MS-Analyzer system. In Section 5 we present the Ontology-based Service Discovery system used in MS-Analyzer. ...
and an ontology-based workflow designer. ...
Finally, distributed data mining environments, such as the Discovery Net [15] or the emerging Knowledge Grids [6, 16] , although providing support for the entire knowledge discovery process, do not ...
doi:10.1002/cpe.1144
fatcat:2rvc3tuwpbcglexcirkoq7leva
Guest Editors' Introduction: Special Issue on Mining Biological Data
2005
IEEE Transactions on Knowledge and Data Engineering
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Mining frequent trees is very useful in bioinformatics applications. The first paper, "Efficiently Mining Frequent Trees in a Forest: Algorithms and Applications" by Mohammed J. ...
M INING biological data is an emerging area of intersection between data mining and bioinformatics. ...
doi:10.1109/tkde.2005.128
fatcat:o3vmjyzy3ncplknsce52diieo4
Towards a semantic framework for an integrative description of neuroscience patterns and studies: a case for emotion-related data
2009
Studies in Health Technology and Informatics
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systems used, as well as, the emerging neuro-physiological patterns found, may facilitate an integrative view of neuroscience theories. ...
To this end, the current piece of work aims to provide a global theoretical framework using ontologies and semantic rules to describe neuroscience studies. ...
To this end, ontologies may offer an attractive solution for the semantic description of neuroscience patterns and studies, and, therefore, some efforts have slowly but surely emerged in literature. ...
pmid:19745322
fatcat:bby4z3migzamxngxpo34jmuxp4
Automating Knowledge Discovery Workflow Composition Through Ontology-Based Planning
2011
IEEE Transactions on Automation Science and Engineering
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The second directly queries the ontology using a reasoner. The proposed approach was tested in two use cases, one from scientific discovery in genomics and another from advanced engineering. ...
Our methodology consists of two main ingredients. The first one is defining a formal conceptualization of knowledge types and data mining algorithms by means of knowledge discovery ontology. ...
We built upon the definitions of core knowledge discovery concepts presented in [5] in designing the core parts of the ontology, namely the concepts of knowledge, representation language, pattern, dataset ...
doi:10.1109/tase.2010.2070838
fatcat:rxfbnxy4d5aurgknuslsjj32ja
Data Warehousing and Knowledge Discovery: A Chronological View of Research Challenges
[chapter]
2005
Lecture Notes in Computer Science
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Pattern discovery and event sequence mining has emerged as a new field of interest while data semantics became an increasingly important issue. ...
The most commonly used techniques in data mining and knowledge discovery in the late 1980s and early 1990s are artificial neural networks, decision trees, genetic algorithms, nearest neighbourhood, and ...
doi:10.1007/11546849_52
fatcat:sdcervokrzasvanqlcnbp4jsp4
Frequent Pattern Mining and Current State of the Art
2011
International Journal of Computer Applications
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Identifying the association rules in large databases play a key role in data mining. ...
General Terms Data Mining, Market Basket Analysis, Itemset. ...
of pattern discovery in sensitive datasets has been addressed. ...
doi:10.5120/3114-4279
fatcat:nza37yy2prft3jrueownimthw4
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