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Using Ontology in Hierarchical Information Clustering

T.D. Breaux, J.W. Reed
Proceedings of the 38th Annual Hawaii International Conference on System Sciences  
Using semantic features (e.g. hypernyms, meronyms, synonyms, etc.) encoded in ontology languages, methods such as keyword search and clustering can be augmented to analyze and visualize documents at conceptually  ...  We present findings from a hierarchical clustering system modified for ontological indexing and run on a topic-centric test collection of documents each with fewer than 200 words.  ...  In addition, we are able to demonstrate the relative improvement of using ontological term expansion over traditional hierarchical clustering that does not use ontologies.  ... 
doi:10.1109/hicss.2005.664 dblp:conf/hicss/BreauxR05 fatcat:cygi3fcjtngmddx2tt5h2eke3u

A Hierarchical Document Clustering Approach with Frequent Itemsets

Cheng-Jhe Lee, Chiun-Chieh Hsu, Da-Ren Chen
2017 International Journal of Engineering and Technology  
OCFI uses common words to cluster documents and builds hierarchical topic tree. In addition, OCFI utilizes ontology to solve the semantic problem and mine the meaning behind the words in documents.  ...  We propose the OCFI (Ontology and Closed Frequent Itemset-based Hierarchical Clustering) method, which is a hierarchical clustering method developed for document clustering.  ...  OCFI uses common words to cluster documents and builds hierarchical topic tree. In addition, OCFI utilizes ontology to solve the semantic problem and mine the meaning behind the words in documents.  ... 
doi:10.7763/ijet.2017.v9.965 fatcat:ft2h5bjxj5es3dha3ovydcvoye

A Novel Ontology Analysis Tool

Zhixiao Wang, Shixiong Xia, Qiang Niu
2014 Applied Mathematics & Information Sciences  
Experiments showed that the semantic field does well in ontology concept hierarchical clustering analysis.  ...  Based on equipotential line distribution, we can analyze concept hierarchical clustering characteristics.  ...  Our sincere thanks go to Professor Dalu Zhang, the doctoral supervisor of first author Zhixiao Wang, who introduces field theory to us to solve scientific problems.  ... 
doi:10.12785/amis/080131 fatcat:llquqrq5fzeq7ifwzuhlu5h54q

Ontology Knowledge Mining for Ontology Alignment

Rihab Idoudi, Karim Saheb Ettabaa, Basel Solaiman, Kamel Hamrouni
2016 International Journal of Computational Intelligence Systems  
The ontology alignment process is performed iteratively over the produced hierarchical structure of the fuzzy clusters using semantic techniques.  ...  The latter consists on producing for each ontology a hierarchical structure of fuzzy conceptual clusters, where a concept can belong to several clusters simultaneously.  ...  The use of limited information about the cluster may result in less alignment quality.  ... 
doi:10.1080/18756891.2016.1237187 fatcat:3n7usmjidzdjzesxw6xx37cj34

Biomedical ontology improves biomedical literature clustering performance: a comparison study

Illhoi Yoo, Xiaohua Hu, Il Yeol Song
2007 International Journal of Bioinformatics Research and Applications  
In addition, our results show that decent document clustering approaches, such as Bisecting K-means, K-means and STC, gains some benefit from the ontology while hierarchical algorithms showing the poorest  ...  Document clustering has been used for better document retrieval and text mining.  ...  Acknowledgements This research work is supported in part from the NSF Career grant (NSF IIS 0448023).  ... 
doi:10.1504/ijbra.2007.015010 pmid:18048199 fatcat:lhtzgq4owbclrd7dye5r22ax4u

A schema-free instance matching algorithm based on virtual document similarity

Siham Amrouch, Sihem Mostefai
2022 ˜The œinternational Arab journal of information technology  
We transform the instance matching problem to a document similarity problem and we solve it by a Clustering technique that uses an Ascendant Hierarchical Clustering algorithm to group similar instances  ...  in the same clusters.  ...  To deal with this issue, we use an appropriate approach to stop combining the clusters in the Hierarchical Clustering algorithm.  ... 
doi:10.34028/iajit/19/3a/3 dblp:journals/iajit/AmrouchM22 fatcat:v3ggrxk5bfewpiw66l6v4qcpta

A comprehensive comparison study of document clustering for a biomedical digital library MEDLINE

Illhoi Yoo, Xiaohua Hu
2006 Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries - JCDL '06  
Because an ontology is a formal, explicit specification of a shared conceptualization for a domain of interest, the use of ontologies is a natural way to solve traditional information retrieval problems  ...  Document clustering has been used for better document retrieval, document browsing, and text mining in digital library.  ...  [10] claims the use of ontology may improve document clustering.  ... 
doi:10.1145/1141753.1141802 dblp:conf/jcdl/YooH06 fatcat:tidbbq52ojculi74afzwdns4gy

Reconstruction of Phylogenetic Relationships from Metabolic Pathways Based on the Enzyme Hierarchy and the Gene Ontology

Joséc. Clemente, Kenji Satou, Gabriel Valiente
2005 Genome Informatics Series  
In this paper, we show that the combination of a new heuristic algorithm for the comparison of metabolic pathways together with any of three enzyme similarity measures (hierarchical, information content  ...  , and gene ontology) can be used to derive a metabolic pathway similarity measure that is suitable for reconstructing phylogenetic relationships from metabolic pathways.  ...  Acknowledgments The research described in this paper was partially supported by the Spanish CICYT, project GRAM-MARS (TIN2004-07925-C03-01), by the Japan Society for the Promotion of Science through Long-term  ... 
doi:10.11234/gi1990.16.2_45 fatcat:rhqtio7m3ne2tbge3xh3v2prfa

Biomedical Ontology MeSH Improves Document Clustering Qualify on MEDLINE Articles: A Comparison Study

Illhoi Yoo, Xiaohua Hu
2006 19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)  
In addition, our results show that decent document clustering approaches, such as Bisecting K-means, K-means and STC, gains some benefit from MeSH ontology while hierarchical algorithms showing the poorest  ...  In this paper, we investigate if biomedical ontology MeSH improves the clustering quality for MEDLINE articles.  ...  We use BiSecting K-means, K-means, and hierarchical clustering algorithms in the CLUTO clustering package 1 .  ... 
doi:10.1109/cbms.2006.62 dblp:conf/cbms/YooH06 fatcat:jowg4zsk6fa6jcjx7h455pejb4

Bootstrapping Operation-Level Web Service Ontology: A bottom-up Approach

Xumin Liu, Hua Liu
2011 Proceedings of the 7th International Conference on Collaborative Computing: Networking, Applications and Worksharing  
The approach leverages the techniques of information retrieval and machine learning. The relevance and similarity between Web services are measured based on the WSDL descriptions.  ...  The process of developing service ontologies consists of two steps. First, we build service ontologies based on the service relevance.  ...  We omit these information for the sake of space. As can be seen in Figure 3 , the clustering proceeds in a hierarchical fashion.  ... 
doi:10.4108/icst.collaboratecom.2011.247159 dblp:conf/colcom/LiuL11 fatcat:exfif7jjgfclrhohca4ksukrxm

Automated structuring of company profiles

Peter Ljubič, Nada Lavrač, Dunja Mladenić, Joel Plisson, Igor Mozetič
2006 Metodološki zvezki. Advances in methodology and statistics  
Alternatively, there are text mining, conceptual clustering and visualization tools available that can be used for semi-automated ontology creation.  ...  Partner selection can be facilitated by structuring competencies in an ontology which provides a shared conceptualization. Manual ontology construction is a time and resource consuming activity.  ...  Acknowledgments We are grateful to Marko Grobelnik and Rayid Ghani for the discussion in which we chose Yahoo! ontology restructuring to be the topic of this research.  ... 
doi:10.51936/keqv9637 fatcat:tjrovjfdynaclaowl2lhzelzua

Study of Ontology or Thesaurus Based Document Clustering and Information Retrieval

G. Bharathi, D. Venkatesan
2012 Journal of Engineering and Applied Sciences  
Document clustering generates clusters from the whole document collection automatically and is used in many fields, including data mining and information retrieval.  ...  In the traditional vector space model, the unique words occurring in the document set are used as the features.  ...  Thus in this paper, we make a survey of recent methodologies and approaches that are followed, used and developed to improve Document Clustering and Information Retrieval processes by using Ontology or  ... 
doi:10.3923/jeasci.2012.342.347 fatcat:qsdkroainjc4ljxmfunfiqwonm

Fuzzy Logic Applications for Knowledge Discovery: a Survey

Jorge Ropero, Carlos Leon, Alejandro Carrasco, Ariel Gomez, Octavio Rivera
2011 International Journal of Advancements in Computing Technology  
For VSM applications, we split the applications into those related to queries, clustering, user profiles and hierarchical relations.  ...  KD has been widely used for the search of information in vague, imprecise and noisy environments. Computational Intelligence, and mainly Fuzzy Logic, emerges as an ideal tool for IR and IE systems.  ...  There are a few clustering hierarchical algorithms: Hierarchical clustering may build (agglomerative clustering), or divide (divisive clustering) a group of clusters.  ... 
doi:10.4156/ijact.vol3.issue6.22 fatcat:j2d7fl6irzgvbn2qualdgshuqq

Automating Ontology Generation for Information Systems Research Using GHSOM

Mohammad Saad Al-Ahmadi, Ramesh Sharda
2003 Americas Conference on Information Systems  
Our project-in-progress is exploring the use of GHSOM to generate ontology for the Information Systems (IS) published research.  ...  Growing Hierarchical Self-Organizing Map (GHSOM) is a promising unsupervised artificial neural networks architecture that can help in identifying hierarchical relations embedded into datasets.  ...  We use ontology and taxonomy interchangeably. The purpose of this paper is to explore the use of hierarchical clustering techniques to build taxonomies semi-automatically.  ... 
dblp:conf/amcis/Al-AhmadiS03 fatcat:nkxriqxohneyhb6w7ium7zto2q

An Ontology Alignment Approach Combining Word Embedding and the Radius Measure [chapter]

Molka Tounsi Dhouib, Catherine Faron Zucker, Andrea G. B. Tettamanzi
2019 Lecture Notes in Computer Science  
Ontology alignment plays a key role in achieving interoperability on the semantic Web.  ...  The experimental results show that using word embedding and the radius measure make it possible to determine, with good accuracy, not only equivalence relations, but also hierarchical relations between  ...  Searching for Matching Concepts We match every concept in the source ontology O 1 with the similar concept in the target ontology O 2 using the cosine similarity between vector representations of concept  ... 
doi:10.1007/978-3-030-33220-4_14 fatcat:sererwcixnbszj3vdfsdn4k7ce
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