-
Calegari, S.; Sanchez, E.: Object-fuzzy concept network : an enrichment of ontologies in semantic information retrieval (2008)
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- Abstract
- This article shows how a fuzzy ontology-based approach can improve semantic documents retrieval. After formally defining a fuzzy ontology and a fuzzy knowledge base, a special type of new fuzzy relationship called (semantic) correlation, which links the concepts or entities in a fuzzy ontology, is discussed. These correlations, first assigned by experts, are updated after querying or when a document has been inserted into a database. Moreover, in order to define a dynamic knowledge of a domain adapting itself to the context, it is shown how to handle a tradeoff between the correct definition of an object, taken in the ontology structure, and the actual meaning assigned by individuals. The notion of a fuzzy concept network is extended, incorporating database objects so that entities and documents can similarly be represented in the network. Information retrieval (IR) algorithm, using an object-fuzzy concept network (O-FCN), is introduced and described. This algorithm allows us to derive a unique path among the entities involved in the query to obtain maxima semantic associations in the knowledge domain. Finally, the study has been validated by querying a database using fuzzy recall, fuzzy precision, and coefficient variant measures in the crisp and fuzzy cases.
- Date
- 9.11.2008 13:07:29
-
Grzonkowski, S.; Kruk, S.R.; Gzella, A.; Demczuk, J.; McDaniel, B.: Community-aware ontologies (2009)
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- Abstract
- The term "social network" was first mentioned in 1954 by J.A. Barnes. The social network is a structure that consists of nodes; the nodes represent individual people or organizations. Such a structure depicts the ways in which people are connected through diverse social familiarities like acquaintance, friendship or close familiar bonds.
-
Griffiths, T.L.; Steyvers, M.: ¬A probabilistic approach to semantic representation (2002)
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- Date
- 29. 6.2015 14:55:01
29. 6.2015 16:09:05
-
Drexel, G.: Knowledge engineering for intelligent information retrieval (2001)
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- Abstract
- This paper presents a clustered approach to designing an overall ontological model together with a general rule-based component that serves as a mapping device. By observational criteria, a multi-lingual team of experts excerpts concepts from general communication in the media. The team, then, finds equivalent expressions in English, German, French, and Spanish. On the basis of a set of ontological and lexical relations, a conceptual network is built up. Concepts are thought to be universal. Objects unique in time and space are identified by names and will be explained by the universals as their instances. Our approach relies on multi-relational descriptions of concepts. It provides a powerful tool for documentation and conceptual language learning. First and foremost, our multi-lingual, polyhierarchical ontology fills the gap of semantically-based information retrieval by generating enhanced and improved queries for internet search
-
Nelson, S.J.; Powell, T.; Srinivasan, S.; Humphreys, B.L.: Unified Medical Language System® (UMLS®) Project (2009)
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- Abstract
- The Unified Medical Language System (UMLS) is a long-term research and development effort of the National Library of Medicine, aimed at assisting users in finding information from multiple sources without understanding the intricacies of each particular source. Consisting of three major knowledge sources, a Metathesaurus, a Semantic Network, and a set of lexical processing tools, the UMLS is produced and released twice yearly. Recent efforts have been aimed at expanding coverage in genetics and in clinical vocabularies designed for use in medical record systems. RxNorm, produced and released on a monthly basis, with weekly updates, is an outgrowth of the UMLS, focusing on medication terminology.
-
Park, J.-r.: Evolution of concept networks and implications for knowledge representation (2007)
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- Abstract
- Purpose - The purpose of this paper is to present descriptive characteristics of the historical development of concept networks. The linguistic principles, mechanisms and motivations behind the evolution of concept networks are discussed. Implications emanating from the idea of the historical development of concept networks are discussed in relation to knowledge representation and organization schemes. Design/methodology/approach - Natural language data including both speech and text are analyzed by examining discourse contexts in which a linguistic element such as a polysemy or homonym occurs. Linguistic literature on the historical development of concept networks is reviewed and analyzed. Findings - Semantic sense relations in concept networks can be captured in a systematic and regular manner. The mechanism and impetus behind the process of concept network development suggest that semantic senses in concept networks are closely intertwined with pragmatic contexts and discourse structure. The interrelation and permeability of the semantic senses of concept networks are captured on a continuum scale based on three linguistic parameters: concrete shared semantic sense; discourse and text structure; and contextualized pragmatic information. Research limitations/implications - Research findings signify the critical need for linking discourse structure and contextualized pragmatic information to knowledge representation and organization schemes. Originality/value - The idea of linguistic characteristics, principles, motivation and mechanisms underlying the evolution of concept networks provides theoretical ground for developing a model for integrating knowledge representation and organization schemes with discourse structure and contextualized pragmatic information.
-
Rindflesch, T.C.; Fizsman, M.: The interaction of domain knowledge and linguistic structure in natural language processing : interpreting hypernymic propositions in biomedical text (2003)
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- Abstract
- Interpretation of semantic propositions in free-text documents such as MEDLINE citations would provide valuable support for biomedical applications, and several approaches to semantic interpretation are being pursued in the biomedical informatics community. In this paper, we describe a methodology for interpreting linguistic structures that encode hypernymic propositions, in which a more specific concept is in a taxonomic relationship with a more general concept. In order to effectively process these constructions, we exploit underspecified syntactic analysis and structured domain knowledge from the Unified Medical Language System (UMLS). After introducing the syntactic processing on which our system depends, we focus on the UMLS knowledge that supports interpretation of hypernymic propositions. We first use semantic groups from the Semantic Network to ensure that the two concepts involved are compatible; hierarchical information in the Metathesaurus then determines which concept is more general and which more specific. A preliminary evaluation of a sample based on the semantic group Chemicals and Drugs provides 83% precision. An error analysis was conducted and potential solutions to the problems encountered are presented. The research discussed here serves as a paradigm for investigating the interaction between domain knowledge and linguistic structure in natural language processing, and could also make a contribution to research on automatic processing of discourse structure. Additional implications of the system we present include its integration in advanced semantic interpretation processors for biomedical text and its use for information extraction in specific domains. The approach has the potential to support a range of applications, including information retrieval and ontology engineering.
-
Mustafa El Hadi, W.: Terminologies, ontologies and information access (2006)
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- Date
- 29. 2.2008 16:25:23
-
Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009)
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- Date
- 31. 7.2010 16:58:22
-
Assem, M. van; Menken, M.R.; Schreiber, G.; Wielemaker, J.; Wielinga, B.: ¬A method for converting thesauri to RDF/OWL (2004)
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- Date
- 29. 7.2011 14:44:56
-
Priss, U.: Faceted information representation (2000)
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- Date
- 22. 1.2016 17:47:06
-
Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie (2005)
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- Date
- 11. 2.2011 18:22:58
-
Wielinga, B.; Wielemaker, J.; Schreiber, G.; Assem, M. van: Methods for porting resources to the Semantic Web (2004)
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- Date
- 29. 7.2011 14:44:56
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Vallet, D.; Fernández, M.; Castells, P.: ¬An ontology-based information retrieval model (2005)
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- Source
- The Semantic Web: research and applications ; second European Semantic WebConference, ESWC 2005, Heraklion, Crete, Greece, May 29 - June 1, 2005 ; proceedings. Eds.: A. Gómez-Pérez u. J. Euzenat
-
Matuszek, C.; Cabral, J.; Witbrock, M.; DeOliveira, J.: ¬An introduction to the syntax and content of Cyc (2006)
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- Source
- Formalizing and compiling background knowledge and its applications to knowledge representation and question answering : papers from the AAAI spring symposium ; [March 27 - 29, 2006, Stanford, California] / Chitta Baral, chair
-
Gendt, M. van; Isaac, I.; Meij, L. van der; Schlobach, S.: Semantic Web techniques for multiple views on heterogeneous collections : a case study (2006)
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- Source
- Research and advanced technology for digital libraries : 10th European conference, proceedings / ECDL 2006, Alicante, Spain, September 17 - 22, 2006
-
Renear, A.H.; Wickett, K.M.; Urban, R.J.; Dubin, D.; Shreeves, S.L.: Collection/item metadata relationships (2008)
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- Source
- Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
-
Kruk, S.R.; Kruk, E.; Stankiewicz, K.: Evaluation of semantic and social technologies for digital libraries (2009)
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- Date
- 1. 8.2010 12:35:22
-
Bittner, T.; Donnelly, M.; Winter, S.: Ontology and semantic interoperability (2006)
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- Date
- 3.12.2016 18:39:22
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Beppler, F.D.; Fonseca, F.T.; Pacheco, R.C.S.: Hermeneus: an architecture for an ontology-enabled information retrieval (2008)
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- Date
- 28.11.2016 12:43:22
