-
Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019)
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- Content
- Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
-
Xiong, C.: Knowledge based text representations for information retrieval (2016)
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- Content
- Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.
-
Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005)
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- Content
- Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
-
Curras, E.: Ontologies, taxonomy and thesauri in information organisation and retrieval (2010)
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- Content
- Inhalt: 1. From classifications to ontologies Knowledge - A new concept of knowledge - Knowledge and information - Knowledge organisation - Knowledge organisation and representation - Cognitive sciences - Talent management - Learning systematisation - Historical evolution - From classification to knowledge organisation - Why ontologies exist - Ontologies - The structure of ontologies 2. Taxonomies and thesauri From ordering to taxonomy - The origins of taxonomy - Hierarchical and horizontal order - Correlation with classifications - Taxonomy in computer science - Computing taxonomy - Definitions - Virtual taxonomy, cybernetic taxonomy - Taxonomy in Information Science - Similarities between taxonomies and thesauri - ifferences between taxonomies and thesauri 3. Thesauri Terminology in classification systems - Terminological languages - Thesauri - Thesauri definitions - Conditions that a thesaurus must fulfil - Historical evolution - Classes of thesauri 4. Thesauri in (cladist) systematics Systematics - Systematics as a noun - Definitions and historic evolution over time - Differences between taxonomy and systematics - Systematics in thesaurus construction theory - Classic, numerical and cladist systematics - Classic systematics in information science - Numerical systematics in information science - Thesauri in cladist systematics - Systematics in information technology - Some examples 5. Thesauri in systems theory Historical evolution - Approach to systems - Systems theory applied to the construction of thesauri - Components - Classes of system - Peculiarities of these systems - Working methods - Systems theory applied to ontologies and taxonomies
-
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.
-
Amirhosseini, M.; Avidan, G.: ¬A dialectic perspective on the evolution of thesauri and ontologies (2021)
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- Abstract
- The purpose of this article is to identify the most important factors and features in the evolution of thesauri and ontologies through a dialectic model. This model relies on a dialectic process or idea which could be discovered via a dialectic method. This method has focused on identifying the logical relationship between a beginning proposition, or an idea called a thesis, a negation of that idea called the antithesis, and the result of the conflict between the two ideas, called a synthesis. During the creation of knowledge organization systems (KOSs), the identification of logical relations between different ideas has been made possible through the consideration and use of the most influential methods and tools such as dictionaries, Roget's Thesaurus, thesaurus, micro-, macro- and metathesauri, ontology, lower, middle and upper level ontologies. The analysis process has adapted a historical methodology, more specifically a dialectic method and documentary method as the reasoning process. This supports our arguments and synthesizes a method for the analysis of research results. Confirmed by the research results, the principle of unity has shown to be the most important factor in the development and evolution of the structure of knowledge organization systems and their types. There are various types of unity when considering the analysis of logical relations. These include the principle of unity of alphabetical order, unity of science, semantic unity, structural unity and conceptual unity. The results have clearly demonstrated a movement from plurality to unity in the assembling of the complex structure of knowledge organization systems to increase information and knowledge storage and retrieval performance.
-
Menzel, C.: Knowledge representation, the World Wide Web, and the evolution of logic (2011)
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- Abstract
- In this paper, I have traced a series of evolutionary adaptations of FOL motivated entirely by its use by knowledge engineers to represent and share information on the Web culminating in the development of Common Logic. While the primary goal in this paper has been to document this evolution, it is arguable, I think that CL's syntactic and semantic egalitarianism better realizes the goal "topic neutrality" that a logic should ideally exemplify - understood, at least in part, as the idea that logic should as far as possible not itself embody any metaphysical presuppositions. Instead of retaining the traditional metaphysical divisions of FOL that reflect its Fregean origins, CL begins as it were with a single, metaphysically homogeneous domain in which, potentially, anything can play the traditional roles of object, property, relation, and function. Note that the effect of this is not to destroy traditional metaphysical divisions. Rather, it simply to refrain from building those divisions explicitly into one's logic; instead, such divisions are left to the user to introduce and enforce axiomatically in an explicit metaphysical theory.
-
Broughton, V.: Science and knowledge organization : an editorial (2021)
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- Abstract
- The purpose of this article is to identify the most important factors and features in the evolution of thesauri and ontologies through a dialectic model. This model relies on a dialectic process or idea which could be discovered via a dialectic method. This method has focused on identifying the logical relationship between a beginning proposition, or an idea called a thesis, a negation of that idea called the antithesis, and the result of the conflict between the two ideas, called a synthesis. During the creation of knowledge organization systems (KOSs), the identification of logical relations between different ideas has been made possible through the consideration and use of the most influential methods and tools such as dictionaries, Roget's Thesaurus, thesaurus, micro-, macro- and metathesauri, ontology, lower, middle and upper level ontologies. The analysis process has adapted a historical methodology, more specifically a dialectic method and documentary method as the reasoning process. This supports our arguments and synthesizes a method for the analysis of research results. Confirmed by the research results, the principle of unity has shown to be the most important factor in the development and evolution of the structure of knowledge organization systems and their types. There are various types of unity when considering the analysis of logical relations. These include the principle of unity of alphabetical order, unity of science, semantic unity, structural unity and conceptual unity. The results have clearly demonstrated a movement from plurality to unity in the assembling of the complex structure of knowledge organization systems to increase information and knowledge storage and retrieval performance.
-
Pike, W.; Gahegan, M.: Beyond ontologies : toward situated representations of scientific knowledge (2007)
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- Abstract
- In information systems that support knowledge-discovery applications such as scientific exploration, reliance on highly structured ontologies as data-organization aids can be limiting. With current computational aids to science work, the human knowledge that creates meaning out of analyses is often only recorded when work reaches publication-or worse, left unrecorded altogether-for lack of an ontological model for scientific concepts that can capture knowledge as it is created and used. We argue for an approach to representing scientific concepts that reflects (1) the situated processes of science work, (2) the social construction of knowledge, and (3) the emergence and evolution of understanding over time. In this model, knowledge is the result of collaboration, negotiation, and manipulation by teams of researchers. Capturing the situations in which knowledge is created and used helps these collaborators discover areas of agreement and discord, while allowing individual inquirers to maintain different perspectives on the same information. The capture of provenance information allows historical trails of reasoning to be reconstructed, allowing end users to evaluate the utility and trustworthiness of knowledge representations. We present a proof-of-concept system, called Codex, based on this situated knowledge model. Codex supports visualization of knowledge structures through concept mapping, and enables inference across those structures. The proof-of-concept is deployed in the domain of geoscience to support distributed teams of learners and researchers.
-
McGuinness, D.L.: Ontologies come of age (2003)
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- Abstract
- Ontologies have moved beyond the domains of library science, philosophy, and knowledge representation. They are now the concerns of marketing departments, CEOs, and mainstream business. Research analyst companies such as Forrester Research report on the critical roles of ontologies in support of browsing and search for e-commerce and in support of interoperability for facilitation of knowledge management and configuration. One now sees ontologies used as central controlled vocabularies that are integrated into catalogues, databases, web publications, knowledge management applications, etc. Large ontologies are essential components in many online applications including search (such as Yahoo and Lycos), e-commerce (such as Amazon and eBay), configuration (such as Dell and PC-Order), etc. One also sees ontologies that have long life spans, sometimes in multiple projects (such as UMLS, SIC codes, etc.). Such diverse usage generates many implications for ontology environments. In this paper, we will discuss ontologies and requirements in their current instantiations on the web today. We will describe some desirable properties of ontologies. We will also discuss how both simple and complex ontologies are being and may be used to support varied applications. We will conclude with a discussion of emerging trends in ontologies and their environments and briefly mention our evolving ontology evolution environment.
-
Klein, M.; Ding, Y.; Fensel, D.; Omelayenko, B.: Ontology management : storing, aligning and maintaining ontologies (2004)
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- Abstract
- Ontologies need to be stored, sometimes aligned and their evolution needs to be managed. All these tasks together are called ontology management. Alignment is a central task in ontology re-use. Re-use of existing ontologies often requires considerable effort: the ontologies either need to be integrated, which means that they are merged into one new ontology, or the ontologies can be kept separate. In both cases, the ontologies have to be aligned, which means that they have to be brought into mutual agreement. The problems that underlie the difficulties in integrating and aligning are the mismatches that may exist between separate ontologies. Ontologies can differ at the language level, which can mean that they are represented in a different syntax, or that the expressiveness of the ontology language is dissimilar. Ontologies also can have mismatches at the model level, for example, in the paradigm, or modelling style. Ontology alignment is very relevant in a Semantic Web context. The Semantic Web will provide us with a lot of freely accessible domain specific ontologies. To form a real web of semantics - which will allow computers to combine and infer implicit knowledge - those separate ontologies should be aligned and linked.
-
Schmitz-Esser, W.: Language of general communication and concept compatibility (1996)
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- Pages
- S.11-22
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Tudhope, D.; Hodge, G.: Terminology registries (2007)
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- Date
- 26.12.2011 13:22:07
-
Börner, K.: Atlas of knowledge : anyone can map (2015)
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- Date
- 22. 1.2017 16:54:03
22. 1.2017 17:10:56
-
Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009)
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- Date
- 31. 7.2010 16:58:22
-
OWL Web Ontology Language Test Cases (2004)
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- Date
- 14. 8.2011 13:33:22
-
Giunchiglia, F.; Villafiorita, A.; Walsh, T.: Theories of abstraction (1997)
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- Date
- 1.10.2018 14:13:22
-
Priss, U.: Faceted information representation (2000)
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