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Neuss, C.; Kent, R.E.: Conceptual analysis of resource meta-information (1995)
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- Abstract
- With the continuously growing amount of Internet accessible information resources, locating relevant information in the WWW becomes increasingly difficult. Recent developments provide scalable mechanisms for maintaing indexes of network accessible information. In order to implement sophisticated retrieval engines, a means of automatic analysis and classification of document meta information has to be found. Proposes the use of methods from the mathematical theory of concept analysis to analyze and interactively explore the information space defined by wide area resource discovery services
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Eklund, P.; Groh, B.; Stumme, G.; Wille, R.: ¬A conceptual-logic extension of TOSCANA (2000)
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- Abstract
- The aim of this paper is to indicate how TOSCANA may be extended to allow graphical representations not only of concept lattices but also of concept graphs in the sense of Contextual Logic. The contextual- logic extension of TOSCANA requires the logical scaling of conceptual and relational scales for which we propose the Peircean Algebraic Logic as reconstructed by R. W. Burch. As graphical representations we recommend, besides labelled line diagrams of concept lattices and Sowa's diagrams of conceptual graphs, particular information maps for utilizing background knowledge as much as possible. Our considerations are illustrated by a small information system about the domestic flights in Austria
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Eklund. P.W.: Logic-based networks : concept graphs and conceptual structures (2000)
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- Abstract
- Logic-based networks are semantic networks that support reasoning capabilities. In this paper, knowledge processing within logicbased networks is viewed as three stages. The first stage involves the formation of concepts and relations: the basic primitives with which we wish to formulate knowledge. The second stage involves the formation of wellformed formulas that express knowledge about the primitive concepts and relations once isolated. The final stage involves efficiently processing the wffs to the desired end. Our research involves each of these steps as they relate to Sowa's conceptual structures and Wille's concept lattices. Formal Concept Analysis gives us a capability to perform concept formation via symbolic machine learning. Concept(ual) Graphs provide a means to describe relational properties between primitive concept and relation types. Finally, techniques from other areas of computer science are required to compute logic-based networks efficiently. This paper illustrates the three stages of knowledge processing in practical terms using examples from our research
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Kollewe, W.; Sander, C.; Schmiede, R.; Wille, R.: TOSCANA als Instrument der bibliothekarischen Sacherschließung (1995)
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Groh, B.; Strahringer, S.; Wille, R.: TOSCANA-systems based on thesauri (1998)
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Kumar, C.A.; Radvansky, M.; Annapurna, J.: Analysis of Vector Space Model, Latent Semantic Indexing and Formal Concept Analysis for information retrieval (2012)
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- Abstract
- Latent Semantic Indexing (LSI), a variant of classical Vector Space Model (VSM), is an Information Retrieval (IR) model that attempts to capture the latent semantic relationship between the data items. Mathematical lattices, under the framework of Formal Concept Analysis (FCA), represent conceptual hierarchies in data and retrieve the information. However both LSI and FCA uses the data represented in form of matrices. The objective of this paper is to systematically analyze VSM, LSI and FCA for the task of IR using the standard and real life datasets.
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Kipke, U.; Wille, R.: Begriffsverbände als Ablaufschemata zur Gegenstandsbestimmung (1986)
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Kollewe, W.: Instrumente der Literaturverwaltung : Inhaltliche analyse von Datenbeständen durch 'Begriffliche Wissensverarbeitung' (1996)
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Priss, U.; Old, L.J.: Concept neighbourhoods in knowledge organisation systems (2010)
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Wille, R.: Begriffliche Wissensverarbeitung in der Wirtschaft (2002)
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