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Lindig, C.; Snelting, G.: Formale Begriffsnalyse im Software Engineering (2000)
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Rock, T.; Wille, R.: ¬Ein TOSCANA-Erkundungssystem zur Literatursuche (2000)
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Sedelow, S.Y.; Sedelow, W.A.: Thesauri and concept-lattice semantic nets (1994)
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- Abstract
- Formal concept lattices are a promising vehicle for the construction of rigorous and empirically accurate semantic nets. Presented here are results of initial experiments with concept lattices as representations of semantic relationships in the implicit structure of a large database (e.g. Roget's thesaurus)
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Kent, R.E.: Implications and rules in thesauri (1994)
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- Abstract
- A central consideration in the study of whole language semantic space as encoded in thesauri is word sense comparability. Shows how word sense comparability can be adequately expressed by the logical implications and rules from Formal Concept Analysis. Formal concept analysis, a new approach to formal logic initiated by Rudolf Wille, has been used for data modelling, analysis and interpretation, and also for knowledge representation and knowledge discovery
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Priss, U.: Comparing classification systems using facets (2000)
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- Abstract
- This paper describes a qualitative methodology for comparing and analyzing classification schemes. Theoretical facets are modeled as concept lattices in the sense of formal concept analysis and are used as 'ground' on which the underlying conceptual facets of a classification scheme are visually represented as 'figures'.
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Ganter, B.: Computing with conceptual structures (2000)
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- Abstract
- We give an overview over the computational tools for conceptional structures that have emerged from the theory of Formal Concept Analysis, with emphasis on basic ideas rather than technical details. We describe what we mean by conceptual computations, and try to convince the reader that an elaborate formalization is a necessary precondition. Claiming that Formal Concept Analysis provides such a formal background, we present as examples two well known algorithms in very simple pseudo code. These earl be used for navigating in a lattice, thereby supporting some prototypical tasks of conceptual computation. We refer to some of the many more advanced methods, discuss how to compute with limited precision and explain why in the case of incomplete knowledge the conceptual approach is more efficient than a combinatorial one. Utilizing this efficiency requires skillful use of the formalism. We present two results that lead in this direction
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Negm, E.; AbdelRahman, S.; Bahgat, R.: PREFCA: a portal retrieval engine based on formal concept analysis (2017)
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- Abstract
- The web is a network of linked sites whereby each site either forms a physical portal or a standalone page. In the former case, the portal presents an access point to its embedded web pages that coherently present a specific topic. In the latter case, there are millions of standalone web pages, that are scattered throughout the web, having the same topic and could be conceptually linked together to form virtual portals. Search engines have been developed to help users in reaching the adequate pages in an efficient and effective manner. All the known current search engine techniques rely on the web page as the basic atomic search unit. They ignore the conceptual links, that reveal the implicit web related meanings, among the retrieved pages. However, building a semantic model for the whole portal may contain more semantic information than a model of scattered individual pages. In addition, user queries can be poor and contain imprecise terms that do not reflect the real user intention. Consequently, retrieving the standalone individual pages that are directly related to the query may not satisfy the user's need. In this paper, we propose PREFCA, a Portal Retrieval Engine based on Formal Concept Analysis that relies on the portal as the main search unit. PREFCA consists of three phases: First, the information extraction phase that is concerned with extracting portal's semantic data. Second, the formal concept analysis phase that utilizes formal concept analysis to discover the conceptual links among portal and attributes. Finally, the information retrieval phase where we propose a portal ranking method to retrieve ranked pairs of portals and embedded pages. Additionally, we apply the network analysis rules to output some portal characteristics. We evaluated PREFCA using two data sets, namely the Forum for Information Retrieval Evaluation 2010 and ClueWeb09 (category B) test data, for physical and virtual portals respectively. PREFCA proves higher F-measure accuracy, better Mean Average Precision ranking and comparable network analysis and efficiency results than other search engine approaches, namely Term Frequency Inverse Document Frequency (TF-IDF), Latent Semantic Analysis (LSA), and BM25 techniques. As well, it gains high Mean Average Precision in comparison with learning to rank techniques. Moreover, PREFCA also gains better reach time than Carrot as a well-known topic-based search engine.
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Hereth, J.; Stumme, G.; Wille, R.; Wille, U.: Conceptual knowledge discovery and data analysis (2000)
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- Abstract
- In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) in its connection with Data Analysis. Our approach is based on Formal Concept Analysis, a mathematical theory which has been developed and proven useful during the last 20 years. Formal Concept Analysis has led to a theory of conceptual information systems which has been applied by using the management system TOSCANA in a wide range of domains. In this paper, we use such an application in database marketing to demonstrate how methods and procedures of CKDD can be applied in Data Analysis. In particular, we show the interplay and integration of data mining and data analysis techniques based on Formal Concept Analysis. The main concern of this paper is to explain how the transition from data to knowledge can be supported by a TOSCANA system. To clarify the transition steps we discuss their correspondence to the five levels of knowledge representation established by R. Brachman and to the steps of empirically grounded theory building proposed by A. Strauss and J. Corbin
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Ganter, B.; Wille, R.: Implikationen und Abhängigkeiten zwischen Merkmalen (1986)
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Kollewe, W.; Skorsky, M.; Vogt, F.; Wille, R.: TOSCANA - ein Werkzeug zur begrifflichen Analyse und Erkundung von Daten (1994)
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Wille, R.; Wachter, C.: Begriffsanalyse von Dokumenten (1992)
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Wille, R.: Liniendiagramme hierarchischer Begriffssysteme (1984)
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Skorsky, M.: Dokumentensammlungen : Strukturiert und recherchiert mit TOSKANA (1996)
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Scheich, P.; Skorsky, M.; Vogt, F.; Wachter, C.; Wille, R.: Conceptual data systems (1993)
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Skorsky, M.: Graphische Darstellung eines Thesaurus (1997)
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Strack, H.; Skorsky, M.: Zugriffskontrolle bei Programmsystemen und im Datenschutz mittels Formaler Begriffsanalyse (2000)
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Andelfinger, U.: Inhaltliche Erschließung des Bereichs 'Sozialorientierte Gestaltung von Informationstechnik' : Ein begriffsanalytischer Ansatz (2000)
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Eschenfelder, D.; Kollewe, W.; Skorsky, M.; Wille, R.: ¬Ein Erkundungssystem zum Baurecht : Methoden der Entwicklung eines TOSCANA-Systems (2000)
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Kohler-Koch, B.; Vogt, F.: Normen- und regelgeleitete internationale Kooperationen : Formale Begriffsanalyse in der Politikwissenschaft (2000)
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Henning, H.J.; Kemmnitz, W.: Entwicklung eines kontextuellen Methodenkonzeptes mit Hilfe der Formalen Begriffsanalyse an Beispielen zum Risikoverständnis (2000)
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