Search (43 results, page 1 of 3)

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Abstract

TOSCANA is a computer program which allows an online interaction with larger data bases to analyse and explore data conceptually. It uses labelled line diagrams of concept lattices to communicate knowledge coded in given data. The basic problem to create online presentations of concept lattices is solved by composing prepared diagrams to nested line diagrams. A larger number of applications in different areas have already shown that TOSCANA is a useful tool for many purposes

Source

Knowledge organization. 22(1995) no.2, S.78-81

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Abstract

With formal concept analysis surveys are analyzable in the way that a meaningful picture of the answers of the interviewed persons is available. Line diagrams of large concept lattices might become less readable up to the point that it is impossible to pursue the line segments with the eyes. Nested line diagrams give the opportunity to overcome these difficulties. The main idea of nested line diagrams is to partition the line diagram into boxes so that line segments between two boxes are all parallel and may be replaced by one line segment. The possibility to draw line diagrams with more than two factors does allow it to describe concept lattices with many hundred or thousand concepts in a clear structure. In practice it has often been proven useful to take standardized scales for the single levels

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Abstract

This paper presents an abstract formalization of the notion of "facets". Facets are relational structures of units, relations and other facets selected for a certain purpose. Facets can be used to structure large knowledge representation systems into a hierarchical arrangement of consistent and independent subsystems (facets) that facilitate flexibility and combinations of different viewpoints or aspects. This paper describes the basic notions, facet characteristics and construction mechanisms. It then explicates the theory in an example of a faceted information retrieval system (FaIR)

Date

22. 1.2016 17:47:06

Source

Working with conceptual structures: contributions to ICCS 2000. 8th International Conference on Conceptual Structures: Logical, Linguistic, and Computational Issues. Darmstadt, August 14-18, 2000. Ed.: G. Stumme

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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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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

Series

Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence

Source

Conceptual structures: logical, linguistic, and computational issues. 8th International Conference on Conceptual Structures, ICCS 2000, Darmstadt, Germany, August 14-18, 2000. Ed.: B. Ganter et al

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Abstract

Computer scientists create models of a perceived reality. Through AI techniques, these models aim at providing the basic support for emulating cognitive behavior such as reasoning and learning, which is one of the main goals of the Al research effort. Such computer models are formed through the interaction of various acquisition and inference mechanisms: perception, concept learning, conceptual clustering, hypothesis testing, probabilistic inference, etc., and are represented using different paradigms tightly linked to the processes that use them. Among these paradigms let us cite: biological models (neural nets, genetic programming), logic-based models (first-order logic, modal logic, rule-based systems), virtual reality models (object systems, agent systems), probabilistic models (Bayesian nets, fuzzy logic), linguistic models (conceptual dependency graphs, language-based rep resentations), etc. One of the strengths of the Conceptual Graph (CG) theory is its versatility in terms of the representation paradigms under which it falls. It can be viewed and therefore used, under different representation paradigms, which makes it a popular choice for a wealth of applications. Its full coupling with different cognitive processes lead to the opening of the field toward related research communities such as the Description Logic, Formal Concept Analysis, and Computational Linguistic communities. We now see more and more research results from one community enrich the other, laying the foundations of common philosophical grounds from which a successful synergy can emerge. ICCS 2000 embodies this spirit of research collaboration. It presents a set of papers that we believe, by their exposure, will benefit the whole community. For instance, the technical program proposes tracks on Conceptual Ontologies, Language, Formal Concept Analysis, Computational Aspects of Conceptual Structures, and Formal Semantics, with some papers on pragmatism and human related aspects of computing. Never before was the program of ICCS formed by so heterogeneously rooted theories of knowledge representation and use. We hope that this swirl of ideas will benefit you as much as it already has benefited us while putting together this program

Content

Concepts and Language: The Role of Conceptual Structure in Human Evolution (Keith Devlin) - Concepts in Linguistics - Concepts in Natural Language (Gisela Harras) - Patterns, Schemata, and Types: Author Support through Formalized Experience (Felix H. Gatzemeier) - Conventions and Notations for Knowledge Representation and Retrieval (Philippe Martin) - Conceptual Ontology: Ontology, Metadata, and Semiotics (John F. Sowa) - Pragmatically Yours (Mary Keeler) - Conceptual Modeling for Distributed Ontology Environments (Deborah L. McGuinness) - Discovery of Class Relations in Exception Structured Knowledge Bases (Hendra Suryanto, Paul Compton) - Conceptual Graphs: Perspectives: CGs Applications: Where Are We 7 Years after the First ICCS ? (Michel Chein, David Genest) - The Engineering of a CC-Based System: Fundamental Issues (Guy W. Mineau) - Conceptual Graphs, Metamodeling, and Notation of Concepts (Olivier Gerbé, Guy W. Mineau, Rudolf K. Keller) - Knowledge Representation and Reasonings: Based on Graph Homomorphism (Marie-Laure Mugnier) - User Modeling Using Conceptual Graphs for Intelligent Agents (James F. Baldwin, Trevor P. Martin, Aimilia Tzanavari) - Towards a Unified Querying System of Both Structured and Semi-structured Imprecise Data Using Fuzzy View (Patrice Buche, Ollivier Haemmerlé) - Formal Semantics of Conceptual Structures: The Extensional Semantics of the Conceptual Graph Formalism (Guy W. Mineau) - Semantics of Attribute Relations in Conceptual Graphs (Pavel Kocura) - Nested Concept Graphs and Triadic Power Context Families (Susanne Prediger) - Negations in Simple Concept Graphs (Frithjof Dau) - Extending the CG Model by Simulations (Jean-François Baget) - Contextual Logic and Formal Concept Analysis: Building and Structuring Description Logic Knowledge Bases: Using Least Common Subsumers and Concept Analysis (Franz Baader, Ralf Molitor) - On the Contextual Logic of Ordinal Data (Silke Pollandt, Rudolf Wille) - Boolean Concept Logic (Rudolf Wille) - Lattices of Triadic Concept Graphs (Bernd Groh, Rudolf Wille) - Formalizing Hypotheses with Concepts (Bernhard Ganter, Sergei 0. Kuznetsov) - Generalized Formal Concept Analysis (Laurent Chaudron, Nicolas Maille) - A Logical Generalization of Formal Concept Analysis (Sébastien Ferré, Olivier Ridoux) - On the Treatment of Incomplete Knowledge in Formal Concept Analysis (Peter Burmeister, Richard Holzer) - Conceptual Structures in Practice: Logic-Based Networks: Concept Graphs and Conceptual Structures (Peter W. Eklund) - Conceptual Knowledge Discovery and Data Analysis (Joachim Hereth, Gerd Stumme, Rudolf Wille, Uta Wille) - CEM - A Conceptual Email Manager (Richard Cole, Gerd Stumme) - A Contextual-Logic Extension of TOSCANA (Peter Eklund, Bernd Groh, Gerd Stumme, Rudolf Wille) - A Conceptual Graph Model for W3C Resource Description Framework (Olivier Corby, Rose Dieng, Cédric Hébert) - Computational Aspects of Conceptual Structures: Computing with Conceptual Structures (Bernhard Ganter) - Symmetry and the Computation of Conceptual Structures (Robert Levinson) An Introduction to SNePS 3 (Stuart C. Shapiro) - Composition Norm Dynamics Calculation with Conceptual Graphs (Aldo de Moor) - From PROLOG++ to PROLOG+CG: A CG Object-Oriented Logic Programming Language (Adil Kabbaj, Martin Janta-Polczynski) - A Cost-Bounded Algorithm to Control Events Generalization (Gaël de Chalendar, Brigitte Grau, Olivier Ferret)

Series

Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence

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Abstract

The present paper focuses on the extraction, by means of a formal logical/mathematical methodology (i.e. automatically, exclusively by rule), of concept content, as in, for example, continuous discourse. The approach to a fully formal defintion of concept content ultimately is owing to a German government initiative to establish 'standards' regarding concepts, in conjunction with efforts to stipulate precisely (and then, derivatively, through computer prgrams) data and information needs according to work role in certain government offices

Source

Behavior research methods instruments and computers. 25(1993) no.2, S.314-317

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Abstract

In recent years, knowledge structuring is assuming important roles in several real world applications such as decision support, cooperative problem solving, e-commerce, Semantic Web and, even in planning systems. Ontologies play an important role in supporting automated processes to access information and are at the core of new strategies for the development of knowledge-based systems. Yet, developing an ontology is a time-consuming task which often needs an accurate domain expertise to tackle structural and logical difficulties in the definition of concepts as well as conceivable relationships. This work presents an ontology-based retrieval approach, that supports data organization and visualization and provides a friendly navigation model. It exploits the fuzzy extension of the Formal Concept Analysis theory to elicit conceptualizations from datasets and generate a hierarchy-based representation of extracted knowledge. An intuitive graphical interface provides a multi-facets view of the built ontology. Through a transparent query-based retrieval, final users navigate across concepts, relations and population.

Content

Beitrag in einem Themenheft "Soft Approaches to IA on the Web". Vgl.: doi:10.1016/j.ipm.2011.04.003.

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Abstract

Faceted Knowledge Representation provides a formalism for implementing knowledge systems. The basic notions of faceted knowledge representation are "unit", "relation", "facet" and "interpretation". Units are atomic elements and can be abstract elements or refer to external objects in an application. Relations are sequences or matrices of 0 and 1's (binary matrices). Facets are relational structures that combine units and relations. Each facet represents an aspect or viewpoint of a knowledge system. Interpretations are mappings that can be used to translate between different representations. This paper introduces the basic notions of faceted knowledge representation. The formalism is applied here to an abstract modeling of a faceted thesaurus as used in information retrieval.

Date

22. 1.2016 17:30:31

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Abstract

Even for the experienced information professional, designing an efficient multi-purpose information access structure can be a very difficult task. This paper argues for the use of a faceted thesaurus as the basis for organizing a small-scale institutional website. We contend that a faceted approach to knowledge organization can make the process of organization less random and more manageable. We begin by reporting on an informal survey of three institutional websites. This study underscores the problems of organization that can impact access to information. We then formalize the terminology of faceted thesauri and demonstrate its application with several examples.
The writers show that a faceted navigation structure makes web sites easier to use. They begin by analyzing the web sites of three library and information science faculties, and seeing if the sites easily provide the answers to five specific questions, e.g., how the school ranks in national evaluations. (It is worth noting that the web site of the Faculty of Information Studies and the University of Toronto, where this bibliography is being written, would fail on four of the five questions.) Using examples from LIS web site content, they show how facets can be related and constructed, and use concept diagrams for illustration. They briefly discuss constraints necessary when joining facets: for example, enrolled students can be full- or part-time, but prospective and alumni students cannot. It should not be possible to construct terms such as "part-time alumni" (see Yannis Tzitzikas et al, below in Background). They conclude that a faceted approach is best for web site navigation, because it can clearly show where the user is in the site, what the related pages are, and how to get to them. There is a short discussion of user interfaces, and the diagrams in the paper will be of interest to anyone making a facet-based web site. This paper is clearly written, informative, and thought-provoking. Uta Priss's web site lists her other publications, many of which are related and some of which are online: http://www.upriss.org.uk/top/research.html.

Series

Proceedings of the American Society for Information Science; vol.36

Source

Knowledge: creation, organization and use. Proceedings of the 62nd Annual Meeting of the American Society for Information Science, 31.10.-4.11.1999. Ed.: L. Woods

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Abstract

This is the first textbook on formal concept analysis. It gives a systematic presentation of the mathematical foundations and their relation to applications in computer science, especially data analysis and knowledge processing. Above all, it presents graphical methods for representing conceptual systems that have proved themselves in communicating knowledge. Theory and graphical representation are thus closely coupled together. The mathematical foundations are treated thouroughly and illuminated by means of numerous examples. Since computers are being used ever more widely for knowledge processing, formal methods for conceptual analysis are gaining in importance. This book makes the basic theory for such methods accessible in a compact form

Content

Order theoretical foundations. - Concept lattices of contexts. - Determination and presentation. - Parts and factors. - Analysis, construction and properties of concept lattices. - Context comparison and conceptual measurability

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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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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

Series

Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence

Source

Conceptual structures: logical, linguistic, and computational issues. 8th International Conference on Conceptual Structures, ICCS 2000, Darmstadt, Germany, August 14-18, 2000. Ed.: B. Ganter et al

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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

Series

Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence

Source

Conceptual structures: logical, linguistic, and computational issues. 8th International Conference on Conceptual Structures, ICCS 2000, Darmstadt, Germany, August 14-18, 2000. Ed.: B. Ganter et al

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Abstract

A lattice-based model for information retrieval was suggested in the 1960's but has been seen as a theoretical possibility hard to practically apply ever since. This paper attempts to revive the lattice model and demonstrate its applicability in an information retrieval system, FalR, that incorporates a graphical representation of a faceted thesaurus. It shows how Boolean queries can be lattice-theoretically related to the concepts of the thesaurus and visualized within the thesaurus display. An advantage of FaIR is that it allows for a high level of transparency of the system, which can be controlled by the user

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Abstract

Current best-match ranking (BMR) systems perform well but cannot handle word mismatch between a query and a document. The best known alternative ranking method, hierarchical clustering-based ranking (HCR), seems to be more robust than BMR with respect to this problem, but it is hampered by theoretical and practical limitations. We present an approach to document ranking that explicitly addresses the word mismatch problem by exploiting interdocument similarity information in a novel way. Document ranking is seen as a query-document transformation driven by a conceptual representation of the whole document collection, into which the query is merged. Our approach is nased on the theory of concept (or Galois) lattices, which, er argue, provides a powerful, well-founded, and conputationally-tractable framework to model the space in which documents and query are represented and to compute such a transformation. We compared information retrieval using concept lattice-based ranking (CLR) to BMR and HCR. The results showed that HCR was outperformed by CLR as well as BMR, and suggested that, of the two best methods, BMR achieved better performance than CLR on the whole document set, whereas CLR compared more favorably when only the first retrieved documents were used for evaluation. We also evaluated the three methods' specific ability to rank documents that did not match the query, in which case the speriority of CLR over BMR and HCR was apparent

Source

Journal of the American Society for Information Science. 51(2000) no.7, S.587-601

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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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Source

Computers and mathematics with applications. 23(1992), S.493-515

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Abstract

This paper describes a graphical interface for the navigation and construction of faceted thesauri that is based on formal concept analysis. Each facet of a thesaurus is represented as a mathematical lattice that is further subdivided into components. Users can graphically navigate through the Java implementation of the interface by clicking on terms that connect facets and components. Since there are many applications for thesauri in the knowledge representation field, such a graphical interface has the potential of being very useful

Source

Structures and relations in knowledge organization: Proceedings of the 5th International ISKO-Conference, Lille, 25.-29.8.1998. Ed.: W. Mustafa el Hadi et al