Search (13 results, page 1 of 1)

0.034876935 = product of:
  0.06975387 = sum of:
    0.022872243 = weight(_text_:world in 5089) [ClassicSimilarity], result of:
      0.022872243 = score(doc=5089,freq=2.0), product of:
        0.1538826 = queryWeight, product of:
          3.8436708 = idf(docFreq=2573, maxDocs=44218)
          0.04003532 = queryNorm
        0.14863437 = fieldWeight in 5089, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.8436708 = idf(docFreq=2573, maxDocs=44218)
          0.02734375 = fieldNorm(doc=5089)
    0.030392924 = weight(_text_:wide in 5089) [ClassicSimilarity], result of:
      0.030392924 = score(doc=5089,freq=2.0), product of:
        0.17738682 = queryWeight, product of:
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.04003532 = queryNorm
        0.171337 = fieldWeight in 5089, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.02734375 = fieldNorm(doc=5089)
    0.0164887 = weight(_text_:web in 5089) [ClassicSimilarity], result of:
      0.0164887 = score(doc=5089,freq=2.0), product of:
        0.13065568 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.04003532 = queryNorm
        0.12619963 = fieldWeight in 5089, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.02734375 = fieldNorm(doc=5089)
  0.5 = coord(3/6)

Abstract

The 8th International Conference on Conceptual Structures - Logical, Linguistic, and Computational Issues (ICCS 2000) brings together a wide range of researchers and practitioners working with conceptual structures. During the last few years, the ICCS conference series has considerably widened its scope on different kinds of conceptual structures, stimulating research across domain boundaries. We hope that this stimulation is further enhanced by ICCS 2000 joining the long tradition of conferences in Darmstadt with extensive, lively discussions. This volume consists of contributions presented at ICCS 2000, complementing the volume "Conceptual Structures: Logical, Linguistic, and Computational Issues" (B. Ganter, G.W. Mineau (Eds.), LNAI 1867, Springer, Berlin-Heidelberg 2000). It contains submissions reviewed by the program committee, and position papers. We wish to express our appreciation to all the authors of submitted papers, to the general chair, the program chair, the editorial board, the program committee, and to the additional reviewers for making ICCS 2000 a valuable contribution in the knowledge processing research field. Special thanks go to the local organizers for making the conference an enjoyable and inspiring event. We are grateful to Darmstadt University of Technology, the Ernst Schröder Center for Conceptual Knowledge Processing, the Center for Interdisciplinary Studies in Technology, the Deutsche Forschungsgemeinschaft, Land Hessen, and NaviCon GmbH for their generous support

Content

Concepts & Language: Knowledge organization by procedures of natural language processing. A case study using the method GABEK (J. Zelger, J. Gadner) - Computer aided narrative analysis using conceptual graphs (H. Schärfe, P. 0hrstrom) - Pragmatic representation of argumentative text: a challenge for the conceptual graph approach (H. Irandoust, B. Moulin) - Conceptual graphs as a knowledge representation core in a complex language learning environment (G. Angelova, A. Nenkova, S. Boycheva, T. Nikolov) - Conceptual Modeling and Ontologies: Relationships and actions in conceptual categories (Ch. Landauer, K.L. Bellman) - Concept approximations for formal concept analysis (J. Saquer, J.S. Deogun) - Faceted information representation (U. Priß) - Simple concept graphs with universal quantifiers (J. Tappe) - A framework for comparing methods for using or reusing multiple ontologies in an application (J. van ZyI, D. Corbett) - Designing task/method knowledge-based systems with conceptual graphs (M. Leclère, F.Trichet, Ch. Choquet) - A logical ontology (J. Farkas, J. Sarbo) - Algorithms and Tools: Fast concept analysis (Ch. Lindig) - A framework for conceptual graph unification (D. Corbett) - Visual CP representation of knowledge (H.D. Pfeiffer, R.T. Hartley) - Maximal isojoin for representing software textual specifications and detecting semantic anomalies (Th. Charnois) - Troika: using grids, lattices and graphs in knowledge acquisition (H.S. Delugach, B.E. Lampkin) - Open world theorem prover for conceptual graphs (J.E. Heaton, P. Kocura) - NetCare: a practical conceptual graphs software tool (S. Polovina, D. Strang) - CGWorld - a web based workbench for conceptual graphs management and applications (P. Dobrev, K. Toutanova) - Position papers: The edition project: Peirce's existential graphs (R. Mülller) - Mining association rules using formal concept analysis (N. Pasquier) - Contextual logic summary (R Wille) - Information channels and conceptual scaling (K.E. Wolff) - Spatial concepts - a rule exploration (S. Rudolph) - The TEXT-TO-ONTO learning environment (A. Mädche, St. Staab) - Controlling the semantics of metadata on audio-visual documents using ontologies (Th. Dechilly, B. Bachimont) - Building the ontological foundations of a terminology from natural language to conceptual graphs with Ribosome, a knowledge extraction system (Ch. Jacquelinet, A. Burgun) - CharGer: some lessons learned and new directions (H.S. Delugach) - Knowledge management using conceptual graphs (W.K. Pun)

0.029389432 = product of:
  0.08816829 = sum of:
    0.03920956 = weight(_text_:world in 2737) [ClassicSimilarity], result of:
      0.03920956 = score(doc=2737,freq=2.0), product of:
        0.1538826 = queryWeight, product of:
          3.8436708 = idf(docFreq=2573, maxDocs=44218)
          0.04003532 = queryNorm
        0.25480178 = fieldWeight in 2737, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.8436708 = idf(docFreq=2573, maxDocs=44218)
          0.046875 = fieldNorm(doc=2737)
    0.048958737 = weight(_text_:web in 2737) [ClassicSimilarity], result of:
      0.048958737 = score(doc=2737,freq=6.0), product of:
        0.13065568 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.04003532 = queryNorm
        0.37471575 = fieldWeight in 2737, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.046875 = fieldNorm(doc=2737)
  0.33333334 = coord(2/6)

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.

0.011578257 = product of:
  0.06946954 = sum of:
    0.06946954 = weight(_text_:wide in 2204) [ClassicSimilarity], result of:
      0.06946954 = score(doc=2204,freq=2.0), product of:
        0.17738682 = queryWeight, product of:
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.04003532 = queryNorm
        0.3916274 = fieldWeight in 2204, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.0625 = fieldNorm(doc=2204)
  0.16666667 = coord(1/6)

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

0.010891545 = product of:
  0.065349266 = sum of:
    0.065349266 = weight(_text_:world in 5908) [ClassicSimilarity], result of:
      0.065349266 = score(doc=5908,freq=2.0), product of:
        0.1538826 = queryWeight, product of:
          3.8436708 = idf(docFreq=2573, maxDocs=44218)
          0.04003532 = queryNorm
        0.42466965 = fieldWeight in 5908, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.8436708 = idf(docFreq=2573, maxDocs=44218)
          0.078125 = fieldNorm(doc=5908)
  0.16666667 = coord(1/6)

0.008309524 = product of:
  0.04985714 = sum of:
    0.04985714 = weight(_text_:web in 2470) [ClassicSimilarity], result of:
      0.04985714 = score(doc=2470,freq=14.0), product of:
        0.13065568 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.04003532 = queryNorm
        0.38159183 = fieldWeight in 2470, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.03125 = fieldNorm(doc=2470)
  0.16666667 = coord(1/6)

Abstract

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.

0.007693123 = product of:
  0.04615874 = sum of:
    0.04615874 = weight(_text_:web in 3291) [ClassicSimilarity], result of:
      0.04615874 = score(doc=3291,freq=12.0), product of:
        0.13065568 = queryWeight, product of:
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.04003532 = queryNorm
        0.35328537 = fieldWeight in 3291, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          3.2635105 = idf(docFreq=4597, maxDocs=44218)
          0.03125 = fieldNorm(doc=3291)
  0.16666667 = coord(1/6)

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.

0.007236411 = product of:
  0.043418463 = sum of:
    0.043418463 = weight(_text_:wide in 5083) [ClassicSimilarity], result of:
      0.043418463 = score(doc=5083,freq=2.0), product of:
        0.17738682 = queryWeight, product of:
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.04003532 = queryNorm
        0.24476713 = fieldWeight in 5083, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.4307585 = idf(docFreq=1430, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5083)
  0.16666667 = coord(1/6)

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

0.0054457723 = product of:
  0.032674633 = sum of:
    0.032674633 = weight(_text_:world in 4843) [ClassicSimilarity], result of:
      0.032674633 = score(doc=4843,freq=2.0), product of:
        0.1538826 = queryWeight, product of:
          3.8436708 = idf(docFreq=2573, maxDocs=44218)
          0.04003532 = queryNorm
        0.21233483 = fieldWeight in 4843, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.8436708 = idf(docFreq=2573, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4843)
  0.16666667 = coord(1/6)

Abstract

Formal Concept Analysis (FCA) is a well founded mathematical framework used for conceptual classication and knowledge management. Given a binary table describing a relation between objects and attributes, FCA consists in building a set of concepts organized by a subsumption relation within a concept lattice. Accordingly, FCA requires to transform complex data, e.g. numbers, intervals, graphs, into binary data leading to loss of information and poor interpretability of object classes. In this paper, we propose a pre-processing method producing binary data from complex data taking advantage of similarity between objects. As a result, the concept lattice is composed of classes being maximal sets of pairwise similar objects. This method is based on FCA and on a formalization of similarity as a tolerance relation (reexive and symmetric). It applies to complex object descriptions and especially here to interval data. Moreover, it can be applied to any kind of structured data for which a similarity can be dened (sequences, graphs, etc.). Finally, an application highlights that the resulting concept lattice plays an important role in information fusion problem, as illustrated with a real-world example in agronomy.

0.0048653074 = product of:
  0.029191844 = sum of:
    0.029191844 = product of:
      0.08757553 = sum of:
        0.08757553 = weight(_text_:29 in 4305) [ClassicSimilarity], result of:
          0.08757553 = score(doc=4305,freq=2.0), product of:
            0.14083174 = queryWeight, product of:
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.04003532 = queryNorm
            0.6218451 = fieldWeight in 4305, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5176873 = idf(docFreq=3565, maxDocs=44218)
              0.125 = fieldNorm(doc=4305)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date

13. 7.2008 19:29:59

0.0030134628 = product of:
  0.018080777 = sum of:
    0.018080777 = product of:
      0.054242328 = sum of:
        0.054242328 = weight(_text_:22 in 3142) [ClassicSimilarity], result of:
          0.054242328 = score(doc=3142,freq=2.0), product of:
            0.14019686 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.04003532 = queryNorm
            0.38690117 = fieldWeight in 3142, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.078125 = fieldNorm(doc=3142)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date

26. 2.2008 15:58:22

0.0024107702 = product of:
  0.0144646205 = sum of:
    0.0144646205 = product of:
      0.04339386 = sum of:
        0.04339386 = weight(_text_:22 in 1901) [ClassicSimilarity], result of:
          0.04339386 = score(doc=1901,freq=2.0), product of:
            0.14019686 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.04003532 = queryNorm
            0.30952093 = fieldWeight in 1901, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0625 = fieldNorm(doc=1901)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Source

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

0.002109424 = product of:
  0.012656543 = sum of:
    0.012656543 = product of:
      0.03796963 = sum of:
        0.03796963 = weight(_text_:22 in 5095) [ClassicSimilarity], result of:
          0.03796963 = score(doc=5095,freq=2.0), product of:
            0.14019686 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.04003532 = queryNorm
            0.2708308 = fieldWeight in 5095, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5095)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date

22. 1.2016 17:47:06

0.002109424 = product of:
  0.012656543 = sum of:
    0.012656543 = product of:
      0.03796963 = sum of:
        0.03796963 = weight(_text_:22 in 2654) [ClassicSimilarity], result of:
          0.03796963 = score(doc=2654,freq=2.0), product of:
            0.14019686 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.04003532 = queryNorm
            0.2708308 = fieldWeight in 2654, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2654)
      0.33333334 = coord(1/3)
  0.16666667 = coord(1/6)

Date

22. 1.2016 17:30:31