Stumme, G., Wille, R., & Wille U. (1998). Conceptual knowledge discovery in databases using formal concept analysis methods. In J. M. Zytkow, & M. Quafofou (Eds.), Principles of Data Mining and Knowledge Discovery. LNAI 1510. Berlin: Springer, 450-458.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....for ranking the interestingness of generalized relations using DGGs, they are more generally applicable to other problem domains. For example, alternative methods could be used to guide the generation of summaries, such as Galois lattices [6] conceptual graphs [3] or formal concept analysis [19]. Also, summaries could more generally include views generated from databases or summary tables generated from data cubes. However, we do not dwell here on the methods or technical aspects of deriving summaries, views, or summary tables. Instead, we simply refer collectively to these objects as ....

G. Stumme, R. Wille, and U. Wille. Conceptual knowledge discovery in databases using formal concept analysis methods. In J. Zytkow and M. Quafafou, editors, Proceedings of the Second European Conference on the Principles of Data Mining and Knowledge Discovery (PKDD'98), pages 450--458, Nantes, France, September 1998.

....1 1 1 2 1 2 2 1 2 1 1 1 1 1 1 1 2 1 Figure 1. A data cube Of course, numerous methods could be used to guide the generation of summaries, such as concept hierarchies [5] domain generalization graphs [15] Ga lois lattices [9] conceptual graphs [4] and formal concept analysis [22]. Also, summaries could more generally include many other forms of knowledge representation, such as database views, association rules, itemsets, and web search results. However, when given hundreds, or even thousands of summaries (possibly multi dimensional) it is simply not feasible to ....

G. Stumme, R. Wille, and U. Wille. Conceptual knowledge discovery in databases using formal concept analysis methods. In J. Zytkow and M. Quafafou, editors, Proceedings of the Second European Conference on the Principles of Data Mining and Knowledge Discovery (PKDD'98), pages 450--458, Nantes, France, September 1998.

....industrial databases is described in [15, 16] Although this example is based upon summaries generated from databases using AOG and DGGs, alternative methods could be used to guide the generation of summaries. These include Galois lattices [9] conceptual graphs [4] or formal concept analysis [24]. Similarly, summaries could more generally include views generated from databases, characterized generalized association rules generated from itemsets, or summary tables (i.e. data cubes) generated from data warehouses. Regardless of the representation language used to convey the discovered ....

G. Stumme, R. Wille, and U. Wille. Conceptual knowledge discovery in databases using formal concept analysis methods. In J. Zytkow and M. Quafafou, editors, Proceedings of the Second European Conference on the Principles of Data Mining and Knowledge Discovery (PKDD'98), pages 450--458, Nantes, France, September 1998.

....Formale Beschreibungsverfahren (AIFB) Karlsruhe University, D 76128 Karlsruhe, Germany, stumme aifb.uni karlsruhe.de Figure 1. Screenshot of ToscanaJ with nested diagram and highlighting Knowledge Discovery in Databases and the principle ideas underlying TOSCANA systems have been elaborated in [12, 5]. The principle goal of Conceptual Knowledge Discovery (CKDD) is to support a human centered process of knowledge discovery by providing a visualization of the data based on a visualization of underlying conceptual structures. This idea is explained in more detail in [15, 4] Most notably in this ....

Gerd Stumme, Uta Wille, and Rudolf Wille, `Conceptual knowledge discovery in databases using formal concept analysis methods', in Principles of Data Mining and Knowledge Discovery, eds., J. M. Zytkow and M. Quafofou, volume 1510 of Lecture Notes in Computer Science, pp. 450--458. Springer--Verlag, (1998).

.... conceptual clustering [38, 7, 12, 35, 23] a formal framework for implication and association rules discovery and reduction [19, 26, 4, 31] and for improving the response times of algorithms for mining association rules [25, 26, 5] The interaction of FCA and KDD in general has been discussed in [33] and [14] In this paper we present a new approach of conceptual clustering with FCA: iceberg concept lattices. Iceberg concept lattices show only the topmost part of a concept lattice. The extensions of the concepts provide the clusters, and the intensions their descriptions. Beside conceptual ....

G. Stumme, R. Wille, and U. Wille. Conceptual knowledge discovery in databases using formal concept analysis methods. In J. M. Zytkow and M. Quafofou, editors, Principles of Data Mining and Knowledge Discovery. Proc. 2nd European Symposium on PKDD '98, number 1510 in LNAI, pages 450--458, Heidelberg, 1998. Springer.

.... international cooperations [2] for exploring laws and regulations in civil engineering [4] for retrieving books in a library [3] 6] The role of TOSCANA Systems for On Line Analytical Processing (OLAP) and within the Knowledge Discovery in Databases process (KDD) is discussed in [8] and [9]. TOSCANA Systems are developed in an interactive process with a domain expert. In the presentation, we describe this process, analyze and discuss the process with respect to reuse, and illustrate individual steps by means of examples. 2 Reusing conceptual scales in developing TOSCANA Systems ....

Stumme, G., Wille, R., Wille, U.: Conceptual Knowledge Discovery in Databases Using Formal Concept Analysis Methods. In: J. M. Zytkow, M. Quafofou (eds.): Principles of Data Mining and Knowledge Discovery. Proc. 2nd European Symposium, PKDD '98, LNAI 1510, Springer, Heidelberg 1998, 450--458

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Stumme, G., Wille, R., & Wille U. (1998). Conceptual knowledge discovery in databases using formal concept analysis methods. In J. M. Zytkow, & M. Quafofou (Eds.), Principles of Data Mining and Knowledge Discovery. LNAI 1510. Berlin: Springer, 450-458.

No context found.

Stumme G., Wille R., and Wille U., Conceptual Knowledge Discovery in Databases Using Formal Concept Analysis Methods, in Proc. 2 nd European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD'98).

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Stumme, G., Wille, R., Wille, U.: (1998) "Conceptual Knowledge Discovery in DataBases Using Formal Concept Analysis Methods", In: J. M. Zytkow, M. Quafofou (Eds.): Principles of Data Mining and Knowledge Discovery. Proc. 2nd European Symposium on PKDD'98, LNAI 1510, Springer, Heidelberg, pp. 450-458.

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