Conceptual knowledge discovery with frequent concept lattices

Knowledge discovery support environments include beside classical data analysis tools also data mining tools. For supporting both kinds of tools, a unified knowledge representation is needed. We show that concept lattices which are used as knowledge representation in Conceptual Information Systems can also be used for structuring the results of mining association rules. Vice versa, we use ideas of association rules for reducing the complexity of the visualization of Conceptual Information Systems.

CEM - visualization and discovery in Email

This paper presents a lattice-based visual metaphor for knowledge discovery in electronic mail. It allows a user to navigate email using a visual lattice metaphor rather than a tree structure. By using such a conceptual multi-hierarchy, the content and shape of the lattice can be varied to accommodate any number of queries against the email collection. The system provides more flexibility in retrieving stored emails and can be generalised to any electronic documents. The paper presents the underlying mathematical structures, and a number of examples of the lattice and multi-hierarchy working with a prototypical email collection.

Prognosemethode für das Schutzgut ‚Landschaft’ im Rahmen der Strategischen Umweltprüfung

Im Mittelpunkt der Dissertation stehen das Schutzgut ‚Landschaft’ sowie ‚Prognosemethoden in der Umweltprüfung’. Mit beiden Themenbereichen verbinden sich bereits heute ungelöste methodische Probleme, die mit der Umsetzung der Richtlinie zur Strategischen Umweltprüfung (SUP) zusätzlich komplexer und deren Lösung mithin anspruchsvoller werden. Dies hängt einerseits damit zusammen, dass eine gesetzeskonforme Gleichbehandlung aller Schutzgüter zunehmend eingefordert wird und gerade das Schutzgut ‚Landschaft’ in einer SUP methodisch besondere Aufmerksamkeit verlangt. Zum anderen führt die gängige planungsmethodische Diskussion allein nicht zu geeigneten Antworten auf o.g. Fragen, und es bedarf der Prüfung verschiedener Methodenbausteine, auch aus anderen Wissensgebieten, um – über ein eindimensionales Landschaftsverständnis einerseits und die bisher bekannten linearen Wirkungsprognosen andererseits hinaus gehend – mehrfach verknüpfte Prognoseschritte zur Anwendung in der SUP zu entwickeln, in denen das Schutzgut ‚Landschaft’ modellhaft für Bewertungsschritte nachvollziehbar abgebildet wird. Hierbei müssen entscheidungsrelevante Prognosezeiträume ebenso beachtet werden, wie in diesen Zeiträumen möglicherweise auftretende sekundäre, kumulative, synergetische, positive und negative Auswirkungen der zu beurteilenden Planung. Dieser Ziel- und Aufgabenstellung entsprechend erfolgt die theoretische Herangehensweise der Arbeit von zwei Seiten: 1. Die Funktionen und Stellung von Prognosen innerhalb der SUP wird erläutert (Kap. 2), und es wird der Frage nachgegangen, welche Anforderungen an Prognosemethoden zu stellen sind (Kap. 2.4) und welche Prognosemethoden in der SUP Verwendung finden bzw. finden können (Kap. 3). Der Schwerpunkt wird dabei auf die Anwendung der Szenariotechnik gelegt. 2. Es wird dargestellt wie Landschaft für Aufgaben der Landschaftsplanung und Umweltprüfung bisher üblicherweise erfasst und analysiert wird, um in Prognoseschritten handhabbar behandelt zu werden (Kap. 4). Beide Zugänge werden sodann zusammengeführt (Kap. 5), um am Beispiel einer Hochwasserschutzkonzeption im Rahmen der SUP Landschaftliche Prognosen zu erarbeiten. Die Prognose setzt methodisch mit der Beschreibung des zu verwendenden Landschaftsmodells und der Klärung des Modellzwecks ein. Bezugsbasis ist die Beschreibung des Charakters einzelner logisch hergeleiteter Landschaftseinheiten bzw. Landschaftsräume, die typisiert werden. Die Prognose selber unterscheidet zwischen der Abschätzung zu erwartender Landschaftsveränderungen im Sinne der ‚Status-quo-Prognose’ (einschließlich der Entwicklung von drei Szenarien möglicher Zukunftslandschaften bis 2030) und der Wirkungsabschätzungen verschiedener Maßnahmen bzw. Planungsalternativen und zwar zunächst raumunabhängig, und dann raumkonkret. Besondere Bedeutung bei den Wirkungsabschätzungen erhält die klare Trennung von Sach- und Wertebene, eine angemessene Visualisierung und die Dokumentation von Informationslücken und Unsicherheiten bei der Prognose. Diskutiert wird u.a. (Kap. 6) · die Bildung und Abgrenzung landschaftlicher Einheiten und Typen in Bezug zu der Aufgabe, landschaftliche Eigenart zu definieren und planerisch handhabbar und anwendbar zu bestimmen, · die Bedeutung angemessener Visualisierung zur Unterstützung von Beteiligungsverfahren und · die Bestimmung des so genannten ‚Raumwiderstandes’. Beigefügt sind zwei Karten des gesamten Bearbeitungsgebietes: Karte 1 „Landschaftstypen“, Karte 2 „Maßnahmentypen des Hochwasserschutzes mit möglichen Synergieeffekten für die Landschaft“.

Uncover the Concealed Link: Gender & Ethnicity-Divided Local Knowledge on the Agro-Ecosystem of a Forest Margin

This research is a study about knowledge interface that aims to analyse knowledge discontinuities, the dynamic and emergent characters of struggles and interactions within gender system and ethnicity differences. The cacao boom phenomenon in Central Sulawesi is the main context for a changing of social relations of production, especially when the mode of production has shifted or is still underway from subsistence to petty commodity production. This agrarian change is not only about a change of relationship and practice, but, as my previous research has shown, also about the shift of knowledge domination, because knowledge construes social practice in a dialectical process. Agroecological knowledge is accumulated through interaction, practice and experience. At the same time the knowledge gained from new practices and experiences changes mode of interaction, so such processes provide the arena where an interface of knowledge is manifested. In the process of agro-ecological knowledge interface, gender and ethnic group interactions materialise in the decision-making of production and resource allocation at the household and community level. At this point, power/knowledge is interplayed to gain authority in decision-making. When authority dominates, power encounters resistance, whereas the dominant power and its resistance are aimed to ensure socio-economic security. Eventually, the process of struggle can be identified through the pattern of resource utilisation as a realisation of production decision-making. Such processes are varied from one community to another, and therefore, it shows uniqueness and commonalities, especially when it is placed in a context of shifting mode of production. The focus is placed on actors: men and women in their institutional and cultural setting, including the role of development agents. The inquiry is informed by 4 major questions: 1) How do women and men acquire, disseminate, and utilise their agro ecological knowledge, specifically in rice farming as a subsistence commodity, as well as in cacao farming as a petty commodity? How and why do such mechanisms construct different knowledge domains between two genders? How does the knowledge mechanism apply in different ethnics? What are the implications for gender and ethnicity based relation of production? ; 2) Using the concept of valued knowledge in a shifting mode of production context: is there any knowledge that dominates others? How does the process of domination occur and why? Is there any form of struggle, strategies, negotiation, and compromise over this domination? How do these processes take place at a household as well as community level? How does it relate to production decision-making? ; 3) Putting the previous questions in two communities with a different point of arrival on a path of agricultural commercialisation, how do the processes of struggle vary? What are the bases of the commonalities and peculiarities in both communities?; 4) How the decisions of production affect rice field - cacao plantation - forest utilisation in the two villages? How does that triangle of resource use reflect the constellation of local knowledge in those two communities? What is the implication of this knowledge constellation for the cacao-rice-forest agroecosystem in the forest margin area? Employing a qualitative approach as the main method of inquiry, indepth and dialogic interviews, participant observer role, and document review are used to gather information. A small survey and children’s writing competition are supplementary to this data collection method. The later two methods are aimed to give wider information on household decision making and perception toward the forest. It was found that local knowledge, particularly knowledge pertaining to rice-forest-cacao agroecology is divided according to gender and ethnicity. This constellation places a process of decision-making as ‘the arena of interface’ between feminine and masculine knowledge, as well as between dominant and less dominant ethnic groups. Transition from subsistence to a commercial mode of production is a context that frames a process where knowledge about cacao commodity is valued higher than rice. Market mechanism, as an external power, defines valued knowledge. Valued knowledge defines the dominant knowledge holder, and decision. Therefore, cacao cultivation becomes a dominant practice. Its existence sacrifices the presence of rice field and the forest. Knowledge about rice production and forest ecosystem exist, but is less valued. So it is unable to challenge the domination of cacao. Various forms of struggles - within gender an ethnicity context - to resist cacao domination are an expression of unequal knowledge possession. Knowledge inequality implies to unequal access to withdraw benefit from market valued crop. When unequal knowledge fails to construct a negotiated field or struggles fail to reveal ‘marginal’ decision, e.g. intensification instead of cacao expansion to the forest, interface only produces divergence. Gender and ethnicity divided knowledge is unabridged, since negotiation is unable to produce new knowledge that accommodates both interests. Rice is loaded by ecological interest to conserve the forest, while cacao is driven by economic interest to increase welfare status. The implication of this unmediated dominant knowledge of cacao production is the construction of access; access to the forest, mainly to withdraw its economic benefit by eliminating its ecological benefit. Then, access to cacao as the social relationship of production to acquire cacao knowledge; lastly, access to defend sustainable benefit from cacao by expansion. ‘Socio-economic Security’ is defined by Access. The convergence of rice and cacao knowledge, however, should be made possible across gender and ethnicity, not only for the sake of forest conservation as the insurance of ecological security, but also for community’s socio-economic security. The convergence might be found in a range of alternative ways to conduct cacao sustainable production, from agroforestry system to intensification.

Hierarchies of conceptual scales

Formal Concept Analysis allows to derive conceptual hierarchies from data tables. Formal Concept Analysis is applied in various domains, e.g., data analysis, information retrieval, and knowledge discovery in databases. In order to deal with increasing sizes of the data tables (and to allow more complex data structures than just binary attributes), conceputal scales habe been developed. They are considered as metadata which structure the data conceptually. But in large applications, the number of conceptual scales increases as well. Techniques are needed which support the navigation of the user also on this meta-level of conceptual scales. In this paper, we attack this problem by extending the set of scales by hierarchically ordered higher level scales and by introducing a visualization technique called nested scaling. We extend the two-level architecture of Formal Concept Analysis (the data table plus one level of conceptual scales) to many-level architecture with a cascading system of conceptual scales. The approach also allows to use representation techniques of Formal Concept Analysis for the visualization of thesauri and ontologies.

Acquiring expert knowledge for the design of conceptual information systems

Conceptual Information Systems unfold the conceptual structure of data stored in relational databases. In the design phase of the system, conceptual hierarchies have to be created which describe different aspects of the data. In this paper, we describe two principal ways of designing such conceptual hierarchies, data driven design and theory driven design and discuss advantages and drawbacks. The central part of the paper shows how Attribute Exploration, a knowledge acquisition tool developped by B. Ganter can be applied for narrowing the gap between both approaches.

Dual retrieval in conceptual information systems

Conceptual Information Systems provide a multi-dimensional conceptually structured view on data stored in relational databases. On restricting the expressiveness of the retrieval language, they allow the visualization of sets of realted queries in conceptual hierarchies, hence supporting the search of something one does not have a precise description, but only a vague idea of. Information Retrieval is considered as the process of finding specific objects (documents etc.) out of a large set of objects which fit to some description. In some data analysis and knowledge discovery applications, the dual task is of interest: The analyst needs to determine, for a subset of objects, a description for this subset. In this paper we discuss how Conceptual Information Systems can be extended to support also the second task.

Conceptual knowledge discovery and data analysis

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.

Efficient data mining based on formal concept analysis

Formal Concept Analysis is an unsupervised learning technique for conceptual clustering. We introduce the notion of iceberg concept lattices and show their use in Knowledge Discovery in Databases (KDD). Iceberg lattices are designed for analyzing very large databases. In particular they serve as a condensed representation of frequent patterns as known from association rule mining. In order to show the interplay between Formal Concept Analysis and association rule mining, we discuss the algorithm TITANIC. We show that iceberg concept lattices are a starting point for computing condensed sets of association rules without loss of information, and are a visualization method for the resulting rules.

Off to new shores

In the last years, the main orientation of Formal Concept Analysis (FCA) has turned from mathematics towards computer science. This article provides a review of this new orientation and analyzes why and how FCA and computer science attracted each other. It discusses FCA as a knowledge representation formalism using five knowledge representation principles provided by Davis, Shrobe, and Szolovits [DSS93]. It then studies how and why mathematics-based researchers got attracted by computer science. We will argue for continuing this trend by integrating the two research areas FCA and Ontology Engineering. The second part of the article discusses three lines of research which witness the new orientation of Formal Concept Analysis: FCA as a conceptual clustering technique and its application for supporting the merging of ontologies; the efficient computation of association rules and the structuring of the results; and the visualization and management of conceptual hierarchies and ontologies including its application in an email management system.

Conceptual knowledge processing with formal concept analysis and ontologies

Among many other knowledge representations formalisms, Ontologies and Formal Concept Analysis (FCA) aim at modeling ‘concepts’. We discuss how these two formalisms may complement another from an application point of view. In particular, we will see how FCA can be used to support Ontology Engineering, and how ontologies can be exploited in FCA applications. The interplay of FCA and ontologies is studied along the life cycle of an ontology: (i) FCA can support the building of the ontology as a learning technique. (ii) The established ontology can be analyzed and navigated by using techniques of FCA. (iii) Last but not least, the ontology may be used to improve an FCA application.