Richard J. Cole

CEM - A Conceptual Email Manager

CEM is an email management system which stores its email in a concept lattice rather than in the usual tree structure. By using such a conceptual multi-hierarchy, the system provides more flexibility in retrieving stored emails. The paper presents the underlying mathematical structures, discusses requirements for their maintenance and presents their implementation.

Browsing Semi-structured Web Texts Using Formal Concept Analysis

Query-directed browsing of unstructured Web-texts using Formal Concept Analysis (FCA) confronts two problems. Firstly on-line Web-data is sometimes unstructured and any FCA-system must include additional mechanisms to structure input sources. Secondly many online collections are large and dynamic so a Web-robot must be used to automatically extract data. These issues are addressed in this paper. We report on the construction of a Web-based FCA system for browsing classified advertisements for real-estate properties. Real-estate advertisements were chosen because they are typical of semi-structured textual information sources accessible on the Web. Furthermore, the analysis of real-estate data using FCA is a classic example used in introductory courses on FCA. However, unlike the classic FCA real-estate example, whose input is a structure relational database, we automatically mine Web-based texts for their structure.

Scalability in Formal Concept Analysis

Formal Concept Analysis is a symbolic learning technique derived from mathematical algebra and order theory. The technique has been applied to a broad range of knowledge representation and exploration tasks in a number of domains. Most recorded applications of Formal Concept Analysis deal with a small number of objects and attributes, in which case the complexity of the algorithms used for indexing and retrieving data is not a significant issue. However, when Formal Concept Analysis is applied to exploration of a large numbers of objects and attributes, the size of the data makes issues of complexity and scalability crucial.

Analyzing an Email Collection Using Formal Concept Analysis

We demonstrate the use of a data analysis technique called formal concept analysis (FCA) to explore information stored in a set of email documents. The user extends a pre-defined taxonomy of classifiers, designed to extract information from email documents with her own specialized classifiers. The classifiers extract information both from (i) the email headers providing structured information such as the date received, from:, to: and cc: lists, (ii) the email body containing free English text, and (iii) conjunctions of the two sources.

CEM - A Program for Visualization and Discovery in Email

This paper presents a lattice metaphor for knowledge discovery in electronic mail. It allows a user to navigate email using a lattice rather than a tree structure. By using such a conceptual multi-hierarchy, the content and shape of the lattice can be varied to accommodate queries against the email collection. This paper presents the underlying mathematical structures, and a number of examples of the lattice and multi-hierarchy working with a prototypical email collection.

Automated layout of concept lattices using layered diagrams and additive diagrams

Drawings of concept lattices provide the most common mechanism for the communication of structure extracted from data via the process of formal concept analysis. To communicate structure, diagrams of concept lattices are usually made to be additive. Additive diagrams, however, suffer from some unaesthetic properties. Alternatively a common graph drawing approach to the layout of partially ordered sets (of which lattices are a sub-class) is via a layered diagram. The paper presents a mechanism for the layout of concept lattices that combines ideas from both additive and layered diagrams. These new hybrid diagrams preserve the structural aspects of additive diagrams while achieving the aesthetic quality of layered diagrams. Furthermore, a search method is presented that optimizes the layout with respect to structural and aesthetic objective functions.

Automated layout of concept lattices using force directed placement and genetic algorithms

Concept lattices represent a conceptual hierarchy inherent in a data set. A labelled line diagram for such a lattice represents this information diagramatically. A diagram for a concept lattice may be algebraically generated by a set of vectors assigned to elements of the lattice. Such a diagram is called an additive line diagram, and is considered useful because it makes apparent the inherent structure of the lattice. This paper reports on experience with two approaches to automated concept lattice layout. (i) using generic algorithms optimising over a finite discrete space of diagrams, and (ii) force directed placement optimising over a continuous rational space. The layout of concept lattices is of relevance to the layout of lattices in general since any lattice can be represented simply by a concept lattice.