Navigating Context, Pathways and Relationships in Museum Collections using Formal Concept Analysis

The digital medium allows visitors, curators and art historians to gain new insights into their collections through data analysis and rich, interactive visualizations. Motivated by the rise of large-scale cultural heritage collections that have emerged on the Web, we argue that Formal Concept Analysis can be used to highlight the relationships between objects and their features within digital art collections and provide a means for visitors to explore these collections via interactive, narrated pathways. Our work presents four research projects that span 10 years from 2005 - 2015 – ImageSleuth, The Virtual Museum of the Pacific, A Place for Art and a scalability study of Formal Concept Analysis as applied to a data-set from the Brooklyn Museum. Our approach is based on the idea that much of the meaning that can be interpreted from museum collections lies – at least in part – in the way that objects are related to one another. Our work examines how Formal Concept Analysis can drive explorative, narrative-based visitor experiences and reveal new insights into cultural heritage collections

Automated layout of small lattices using layer diagrams

Good quality concept lattice drawings are required to effectively communicate logical structure in Formal Concept Analysis. Data analysis frameworks such as the Toscana System use manually arranged concept lattices to avoid the problem of automatically producing high quality lattices. This limits Toscana systems to a finite number of concept lattices that have been prepared a priori. To extend the use of formal concept analysis, automated techniques are required that can produce high quality concept lattice drawings on demand. This paper proposes and evaluates an adaption of layer diagrams to improve automated lattice drawing. © Springer-Verlag Berlin Heidelberg 2006

Evaluation of concept lattices in a web-based mail browser

Concept lattices assist human understanding in three ways: firstly, by collecting formal concepts that contain maximal sets of objects with shared attributes; secondly, the relatedness of concepts is revealed by providing a hierarchy of formal concepts in the information space. Finally, the concept lattice (drawn as a line diagram) reveals inferences that can automatically derive association rules. Therefore, a major hypothesis of the application of concept lattices is that they visually assist in understanding the structure of information contained within an information space. However, there has been little in the way of empirical tests to substantiate this hypothesis. This paper describes the process and results of a usability evaluation for a program called Mail-Strainer, a Web-based variant of the Mail-Sleuth program, which in turn is based on the Conceptual Email Manager (Cem)

Cubes of Concepts: Multi-Dimensional Exploration of Multi-Valued Contexts

Abstract. A number of information systems offer a limited exploration in that users can only navigate from one object to another object, e.g. navigating from folder to folder in file systems, or from page to page on the Web. An advantage of conceptual information systems is to provide navigation from concept to concept, and therefore from set of objects to set of objects. The main contribution of this paper is to push the exploration capability one step further, by providing navigation from set of concepts to set of concepts. Those sets of concepts are structured along a number of dimensions, thus forming a cube of concepts. We describe a number of representations of concepts, such as sets of objects, multisets of values, and aggregated values. We apply our approach to multi-valued contexts, which stand at an intermediate position between many-valued contexts and logical contexts. We explain how users can navigate from one cube of concepts to another. We show that this navigation includes and extends both conceptual navigation and OLAP operations on cubes

Conceptual Navigation in RDF Graphs with SPARQL-Like Queries

International audienceConcept lattices have been successfully used for information retrieval and browsing. They offer the advantage of combining querying and navigation in a consistent way. Conceptual navigation is more flexible than hierarchical navigation, and easier to use than plain querying. It has already been applied to formal, logical, and relational contexts, but its application to the semantic web is a challenge because of inference mechanisms and expressive query languages such as SPARQL. The contribution of this paper is to extend conceptual navigation to the browsing of RDF graphs, where concepts are accessed through SPARQL-like queries. This extended conceptual navigation is proved consistent w.r.t. the context (i.e., never leads to an empty result set), and complete w.r.t. the conjunctive fragment of the query language (i.e., every query can be reached by navigation only). Our query language has an expressivity similar to SPARQL, and has a more natural syntax close to description logics

Formal Concept Analysis in Knowledge Discovery: A Survey

In this paper, we analyze the literature on Formal Concept Analysis (FCA) using FCA. We collected 702 papers published between 2003-2009 mentioning Formal Concept Analysis in the abstract. We developed a knowledge browsing environment to support our literature analysis process. The pdf-files containing the papers were converted to plain text and indexed by Lucene using a thesaurus containing terms related to FCA research. We use the visualization capabilities of FCA to explore the literature, to discover and conceptually represent the main research topics in the FCA community. As a case study, we zoom in on the 140 papers on using FCA in knowledge discovery and data mining and give an extensive overview of the contents of this literature.status: publishe