Formal Concept Analysis and Semantic File Systems

Martin, Ben

doi:10.1007/978-3-540-24651-0_9

Cited by 7 publications

(6 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although using different extensions that K-FCA, the semantic file systems of Ferré (2007) Martin (2004) Martin and Eklund (2005), and the post-retrieval clustering results of Carpineto and Romano (2004) 2005) are also proof of this. Examples of the use of FCA for the bibliographic analysis of different domains can be found in Poelmans et al (2013a) Poelmans et al (2013b).…”

Section: Indexingmentioning

confidence: 91%

“…Most of these activities are expressed in either the main or the secondary domain of the metaphor, like "browsing" in the physical domain, and "analyzing" in the cognitive domain. Note that these metaphors have already been put to the test in the building of semantic file systems (Martin, 2004;Martin & Eklund, 2005) and Logical Information Systems (Ferré, 2007;Ferré & Ridoux, 2001) as Information Retrieval systems. A thorough review of the use of FCA to model knowledge is Poelmans et al (2013b), while applications are detailed in Poelmans et al (2013a).…”

Section: (Formal Conceptual) Landscapes Of Knowledgementioning

confidence: 99%

See 1 more Smart Citation

Supporting scientific knowledge discovery with extended, generalized Formal Concept Analysis

Valverde-Albacete

González-Calabozo

Peñas

et al. 2016

Expert Systems with Applications

View full text Add to dashboard Cite

a b s t r a c tIn this paper we fuse together the Landscapes of Knowledge of Wille's and Exploratory Data Analysis by leveraging Formal Concept Analysis (FCA) to support data-induced scientific enquiry and discovery.We use extended FCA first by allowing K-valued entries in the incidence to accommodate other, non-binary types of data, and second with different modes of creating formal concepts to accommodate diverse conceptualizing phenomena.With these extensions we demonstrate the versatility of the Landscapes of Knowledge metaphor to help in creating new scientific and engineering knowledge by providing several successful use cases of our techniques that support scientific hypothesis-making and discovery in a range of domains: semiring theory, perceptual studies, natural language semantics, and gene expression data analysis.While doing so, we also capture the affordances that justify the use of FCA and its extensions in scientific discovery.

show abstract

Section: Indexingmentioning

confidence: 91%

Section: (Formal Conceptual) Landscapes Of Knowledgementioning

confidence: 99%

Supporting scientific knowledge discovery with extended, generalized Formal Concept Analysis

Valverde-Albacete

González-Calabozo

Peñas

et al. 2016

Expert Systems with Applications

View full text Add to dashboard Cite

show abstract

“…File Systems (FS) are an interesting application in low-level information retrieval (operating system level). FCA provides a more dynamic interaction with the file system structure where the FS can be represented as a lattice instead of a tree [31,48,67] Source code location is an important task in software engineering as it enables code refactoring, among other applications [53,61,1]. Other interesting applications are mathematical expression search [57] and multimedia indexing [49,26].…”

Section: Ranking Documentsmentioning

confidence: 99%

Formal Concept Analysis and Information Retrieval – A Survey

Codocedo

Napoli

2015

Formal Concept Analysis

View full text Add to dashboard Cite

One of the first models to be proposed as a document index for retrieval purposes was a lattice structure, decades before the introduction of Formal Concept Analysis. Nevertheless, the main notions that we consider so familiar within the community ("extension", "intension", "closure operators", "order") were already an important part of it. In the '90s, as FCA was starting to settle as an epistemic community, lattice-based Information Retrieval (IR) systems smoothly transitioned towards FCA-based IR systems. Currently, FCA theory supports dozens of different retrieval applications, ranging from traditional document indices to file systems, recommendation, multi-media and more recently, semantic linked data. In this paper we present a comprehensive study on how FCA has been used to support IR systems. We try to be as exhaustive as possible by reviewing the last 25 years of research as chronicles of the domain, yet we are also concise in relating works by its theoretical foundations. We think that this survey can help future endeavours of establishing FCA as a valuable alternative for modern IR systems.

show abstract

“…This visualisation differs from our research because it does not result in lattices, but in networks, which completely ignore the hierarchical structure of WordNet's relations. WordNet has been used in several Formal Concept Analysis projects for example by Hotho et al (2003) as a means for improving text clustering by exploiting WordNet's semantic relations and by Martin & Eklund (2005) for adding hypernymic concepts in a lattice of a semantic file system. But in these projects both WordNet and FCA are just tools used for other purposes and, again, this kind of research differs from what we are intending to do.…”

Section: Introductionmentioning

confidence: 99%

Concept Neighbourhoods in Lexical Databases

Priss

Old

2010

Formal Concept Analysis

View full text Add to dashboard Cite

Abstract. This paper discusses results from an experimental study of concept neighbourhoods in WordNet and Roget's Thesaurus. The general aim of this research is to determine ways in which neighbourhood lattices can be derived in real time from a lexical database and displayed on the web. In order to be readable the lattices must not be too large, not contain overlapping concepts or labels and must be calculated within seconds. Lattices should, furthermore, not be too small and they should contain sufficient complexity to be interesting for the viewer. For these purposes the sizes of the lattices of different types of concept neighbourhoods have been calculated. Using the size information should help with the task of on-line generation of the lattices.

show abstract

Formal Concept Analysis and Semantic File Systems

Abstract: , is wholly my own work unless otherwise referenced or acknowledged. The document has not been submitted for qualifications at any other academic institution.

Cited by 7 publications

References 8 publications

Supporting scientific knowledge discovery with extended, generalized Formal Concept Analysis

Supporting scientific knowledge discovery with extended, generalized Formal Concept Analysis

Formal Concept Analysis and Information Retrieval – A Survey

Concept Neighbourhoods in Lexical Databases

Contact Info

Product

Resources

About