Skip to Main content Skip to Navigation

On-demand Relational Concept Analysis

Abstract : Formal Concept Analysis and its associated conceptual structures have been used to support exploratory search through conceptual navigation. Relational Concept Analysis (RCA) is an extension of Formal Concept Analysis to process relational datasets. RCA and its multiple interconnected structures represent good candidates to support exploratory search in relational datasets, as they are enabling navigation within a structure as well as between the connected structures. However, building the entire structures does not present an efficient solution to explore a small localised area of the dataset, for instance to retrieve the closest alternatives to a given query. In these cases, generating only a concept and its neighbour concepts at each navigation step appears as a less costly alternative. In this paper, we propose an algorithm to compute a concept and its neighbourhood in extended concept lattices. The concepts are generated directly from the relational context family, and possess both formal and relational attributes. The algorithm takes into account two RCA scaling operators. We illustrate it on an example.
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-01735865
Contributor : Giacomo Kahn <>
Submitted on : Wednesday, March 21, 2018 - 10:43:02 AM
Last modification on : Wednesday, March 4, 2020 - 12:28:03 PM
Document(s) archivé(s) le : Tuesday, September 11, 2018 - 7:25:55 AM

Files

cla2018rca.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01735865, version 1
  • ARXIV : 1803.07847

Citation

Alexandre Bazin, Jessie Carbonnel, Marianne Huchard, Giacomo Kahn. On-demand Relational Concept Analysis. 2018. ⟨hal-01735865⟩

Share

Metrics

Record views

333

Files downloads

204