An Intelligent User Interface for Browsing and Searching MPEG-7 Images Using Concept Lattices

Ducrou, Jon; Eklund, Peter; Wilson, Tim

doi:10.1007/978-3-540-78921-5_1

Cited by 20 publications

(26 citation statements)

References 10 publications

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“…Visualisations can also be restricted to portions of the data [5], and concept size reduction is possible by incorporating conditions into the data mining process [6]. Finally, conceptual measures can be applied to identify the most relevant concepts and filter outliers [7].…”

Section: Visual Representation Of Concept Latticesmentioning

confidence: 99%

Extracting and Visualising Tree-like Structures from Concept Lattices

Melo¹,

Le-Grand²,

Aufaure³

et al. 2011

2011 15th International Conference on Information Visualisation

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Section: Visual Representation Of Concept Latticesmentioning

confidence: 99%

Extracting and Visualising Tree-like Structures from Concept Lattices

Melo¹,

Le-Grand²,

Aufaure³

et al. 2011

2011 15th International Conference on Information Visualisation

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“…Conceptual navigation [14,3,15,6,7] overcomes the first three limitations by relying on Formal Concept Analysis (FCA) [13]. Users navigate from concept to concept, and hence from set of objects to set of objects.…”

Section: Introductionmentioning

confidence: 99%

Cubes of Concepts: Multi-dimensional Exploration of Multi-valued Contexts

Ferré

Allard

Ridoux

2012

Formal Concept Analysis

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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.

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“…Conceptual navigation, based on Formal Concept Analysis (FCA) [GW99], also supports exploratory search by guiding users from concept to concept [CR96,DE08,Fer09]. The concept lattice plays the role of an exploration space, where each concept can be reached either by entering a query, or by following navigation links between concepts.…”

Section: Introductionmentioning

confidence: 99%

Conceptual Navigation in RDF Graphs with SPARQL-Like Queries

Ferré

2010

Formal Concept Analysis

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Concept 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.

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An Intelligent User Interface for Browsing and Searching MPEG-7 Images Using Concept Lattices

Cited by 20 publications

References 10 publications

Extracting and Visualising Tree-like Structures from Concept Lattices

Extracting and Visualising Tree-like Structures from Concept Lattices

Cubes of Concepts: Multi-dimensional Exploration of Multi-valued Contexts

Conceptual Navigation in RDF Graphs with SPARQL-Like Queries

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