Formal Concept Analysis and Rough Set Theory in Clustering

Bao, Ho Tu

doi:10.1142/9789812703118_0005

Cited by 1 publication

(2 citation statements)

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“…Indeed, FCA and RST have been used in clustering and ontology mapping because of their intrinsic characteristics which make them suitable for such tasks. (Bao, 1999) present models and algorithms to create document clusters by enriching documents with "approximations" of their own terms then applying a clustering method using such "approximations." Although this approach is applied on documents, their target problem is different from our own in the sense that our document types are predefined "clusters" which a document is to be aligned to, whereas in (Bao, 1999) the approach is to create the clusters.…”

Section: Related Workmentioning

confidence: 99%

“…(Bao, 1999) present models and algorithms to create document clusters by enriching documents with "approximations" of their own terms then applying a clustering method using such "approximations." Although this approach is applied on documents, their target problem is different from our own in the sense that our document types are predefined "clusters" which a document is to be aligned to, whereas in (Bao, 1999) the approach is to create the clusters. (Zhao et al, 2006) addresses the problem of ontology mapping by introducing an improved similarity measure between two concepts of different ontologies.…”

Section: Related Workmentioning

confidence: 99%

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A Study on Aligning Documents Using the Circle of Interest Technique

Joseph¹,

Marín²

2010

Proceedings of the 5th International Conference on Software and Data Technologies

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In this paper we present a study on applying a technique called Circle of Interest, along with Formal Concept Analysis and Rough Set Theory to semantically align documents such as those found in a business domain. Indeed, when companies try to engage in business it becomes crucial to keep the semantics when exchanging information usually known as a business document. Typical approaches are not practical or require a high cost to implement. In contrast, we consider the concepts and their relationships discovered within an exchanged business document to find automatically an alignment to a local interpretation known as a document type. We present experimental results on applying Formal Concept Analysis as the ontological representation of documents, the Circle of Interest for selecting the most relevant document types to choose from, and Rough Set Theory for discerning among them. The results on a set of business documents show the feasibility of our approach and its direct application to a business domain.

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Section: Related Workmentioning

confidence: 99%