2010•Frontiers in artificial intelligence and applicationsRequires access

Concept Drift in documents and Formal Concept Analysis

Miyazaki Yutaka, Yuzuru Tanaka

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Abstract

Formal Concept Analysis (FCA) enables us to extract conceptual information from data and to visualize its structure in a lattice form. Here, we apply FCA to the analysis of a series of documents published periodically, in order to capture drifts of formal concepts occurred in the series by shifting the corresponding formal context as a viewpoint by some constant amount of time little by little. The resulting concept drifts can reflect the change of topics frequently discussed at that time.

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What this paper is about

Formal Concept Analysis (FCA) enables us to extract conceptual information from data and to visualize its structure in a lattice form. Here, we apply FCA to the analysis of a series of documents published periodically, in order to capture drifts of formal concepts occurred in the series by shifting the corresponding formal context as a viewpoint by some constant amount of time little by little. The resulting concept drifts can reflect the change of topics frequently discussed at that time.

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Available abstract

Formal Concept Analysis (FCA) enables us to extract conceptual information from data and to visualize its structure in a lattice form. Here, we apply FCA to the analysis of a series of documents published periodically, in order to capture drifts of formal concepts occurred in the series by shifting the corresponding formal context as a viewpoint by some constant amount of time little by little. The resulting concept drifts can reflect the change of topics frequently discussed at that time.

Key concepts: Mathematics, Combinatorics, Discrete mathematics

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