IRApr 1, 2014

Interestingness a Unifying Paradigm Bipolar Function Composition

arXiv:1404.0091v110 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the challenge of formalizing interestingness for researchers in knowledge discovery, though it appears incremental as it builds on existing concepts without introducing a new method.

The paper tackles the problem of defining 'interestingness' in knowledge discovery by proposing a unifying paradigm based on bipolar function composition, where relevance and unexpectedness serve as the two semantic poles, and demonstrates its generality through case studies and examples.

Interestingness is an important criterion by which we judge knowledge discovery. But, interestingness has escaped all attempts to capture its intuitive meaning into a concise and comprehensive form. A unifying paradigm is formulated by function composition. We claim that composition is bipolar, i.e. composition of exactly two functions, whose two semantic poles are relevance and unexpectedness. The paradigm generality is demonstrated by case studies of new interestingness functions, examples of known functions that fit the framework, and counter-examples for which the paradigm points out to the lacking pole.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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