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Communications of the ACM
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A completeness analysis of frequent weighted concept lattices and their algebraic properties
Data & Knowledge Engineering
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The paper reports the design of Dipe-R, a knowledge representation language. It meets two requirements: (1) Dipe-R should enable the appropriate expression of mental states and processes, viz. in line with basic insights on the nature of (human) communication and knowledge, and (2) Dipe-R should offer the possibility of identifying concepts by describing them by their features. The first requirement means that Dipe-R is capable of representing knowledge adequately. The second reflects a common way of exploring knowledge; this seems useful in various applications, e.g., in Information Retrieval.For meeting these requirements, Dipe-R has as main characteristics: (a) two types of expressions for representing thoughts (using binary relations), (b) for each expression Dipe-R creates at least one sentence in natural language, thus distinguishing language from 'meaning', and (c) each expression in Dipe-R is provided with information on its origin. Some relation types are pre-represented, e.g., for creating type hierarchies. Experiments (in Information Retrieval) indicate that Dipe-R indeed meets its requirements.