Concept Membership Modeling Using a Choquet Integral
| Autor: | Olivier Pivert, Ronald R. Yager, Marie-Jeanne Lesot, Grégory Smits |
|---|---|
| Přispěvatelé: | Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Property (philosophy)
Information retrieval [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB] Computer science media_common.quotation_subject Aggregate (data warehouse) 020207 software engineering 02 engineering and technology Data point Choquet integral [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR] 0202 electrical engineering electronic engineering information engineering Fuzzy concept 020201 artificial intelligence & image processing Relevance (information retrieval) Function (engineering) Membership function ComputingMilieux_MISCELLANEOUS media_common |
| Zdroj: | Information Processing and Management of Uncertainty in Knowledge-Based Systems Information Processing and Management of Uncertainty in Knowledge-Based Systems, 1237, Springer International Publishing, pp.359-372, 2020, Communications in Computer and Information Science, ⟨10.1007/978-3-030-50146-4_27⟩ Information Processing and Management of Uncertainty in Knowledge-Based Systems ISBN: 9783030501457 IPMU (1) |
| DOI: | 10.1007/978-3-030-50146-4_27⟩ |
| Popis: | Imprecise and subjective concepts, as e.g. promising students, may be used within data mining tasks or database queries to faithfully describe data properties of interest. However, defining these concepts is a demanding task for the end-user. We thus provide a strategy, called CHOCOLATE, that only requires the user to give a tiny subset of data points that are representative of the concept he/she has in mind, and that infers a membership function from them. This function may then be used to retrieve, from the whole dataset, a ranked list of points that satisfy the concept of interest. CHOCOLATE relies on a Choquet integral to aggregate the relevance of individual attribute values among all the representative points as well as the representativity of sets of such attribute values. As a consequence, a valuable property of the proposed approach is that it is able to both capture properties shared by most of the user-selected representative data points as well as specific properties possessed by only one specific representative data point. |
| Databáze: | OpenAIRE |
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