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A Flexible Approach to Matching User Preferences with Records in Datasets based on the Conformance Measure and Aggregation Functions

Topics: Applications: Fuzzy Systems in Robotics, Fuzzy Image, Speech and Signal Processing, Vision and Multimedia, Pattern Recognition, Financial and Medical Applications, Fuzzy Information Retrieval and Data Mining, Big Data and Cloud Computing, Industrial and R; Fuzzy Information Processing, Fusion, Text Mining

Authors: Miljan Vučetić 1 and Miroslav Hudec 2

Affiliations: 1 Vlatacom Institute of High Technologies, 5 Milutina Milankovića Blvd, Belgrade and Serbia ; 2 Faculty of Economic Informatics, University of Economics in Bratislava, Dolnozemská cesta 1, Bratislava and Slovakia

ISBN: 978-989-758-327-8

Keyword(s): Similarity, Conformance Measure, Fuzzy Conjunction, Uni-norms, Geometric Mean, Quantified Fuzzy Aggregation.

Abstract: Matching user preferences with content in datasets is an important task in building robust query engines. However, this is still a challenging task, because the entities’ attributes are often expressed by various data types including numerical, categorical, and fuzzy data. Moreover, the user’s preferences and data types for particular attributes may not collide, i.e. the user explains his requirements in linguistic term(s), whereas the respective attribute is recorded as a real number and vice versa. Further, the user may provide different relevancies for atomic conditions, where usual one-directional reinforcement aggregation functions, e.g. conjunction, are not suitable. In this paper, we propose a robust framework capable to manage user requirements and match them with records in a dataset. The former is solved by conformance measure, whereas for the latter the suitable aggregation functions have been suggested to cover particular aggregation needs. Finally, we discuss benefits, dr awbacks and outline further activities. (More)

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Paper citation in several formats:
Vučetić, M. and Hudec, M. (2018). A Flexible Approach to Matching User Preferences with Records in Datasets based on the Conformance Measure and Aggregation Functions.In Proceedings of the 10th International Joint Conference on Computational Intelligence - Volume 1: IJCCI, ISBN 978-989-758-327-8, pages 168-175. DOI: 10.5220/0006925801680175

@conference{ijcci18,
author={Miljan Vučetić. and Miroslav Hudec.},
title={A Flexible Approach to Matching User Preferences with Records in Datasets based on the Conformance Measure and Aggregation Functions},
booktitle={Proceedings of the 10th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,},
year={2018},
pages={168-175},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006925801680175},
isbn={978-989-758-327-8},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,
TI - A Flexible Approach to Matching User Preferences with Records in Datasets based on the Conformance Measure and Aggregation Functions
SN - 978-989-758-327-8
AU - Vučetić, M.
AU - Hudec, M.
PY - 2018
SP - 168
EP - 175
DO - 10.5220/0006925801680175

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