Aug 31, 2018 · In this paper, we propose a novel fuzzy rough set-based semi-supervised learning algorithm (FRL) for categorizing relational facts derived from ...
In this paper, we propose a novel fuzzy rough set-based semi-supervised learning algorithm (FRL) for categorizing relational facts derived from a given corpus.
Oct 22, 2024 · In this paper, we propose a novel fuzzy rough set-based semi-supervised learning algorithm (FRL) for categorizing relational facts derived from ...
Categorizing relational facts from the web with fuzzy rough sets ; Journal: Knowledge and Information Systems, 2018, № 3, p. 1695-1713 ; Publisher: Springer ...
This paper presents a novel approach, based on an integrated use of fuzzy and rough set theories, to greatly reduce this data redundancy. Formal concepts of ...
Missing: facts | Show results with:facts
Nov 21, 2024 · In this paper, we propose a semi-supervised learning algorithm (TPL) to extract categorical noun phrase instances from unstructured web ...
Dec 1, 2015 · A key issue when mining web information is the labeling problem. •. Tolerance rough sets are used to structure categorical instances and ...
Jun 1, 2016 · A fuzzy rough set is an important rough set model used for feature selection. It uses the fuzzy rough dependency as a criterion for feature selection.
Missing: Categorizing relational facts
This paper presents an easy-to-use and easy-to-implement framework for fuzzy data classification and extraction in relational databases.
Abstract—Traditional rough set theory uses equivalence rela- tions to compute lower and upper approximations of sets. The.