Titlebook: Database and Expert Systems Applications; 29th International C Sven Hartmann,Hui Ma,Roland R. Wagner Conference proceedings 2018 Springer N

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A Fuzzy Unified Framework for Imprecise Knowledgege type if they were multi-valued. Our proposal offer a high flexibility to the user to reason regardless to the knowledge type. In addition, it is an alternative to overcome the modeling shortcoming of abstract data by taking advantage of a rigorous mathematical framework of fuzzy logic. A numerica

MAOIS

Information Filtering Method for Twitter Streaming Data Using Human-in-the-Loop Machine Learning again. We assume that if we continue instigating this loop, the accuracy of the classifier will improve, and we will obtain useful information without having to specify keywords. Experimental results demonstrated that our proposed system is effective for filtering social media streams. Moreover, we

GROG

A Recommender System with Advanced Time Series Medical Data Analysis for Diabetes Patients in a Teletions on their need to take a medical test or not on the coming day based on the analysis of their medical data. A real-life time series dataset is used for experimental evaluation. The experimental results show that the proposed system yields very good recommendation accuracy and can effectively re

惡心

insomnia

奇怪

crescendo

CROP: An Efficient Cross-Platform Event Popularity Prediction Model for Online Media-making for online platforms. Numerous studies concentrate on the trend analysis on single platform, but they neglect the data correlation between different platforms. In this paper, we propose CROP, a cross-platform event popularity prediction model to forecast the popularity of events on one platf

組成

有危險(xiǎn)

A Fuzzy Unified Framework for Imprecise Knowledgeased on fuzzy set theory, or using symbolic multi-valued logic, which is based on multi-set theory. To provide a unified framework to handle simultaneously both types of information, we propose in this paper a new approach to translate multi-valued knowledge into fuzzy knowledge. For that purpose, w

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