scholarly journals A generative-discriminative learning model for noisy information fusion

Author(s):  
Thomas Hecht ◽  
Alexander Gepperth
Author(s):  
Nasir Jamal ◽  
Chen Xianqiao ◽  
Fadi Al-Turjman ◽  
Farhan Ullah

Emotions detection in natural languages is very effective in analyzing the user's mood about a concerned product, news, topic, and so on. However, it is really a challenging task to extract important features from a burst of raw social text, as emotions are subjective with limited fuzzy boundaries. These subjective features can be conveyed in various perceptions and terminologies. In this article, we proposed an IoT-based framework for emotions classification of tweets using a hybrid approach of Term Frequency Inverse Document Frequency (TFIDF) and deep learning model. First, the raw tweets are filtered using the tokenization method for capturing useful features without noisy information. Second, the TFIDF statistical technique is applied to estimate the importance of features locally as well as globally. Third, the Adaptive Synthetic (ADASYN) class balancing technique is applied to solve the imbalance class issue among different classes of emotions. Finally, a deep learning model is designed to predict the emotions with dynamic epoch curves. The proposed methodology is analyzed on two different Twitter emotions datasets. The dynamic epoch curves are shown to show the behavior of test and train data points. It is proved that this methodology outperformed the popular state-of-the-art methods.


1968 ◽  
Vol 65 (3, Pt.1) ◽  
pp. 427-432 ◽  
Author(s):  
R. C. Gonzalez ◽  
M. E. Bitterman

2020 ◽  
Vol 1 (3) ◽  
pp. 333-340
Author(s):  
Syarifah Roswan

The purpose of this study was to increase the learning outcomes of IPA in the Ecosystem Balance mate-rial through the application of the Contextual Teaching And Learning (CTL) learning model for class VI students of SD Negeri 1 Manggeng for the 2017/2018 academic year. The research methodology is Classroom Action Research (CAR) consisting of two cycles and each cycle consisting of two findings. Each cycle consists of planning, implementing, observing and reflecting. The data collection technique is to collect test scores that are carried out at the end of each lesson in each cycle using a question in-strument (written test). The learning outcome data were analyzed by means of percentage statistics. The results showed that the completeness of student learning outcomes increased from 66,67% in the first cycle and increased to 83,33% in the second cycle. The application of the Contextual Teaching And Learning (CTL) learning model can increase the learning outcomes of IPA in the Ecosystem Balance material of class VI SD Negeri 1 Manggeng for the 2017/2018 academic year


2020 ◽  
Vol 1 (3) ◽  
pp. 299-306
Author(s):  
Nurdahri Nurdahri

he purpose of this study was to improve science learning outcomes on the structure and function of plant networks in class VIII students of MTsN 2 Aceh Besar in the 2017/2018 academic year. The learning model used in this study is the Mind Mapping Learning Model. The subjects of this study were students of class VIII MTsN 2 Aceh Besar with a total of 33 students consisting of 13 male students and 20 fe-male students. This research was conducted in the 2017/2018 Academic Year within a period of 3 months, namely from August 2017 to October 2017 in Odd Semester. The research methodology is Classroom Action Research (CAR) consisting of two cycles and each cycle consisting of two meetings. Each cycle consists of planning, implementing, observing and reflecting. The research procedure con-sisted of pre-research, planning cycle one, implementing action cycle one, observing cycle one, reflect-ing cycle one, planning cycle two, implementing action cycle two, observing cycle two and reflecting cycle two. The data collection technique is to collect test scores that are carried out at the end of each lesson in each cycle using a question instrument (written test). Observation data was carried out by look-ing at the activeness of teachers and students during the learning process. The learning outcome data were analyzed by means of percentage statistics, while the observation data were analyzed by means of a Likert scale. The results showed that there was an increase in the completeness of student learning outcomes from 39.39% in the pre-cycle increased to 60.60% in Cycle I and increased to 87.87% in Cy-cle II. Observation of teacher activity during PBM has increased from a total score of 88 good categories in Cycle I, increasing to a total score of 93 good categories in Cycle II. The application of the Mind Mapping learning model can improve science learning outcomes on the structure and function of plant tissue for class VIII students of MTsN 2 Aceh Besar for the 2017/2018 academic year.


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