How subjective information with AI for digital revolution

This paper summarizes the relationship of subjective information with artificial intelligence (AI) technology and points out how the role of subjective information and its position in AI. Eventually, the characteristic of digital era is the “softening of the theories and hardening of the experiences”. Subjective information is widely used in digital revolution for transforming the qualitative estimations into quasi-quantitative solutions, such as the empirical methods in decision making for quantitative management, etc., it will be the transferor for realizing it. The theoretical formulation of how subjective information is digitized through “Fuzzy-AI Model” for digital revolution is presented in this paper; it has becoming a universal problem solver of utilizing AI technology for quantizing the degree uncertainties in decision-making and fuzzy estimation. Besides, the “Big Data” searching will heavily depend on the completeness of its source information, yet “subjective information” approach can directly predict human thinking or the internal law of complicated objective events into an explicit digital form, for the completeness of source information to make the correct and comprehensive “Big Data” prediction possible. Practical case studies are presented.

Objective / subjective information strategies in electronic German media

The article is devoted to the research of linguistic implementation of objective / subjective information strategies in the complex of electronic texts (article + comments) from modern German media. The material of the research was the primary texts of messages on topical issues from the newspaper ZEIT ONLINE and the magazine Focus Online as well as secondary texts of messages in the form of comments from the general reader. According to the analysis it is obvious that the strategic program in the studied discursive space is a complex multicomponent system due to both the intentional attitudes of the sender of the message and the special conditions of interaction in the Internet space. The topicality of the research is determined by consideration of verbal organization and implementation of the information strategies chosen for analysis and sorted on the objectivity subjectivity scale. The author emphasizes the use of means of different levels of the German language in the process of overlapping and intentional change of strategies. The emphasis is made on the fact that the strategic program of the message sender in the electronic environment can be guessed by the recipient, but there is no further continuation in the comments. The scientific novelty of the research is determined by the fact that in electronic German media a commentator, choosing suitable strategies of his own can turn the polemics based on what he read in the article into a new direction. In the course of the language analysis, it is noticed that for an electronic article, strategies of objective information are the most typically ones (detail strategy, information and interpretation strategy, logical persuasion strategy and evasion of the truth strategy), and for an electronic comment, it is more common the choice of subjective information strategy (control over the topic strategy, feelings appeal strategies and evaluation strategies).

Sleep Related Abnormal Sexual Behaviors: Uncommon yet Grave!

Sexual activities during sleep have been reported by some people, often along with the amnesia for the same. Such activities, when involuntary, may arise because of disorders of arousal or may be attributed to sleep related seizures. However, differentiation between the two etiological factors and, also from voluntary acts committed during sleep-period is important not only for the management of disorders but for medicolegal purpose! Subjective information as well gathered by the patients, bed-partners or victims as objective measures, namely polysomnography, long-term video EEG, and neuroimaging techniques may be helpful in achieving the same.

IMPROVING STUDENTS' SPEAKING SKILLS USING SPEAKING BINGO GAME

This research aimed to find out the improvement of students’ ability by using speaking bingo game in speaking for the seventh grade students of SMP Muhammadiyah Salatiga. The classroom action research adopted two cycles consisted of steps based on Kemmis and Taggart; planning, acting, observing, and reflecting. In each cycle comprised of pre-test, treatment, and post-test. The information gathered were subjective and quantitative information. The subjective information were acquired through perception, and documentation. Tests are utilized to gather the quantitative information. The understudies improve their talking abilities after instructed by talking bingo game and the mean of post-test is higher than the mean of the pre-test. The mean of pre-test are 57.0, while post-test is 61.8. In the cycle II, the mean of post-test is higher than the mean of the pre-test. The mean pre-test are 65.6, while post-test is 72.0. There is huge improvement for understudies talking abilities utilizing talking bingo game. The consequence of T-test in cycle I is 4.485 and cycle II is 6.025. In addition, the t-test in the cycle II is greater than the t-trial of the cycle I. From the outcome, the finish of the examination on utilizing talking bingo game can improve the 7th grade understudies' capacity in talking at SMP Muhammadiyah Salatiga fundamentally.Key Words: Speaking Bingo Game and Speaking Ability.

Sentiment Analysis and Sarcasm Detection (Using Emoticons)

Sentiment analysis is contextual mining of text which identifies and extracts subjective information in source material and helps a business to understand the social sentiment of their brand, product, or service while monitoring online conversations. However, analysis of social media streams is usually restricted to just basic sentiment analysis and count-based metrics. This is akin to just scratching the surface and missing out on those high value insights that are waiting to be discovered. Twitter is an online person-to-person communication administration where overall clients distribute their suppositions on an assortment of themes, talk about current issues, grumble, and express positive or on the other hand negative notions for items they use in life. Hence, Twitter is a rich source of information for supposition mining and estimation investigation.

Towards Semantic Aspect-Based Sentiment Analysis for Arabic Reviews

Sentiment analysis is a text mining discipline that aims to identify and extract subjective information. This growing field results in the emergence of three levels of granularity (document, sentence, and aspect). However, both the document and sentence levels do not find what exactly the opinion holder likes and dislikes. Furthermore, most research in this field deals with English texts, and very limited researches are undertaken on Arabic language. In this paper, the authors propose a semantic aspect-based sentiment analysis approach for Arabic reviews. This approach utilizes the semantic of description logics and linguistic rules in the identification of opinion targets and their polarity.

Avaliando o Desempenho da Abordagem de Comitê na Análise de Sentimentos na Língua Portuguesa

Sentiment Analysis aims extract subjective information from texts that, when written in Portuguese face a number of difficulties related to grammatical nature and vocabulary diversity. In order to collaborate with researches in this area, this paper presents the proposal to evaluate the performance of the committee approach in relation to the traditional approaches of sentiment analysis in the Portuguese language context. As object of application we choose tweets about volleyball theme that will serve as basis for the approaches application. These texts will be treated using Natural Language Processing for better performance of the algorithms. Other approaches will also be used in this study to assist in the evaluation of the committee along with the aid of metrics such as accuracy, precision, recall and F-measure.