Method for Determining Linguometric Coefficient Dynamics of Ukrainian Text Content Authorship

2018 ◽  
pp. 132-151 ◽  
Author(s):  
Victoria Vysotska ◽  
Vitor Basto Fernandes ◽  
Vasyl Lytvyn ◽  
Michael Emmerich ◽  
Mariya Hrendus
Keyword(s):  
Ukrainian Text ◽  
Text Content

Solving the Message Classification Problem in Voice Interaction Systems

Vestnik MEI ◽  
2020 ◽  
Vol 5 (5) ◽  
pp. 132-139
Author(s):  
Ivan E. Kurilenko ◽  
◽  
Igor E. Nikonov ◽  
Keyword(s):  
Artificial Intelligence ◽  
Classification Problem ◽  
Subject Area ◽  
Text Messages ◽  
Case Based Reasoning ◽  
Short Text ◽  
Proposed Modification ◽  
Voice Interaction ◽  
Text Content ◽  
Case Based

A method for solving the problem of classifying short-text messages in the form of sentences of customers uttered in talking via the telephone line of organizations is considered. To solve this problem, a classifier was developed, which is based on using a combination of two methods: a description of the subject area in the form of a hierarchy of entities and plausible reasoning based on the case-based reasoning approach, which is actively used in artificial intelligence systems. In solving various problems of artificial intelligence-based analysis of data, these methods have shown a high degree of efficiency, scalability, and independence from data structure. As part of using the case-based reasoning approach in the classifier, it is proposed to modify the TF-IDF (Term Frequency - Inverse Document Frequency) measure of assessing the text content taking into account known information about the distribution of documents by topics. The proposed modification makes it possible to improve the classification quality in comparison with classical measures, since it takes into account the information about the distribution of words not only in a separate document or topic, but in the entire database of cases. Experimental results are presented that confirm the effectiveness of the proposed metric and the developed classifier as applied to classification of customer sentences and providing them with the necessary information depending on the classification result. The developed text classification service prototype is used as part of the voice interaction module with the user in the objective of robotizing the telephone call routing system and making a shift from interaction between the user and system by means of buttons to their interaction through voice.

scholarly journals Systemic Lupus Erythematosus before and after COVID-19 Lockdown: How the Perception of Disease Changes through the Lenses of Narrative Medicine

Healthcare ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 726
Author(s):  
Fulvia Ceccarelli ◽  
Venusia Covelli ◽  
Giulio Olivieri ◽  
Francesco Natalucci ◽  
Fabrizio Conti
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
Narrative Medicine ◽  
Good Control ◽  
Final Analysis ◽  
Point Of View ◽  
Systemic Lupus ◽  
Before And After ◽  
Text Content ◽  
Insight Into

Background: The COVID-19 pandemic contributes to the burden of living with different diseases, including Systemic Lupus Erythematosus (SLE). We described, from a narrative point of view, the experiences and perspectives of Italian SLE adults during the COVID-19 emergency, by distinguishing the illness experience before and after the lockdown. Methods: Fifteen patients were invited to participate. Illness narratives were collected between 22 and 29 March 2020 using a written modality to capture patients’ perspectives before and after the COVID-19 lockdown. We performed a two-fold analysis of collected data by distinguishing three narrative types and a qualitative analysis of content to identify the relevant themes and sub-themes reported. Results: Eight narratives included in the final analysis (mean length 436.9 words) have been written by eight females (mean age 43.3 ± 9.9 years, mean disease duration 13.1 ± 7.4 years). Six patients provided a quest narrative, one a chaos and the remaining one a restitution narrative. By text content analysis, we identified specific themes, temporally distinct before and after the lockdown. Before COVID-19, all the patients referred to a good control of disease, however the unexpected arrival of the COVID-19 emergency broke a balance, and patients perceived the loss of health status control, with anxiety and stress. Conclusions: We provided unique insight into the experiences of people with SLE at the time of COVID-19, underlining the perspective of patients in relation to the pandemic.

Text Content Based Layout Analysis

2020 ◽  
Author(s):  
Jose Ramon Prieto ◽  
Vicente Bosch ◽  
Enrique Vidal ◽  
Dominique Stutzmann ◽  
Sebastien Hamel
Keyword(s):  
Layout Analysis ◽  
Text Content

scholarly journals A Comparative Analysis of Arabic Text Steganography

2021 ◽  
Vol 11 (15) ◽  
pp. 6851
Author(s):  
Reema Thabit ◽  
Nur Izura Udzir ◽  
Sharifah Md Yasin ◽  
Aziah Asmawi ◽  
Nuur Alifah Roslan ◽  
...  
Keyword(s):  
Evaluation Criteria ◽  
Arabic Language ◽  
Text Messages ◽  
Secret Message ◽  
Sensitive Information ◽  
Arabic Text ◽  
Ideal Object ◽  
Internet Users ◽  
Text Steganography ◽  
Text Content

Protecting sensitive information transmitted via public channels is a significant issue faced by governments, militaries, organizations, and individuals. Steganography protects the secret information by concealing it in a transferred object such as video, audio, image, text, network, or DNA. As text uses low bandwidth, it is commonly used by Internet users in their daily activities, resulting a vast amount of text messages sent daily as social media posts and documents. Accordingly, text is the ideal object to be used in steganography, since hiding a secret message in a text makes it difficult for the attacker to detect the hidden message among the massive text content on the Internet. Language’s characteristics are utilized in text steganography. Despite the richness of the Arabic language in linguistic characteristics, only a few studies have been conducted in Arabic text steganography. To draw further attention to Arabic text steganography prospects, this paper reviews the classifications of these methods from its inception. For analysis, this paper presents a comprehensive study based on the key evaluation criteria (i.e., capacity, invisibility, robustness, and security). It opens new areas for further research based on the trends in this field.

Does One Size Fit All? Exploring the Contribution of Text features, Text content, and Grade of Use on Comprehension

2020 ◽  
pp. 1-32
Author(s):  
Heidi Anne E. Mesmer ◽  
Elfrieda H. Hiebert ◽  
James W. Cunningham ◽  
Madhu Kapania
Keyword(s):  
Text Features ◽  
Text Content

Fast Text Processing for Interlaced Sports or News Videos

2015 ◽  
Vol 740 ◽  
pp. 652-655
Author(s):  
Qian Huang ◽  
Feng Xu
Keyword(s):  
Unsolved Problem ◽  
Text Processing ◽  
Picture Quality ◽  
Trade Off ◽  
Coding Efficiency ◽  
The Past ◽  
Processing Strategies ◽  
Visual Artifacts ◽  
Text Content ◽  
Almost All

Interlaced scanning has been widely used as a trade-off solution between picture quality and transmission bandwidth since the invention of television. During the past decades, various interlaced-to-progressive conversion algorithms have been proposed to improve subjective quality or coding efficiency. However, almost all the researchers concentrate on general cases, without making full use of specific application scenarios. Based on extensive investigations, eliminating visual artifacts in areas of subtitles and station captions for interlaced sports and news videos is still an unsolved problem, which will be addressed in this paper. Firstly, motion estimation is performed between field pictures. Secondly, text edge detection is proposed for sports and news videos. Finally, different processing strategies are applied to text regions and non-text regions. Experimental results show that the proposed method can generate much better text content than existing algorithms. In addition, it is quite stable for non-text parts.

How marketer-generated content characteristics affect consumer engagement? Empirical evidence from China's WeChat food marketing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Si Tan ◽  
Weiping Chen
Keyword(s):  
Body Text ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Food Marketing ◽  
Consumer Engagement ◽  
Content Type ◽  
Positive Effects ◽  
Binomial Regression ◽  
Media Research ◽  
Text Content

Purpose Leveraging marketer-generated content (MGC) can increase firms' success. However, few studies uncover the effects of MGC-related attributes on consumer engagement in the context of food marketing. This paper aims to explore the influence of MGC characteristics (valence, content types, vividness and interactivity) on consumer engagement.Design/methodology/approachThis study uses WeChat official account data of seven food companies from China and conducts negative binomial regression models.FindingsThe findings indicate that different MGC-related characteristics have separate impacts on consumer WeChat engagement. Title valence, transactional title content and title with punctuation vividness negatively affect consumers' consuming engagement. Knowledgeable or entertaining title content and title with interactivity both positively affect consumers' consuming engagement. Moreover, transactional body text content negatively influences consumers' contributing engagement, whereas entertaining body text content shows positive effects. Vivid and interactive MGC body text attributes enhance consumers' contributing engagement behavior.Originality/value This study contributes to social media research in food marketplaces and sheds light on the effect of different WeChat MGC characteristics on separate consumer engagement.

Sign in / Sign up

Export Citation Format

Share Document