Corpus Construction and Semantic Analysis of Indonesian Image Description

2018 ◽  
Author(s):  
Khumaisa Nur'Aini ◽  
Johanes Effendi ◽  
Sakriani Sakti ◽  
Mirna Adriani ◽  
Satoshi Nakamura
Keyword(s):  
Semantic Analysis ◽  
Image Description ◽  
Corpus Construction

scholarly journals Del píxel a las resonancias visuales: La imagen con voz propia

AusArt ◽  
2016 ◽  
Vol 4 (1) ◽  
pp. 19-28
Author(s):  
Pilar Rosado Rodrigo ◽  
Eva Figueras Ferrer ◽  
Ferran Reverter Comes
Keyword(s):  
Computer Vision ◽  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Specific Model ◽  
Visual Word ◽  
Probabilistic Latent Semantic Analysis ◽  
Bag Of Words ◽  
Regular Grid ◽  
Image Description ◽  
Visual Words

Esta investigación aborda el problema de la detección aspectos latentes en grandes colecciones de imágenes de obras de artista abstractas, atendiendo sólo a su contenido visual. Se ha programado un algoritmo de descripción de imágenes utilizado en visión artificial cuyo enfoque consiste en colocar una malla regular de puntos de interés en la imagen y seleccionar alrededor de cada uno de sus nodos una región de píxeles para la que se calcula un descriptor que tiene en cuenta los gradientes de grises encontrados. Los descriptores de toda la colección de imágenes se pueden agrupar en función de su similitud y cada grupo resultante pasará a determinar lo que llamamos “palabras visuales”. El método se denomina Bag-of-Words (bolsa de palabras). Teniendo en cuenta la frecuencia con que cada “palabra visual”  ocurre en cada imagen, aplicamos el modelo estadístico pLSA (Probabilistic Latent Semantic Analysis), que clasificará de forma totalmente automática las imágenes según su categoría formal. Esta herramienta resulta de utilidad tanto en el análisis de obras de arte como en la producción artística. Palabras-clave: visión artificial; modelo Bag-of-Words; CBIR (Recuperación de imágenes por contenido); pLSA (ANÁLISIS PROBABILÍSTICO DE ASPECTOS LATENTES); palabra visual From pixel to visual resonances: Images with voicesAbstractThe objective of our research is to develop a series of computer vision programs to search for analogies in large datasets—in this case, collections of images of abstract paintings—based solely on their visual content without textual annotation. We have programmed an algorithm based on a specific model of image description used in computer vision. This approach involves placing a regular grid over the image and selecting a pixel region around each node. Dense features computed over this regular grid with overlapping patches are used to represent the images. Analysing the distances between the whole set of image descriptors we are able to group them according to their similarity and each resulting group will determines what we call "visual words". This model is called Bag-of-Words representation Given the frequency with which each visual word occurs in each image, we apply the method pLSA (Probabilistic Latent Semantic Analysis), a statistical model that classifies fully automatically, without any textual annotation, images according to their formal patterns. In this way, the researchers hope to develop a tool both for producing and analysing works of art. Keywords: artificial visión; Bag-of-Words model; CBIR (Content-Based Image Retrieval); pLSA (Probabilistic Latent Semantic Analysis); visual word

scholarly journals A Semantic Analysis and Community Detection-Based Artificial Intelligence Model for Core Herb Discovery from the Literature: Taking Chronic Glomerulonephritis Treatment as a Case Study

2020 ◽  
Vol 2020 ◽  
pp. 1-23
Author(s):  
Yun Zhang ◽  
Yongguo Liu ◽  
Jiajing Zhu ◽  
Shuangqing Zhai ◽  
Rongjiang Jin ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Community Detection ◽  
Large Scale ◽  
Semantic Analysis ◽  
Semantic Network ◽  
Closeness Centrality ◽  
Chinese Herbs ◽  
Chronic Glomerulonephritis ◽  
The Core ◽  
Corpus Construction

The Traditional Chinese Medicine (TCM) formula is the main treatment method of TCM. A formula often contains multiple herbs where core herbs play a critical therapeutic effect for treating diseases. It is of great significance to find out the core herbs in formulae for providing evidences and references for the clinical application of Chinese herbs and formulae. In this paper, we propose a core herb discovery model CHDSC based on semantic analysis and community detection to discover the core herbs for treating a certain disease from large-scale literature, which includes three stages: corpus construction, herb network establishment, and core herb discovery. In CHDSC, two artificial intelligence modules are used, where the Chinese word embedding algorithm ESSP2VEC is designed to analyse the semantics of herbs in Chinese literature based on the stroke, structure, and pinyin features of Chinese characters, and the label propagation-based algorithm LILPA is adopted to detect herb communities and core herbs in the herbal semantic network constructed from large-scale literature. To validate the proposed model, we choose chronic glomerulonephritis (CGN) as an example, search 1126 articles about how to treat CGN in TCM from the China National Knowledge Infrastructure (CNKI), and apply CHDSC to analyse the collected literature. Experimental results reveal that CHDSC discovers three major herb communities and eighteen core herbs for treating different CGN syndromes with high accuracy. The community size, degree, and closeness centrality distributions of the herb network are analysed to mine the laws of core herbs. As a result, we can observe that core herbs mainly exist in the communities with more than 25 herbs. The degree and closeness centrality of core herb nodes concentrate on the range of [15, 40] and [0.25, 0.45], respectively. Thus, semantic analysis and community detection are helpful for mining effective core herbs for treating a certain disease from large-scale literature.

Feel Thine Own Self – Mood Congruency Evaluation of Emotional State Adjectives

2020 ◽  
pp. 1-17
Author(s):  
Szczepan J. Grzybowski ◽  
Miroslaw Wyczesany ◽  
Jan Kaiser
Keyword(s):  
Mood Induction ◽  
Semantic Analysis ◽  
Emotional State ◽  
Time Window ◽  
Event Related Potential ◽  
Negativity Bias ◽  
Positive Potential ◽  
Semantic Access ◽  
Current Mood ◽  
Component Time

Abstract. The goal of the study was to explore event-related potential (ERP) differences during the processing of emotional adjectives that were evaluated as congruent or incongruent with the current mood. We hypothesized that the first effects of congruence evaluation would be evidenced during the earliest stages of semantic analysis. Sixty mood adjectives were presented separately for 1,000 ms each during two sessions of mood induction. After each presentation, participants evaluated to what extent the word described their mood. The results pointed to incongruence marking of adjective’s meaning with current mood during early attention orientation and semantic access stages (the P150 component time window). This was followed by enhanced processing of congruent words at later stages. As a secondary goal the study also explored word valence effects and their relation to congruence evaluation. In this regard, no significant effects were observed on the ERPs; however, a negativity bias (enhanced responses to negative adjectives) was noted on the behavioral data (RTs), which could correspond to the small differences traced on the late positive potential.

Syntactic and Semantic Analysis on Slogans of Aviation Companies in Asean Countries

2019 ◽  
Vol 3 (2) ◽  
pp. 123-131
Author(s):  
Ervina CM Simatupang
Keyword(s):  
Semantic Analysis ◽  
Data Source ◽  
Asean Countries ◽  
Descriptive Method

The title of this study is Syntactic and Sematic Analysis on Slogans of Aviation in Asean Countries. The aim of this study is to analyze and describe the slogans of aviation companies in Asean companies syntactically and semantically. The method used in this study is descriptive method. Data source are taken from official websites of various aviation companies in Asean countries, and there are taken from Wikipedia as the website has listed in chart. The chart has covered the profile of the aviation companies in Asean countries. The theories used to analyze the data syntactically are from O

Principles of economic security management of institutions of higher education

2019 ◽  
pp. 174-181
Author(s):  
Nataliia Tsymbalenko
Keyword(s):  
Management System ◽  
Semantic Analysis ◽  
Security Management ◽  
Economic Security ◽  
Theoretical Concepts ◽  
Economic Role ◽  
Social Mission ◽  
Analysis And Synthesis ◽  
Definition Of ◽  
The University

The subject of research-theoretical concepts of economic security managementof universities. The purpose of the article. The study of the essence of the economicsecurity management system of the university and the definition of its main tasks,the formulation of principles of economic security management of the university.Methodology. The dialectical method, methods of analysis and synthesis, methodsof structural-logical and semantic analysis were used to study and summarizescientific papers on the research topic. The results of the work. The essence of theuniversity’s economic security management system has been reviewed. The maintasks of the control system have been identified. A definition of the university’seconomic security system has been proposed. Principles of management of economicsecurity of the university have been formulated. These are: scientific andorganizational and social principles. Conclusions. The proposed principles allow totake into account the economic role and social mission of universities in managingeconomic security.

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