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Int. J. Synth. Emot.最新文献

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A Comparative Study of Different Classification Techniques for Sentiment Analysis 情感分析中不同分类技术的比较研究
Int. J. Synth. Emot. Pub Date : 2020-01-01 DOI: 10.4018/ijse.20200101.oa
Soumadip Ghosh, A. Hazra, A. Raj
{"title":"A Comparative Study of Different Classification Techniques for Sentiment Analysis","authors":"Soumadip Ghosh, A. Hazra, A. Raj","doi":"10.4018/ijse.20200101.oa","DOIUrl":"https://doi.org/10.4018/ijse.20200101.oa","url":null,"abstract":"Sentiment analysis denotes the analysis of emotions and opinions from text. The authors also refer to sentiment analysis as opinion mining. It finds and justifies the sentiment of the person with respect to a given source of content. Social media contain vast amounts of the sentiment data in the form of product reviews, tweets, blogs, and updates on the statuses, posts, etc. Sentiment analysis of this largely generated data is very useful to express the opinion of the mass in terms of product reviews. This work is proposing a highly accurate model of sentiment analysis for reviews of products, movies, and restaurants from Amazon, IMDB, and Yelp, respectively. With the help of classifiers such as logistic regression, support vector machine, and decision tree, the authors can classify these reviews as positive or negative with higher accuracy values.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117256882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Analyzing Tagore's Emotion With the Passage of Time in Song-Offerings: A Philosophical Study Based on Computational Intelligence 泰戈尔的情感随时间的流逝——基于计算智能的哲学研究
Int. J. Synth. Emot. Pub Date : 2019-07-01 DOI: 10.4018/ijse.2019070102
Sirshendu Hore, T. Bhattacharya
{"title":"Analyzing Tagore's Emotion With the Passage of Time in Song-Offerings: A Philosophical Study Based on Computational Intelligence","authors":"Sirshendu Hore, T. Bhattacharya","doi":"10.4018/ijse.2019070102","DOIUrl":"https://doi.org/10.4018/ijse.2019070102","url":null,"abstract":"The emotions of humans can be observed through tears, smiles, etc. The emotion of poets is reflected through poetry/songs. The works of a poet give philosophical insights about the beauty and mystery of nature, socio-economic conditions of that era, besides his personal state of mind. In the proposed work ‘Song- Offerings': A collection of poems and songs composed by Rabindranath Tagore, for which, Tagore received the Nobel Prize for literature in 1913, has been analyzed. Earlier, most of the research work on Song-Offerings was based on Zipf's law or bibliometric laws. This article analyzes the changes in Tagore's emotion in Song-Offerings with the passage of time (1895-1912). Emotions are analyzed based on the Arousal-Valence Model. To analyze the arousal state, ‘Plutchik's' emotion model has been employed and to find the valence, a Fuzzy-based model has been engaged. The work reveals that the emotions of the poet gradually mellows with the passage of time barring some transitional time, nevertheless, poet submission towards almighty remains unchanged during this period.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125588880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Segmentation of Leukemia Cells Using Clustering: A Comparative Study 用聚类方法分割白血病细胞的比较研究
Int. J. Synth. Emot. Pub Date : 2019-07-01 DOI: 10.4018/ijse.2019070103
Eman Mostafa, H. El-Dien
{"title":"Segmentation of Leukemia Cells Using Clustering: A Comparative Study","authors":"Eman Mostafa, H. El-Dien","doi":"10.4018/ijse.2019070103","DOIUrl":"https://doi.org/10.4018/ijse.2019070103","url":null,"abstract":"Leukemia is a blood cancer which is defined as an irregular augment of undeveloped white blood cells called “blasts.” It develops in the bone marrow, which is responsible for blood cell generation including leukocytes and white blood cells. The early diagnosis of leukemia greatly helps in the treatment. Accordingly, researchers are interested in developing advanced and accurate automated techniques for localizing such abnormal blood cells. Subsequently, image segmentation becomes an important image processing stage for successful feature extraction and classification of leukemia in further stages. It aims to separate cancer cells by segmenting the microscopic image into background and cancer cells that are known as the region of interested (ROI). In this article, the cancer blood cells were segmented using two separated clustering techniques, namely the K-means and Fuzzy-c-means techniques. Then, the results of these techniques were compared to in terms of different segmentation metrics, such as the Dice, Jac, specificity, sensitivity, and accuracy. The results proved that the k-means provided better performance in leukemia blood cells segmentation as it achieved an accuracy of 99.8% compared to 99.6% with the fuzzy c-means.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114723849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Sarcasm Detection for Workplace Stress Management 职场压力管理中的讽刺检测
Int. J. Synth. Emot. Pub Date : 2019-07-01 DOI: 10.4018/ijse.2019070101
U. Shrawankar, Chaitali Chandankhede
{"title":"Sarcasm Detection for Workplace Stress Management","authors":"U. Shrawankar, Chaitali Chandankhede","doi":"10.4018/ijse.2019070101","DOIUrl":"https://doi.org/10.4018/ijse.2019070101","url":null,"abstract":"Working stress is becoming very common. Handling working stress at the workplace is really going to be challenging. As a result, most of the time most of the time people start behaving in sarcastic ways through verbal communication, through different gestures, using emoticons, or writing reviews or comments that leads to increasing their anxiety sometimes promotes depression. It is difficult to identify sarcasm in written notes or communication. Feedback analysis is not a direct method since feedback or employer reviews are written in more formal language. This motivates the authors to work on the employee feedback system. The currently developed system helps to detect the sarcastic emotions by applying different methodologies on several types of statements. This will help corporations and other big organizations to identify reasons behind sarcastic behavior or increased anxiety. As a result, they can promote counseling programs, psychological treatment, or yoga-meditation camps.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126107847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
2D Shape Recognition and Retrieval Using Shape Contour Based on the 8-Neighborhood Patterns Matching Technique 基于8邻域模式匹配技术的二维形状轮廓识别与检索
Int. J. Synth. Emot. Pub Date : 2019-07-01 DOI: 10.4018/ijse.2019070104
Muzameel Ahmed, V. Aradhya
{"title":"2D Shape Recognition and Retrieval Using Shape Contour Based on the 8-Neighborhood Patterns Matching Technique","authors":"Muzameel Ahmed, V. Aradhya","doi":"10.4018/ijse.2019070104","DOIUrl":"https://doi.org/10.4018/ijse.2019070104","url":null,"abstract":"A technique for 2D shape recognition and retrieval is proposed. The proposed technique is based on the 8-neighborhood pattern which represents each point or pixel on the contour of the shape. These patterns are used as a framework in matching the shape of the object. The recognition and retrieval process are conducted by traversing through the contour of the shape and analyzes each point on the contour by considering the 8-neighborhood pattern. The 8-neighborhood patterns are assigned unique labels which are computed on their every occurrence during contour traversal. The cost of the best match between the shapes is evaluated by comparing the hit value obtained by the contour traversal of the shapes to be matched. The recognition and retrieval are carried out using the leave-one-out strategy and standard bull eye score, respectively. The proposed method is experimented on the MPEG-7 data set and the chicken piece data set. The results both for recognition and retrieval outperform most of the previously proposed methods.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134426489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Emotion Recognition Approach Using Multilayer Perceptron Network and Motion Estimation 基于多层感知器网络和运动估计的情绪识别方法
Int. J. Synth. Emot. Pub Date : 2019-01-01 DOI: 10.4018/ijse.2019010102
M. Berkane, Kenza Belhouchette, H. Belhadef
{"title":"Emotion Recognition Approach Using Multilayer Perceptron Network and Motion Estimation","authors":"M. Berkane, Kenza Belhouchette, H. Belhadef","doi":"10.4018/ijse.2019010102","DOIUrl":"https://doi.org/10.4018/ijse.2019010102","url":null,"abstract":"Man-machine interaction is an interdisciplinary field of research that provides natural and multimodal ways of interaction between humans and computers. For this purpose, the computer must understand the emotional state of the person with whom it interacts. This article proposes a novel method for detecting and classify the basic emotions like sadness, joy, anger, fear, disgust, surprise, and interest that was introduced in previous works. As with all emotion recognition systems, the approach follows the basic steps, such as: facial detection and facial feature extraction. In these steps, the contribution is expressed by using strategic face points and interprets motions as action units extracted by the FACS system. The second contribution is at the level of the classification step, where two classifiers were used: Kohonen self-organizing maps (KSOM) and multilayer perceptron (MLP) in order to obtain the best results. The obtained results show that the recognition rate of basic emotions has improved, and the running time was minimized by reducing resource use.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134060089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Towards a Sentiment Analysis Model Based on Semantic Relation Analysis 基于语义关系分析的情感分析模型研究
Int. J. Synth. Emot. Pub Date : 2018-07-01 DOI: 10.4018/IJSE.2018070104
T. K. Tran, T. Phan
{"title":"Towards a Sentiment Analysis Model Based on Semantic Relation Analysis","authors":"T. K. Tran, T. Phan","doi":"10.4018/IJSE.2018070104","DOIUrl":"https://doi.org/10.4018/IJSE.2018070104","url":null,"abstract":"In this paper, we propose an effective model for aspect-based sentiment analysis. First, we combined a sentiment dictionary and syntactic dependency rules to extract reliable word pairs (sentiment — aspect). Then, thanks to ontology, we grouped those aspects and determined the sentiment polarity of each. When we conducted experiments on real reviews, the system showed positive results.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115818290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
An Improved Method for Restoring the Shape of 3D Point Cloud Surfaces 一种改进的三维点云表面形状恢复方法
Int. J. Synth. Emot. Pub Date : 2018-07-01 DOI: 10.4018/IJSE.2018070103
V. Nguyen, Ha Manh Tran, Minh Khai Tran
{"title":"An Improved Method for Restoring the Shape of 3D Point Cloud Surfaces","authors":"V. Nguyen, Ha Manh Tran, Minh Khai Tran","doi":"10.4018/IJSE.2018070103","DOIUrl":"https://doi.org/10.4018/IJSE.2018070103","url":null,"abstract":"Building 3D objects or reconstructing their surfaces from 3D point cloud data are researched activities in the field of geometric modeling and computer graphics. In the recent years, they are also studied and used in some fields such as: graph models and simulation; image processing or restoration of digital heritages. This article presents an improved method for restoring the shape of 3D point cloud surfaces. The method is a combination of creating a Bezier surface patch and computing tangent plane of 3D points to fill holes on a surface of 3D point clouds. This method is described as follows: at first, a boundary for each hole on the surface is identified. The holes are then filled by computing Bezier curves of surface patches to find missing points. After that, the holes are refined based on two steps (rough and elaborate) to adjust the inserted points and preserve the local curvature of the holes. The contribution of the proposed method has been shown in processing time and the novelty of combined computation in this method has preserved the initial shape of the surface","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123774301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Emotion Mining Using Semantic Similarity 基于语义相似度的情感挖掘
Int. J. Synth. Emot. Pub Date : 2018-07-01 DOI: 10.4018/IJSE.2018070101
Rafiya Jan, Afaq Alam Khan
{"title":"Emotion Mining Using Semantic Similarity","authors":"Rafiya Jan, Afaq Alam Khan","doi":"10.4018/IJSE.2018070101","DOIUrl":"https://doi.org/10.4018/IJSE.2018070101","url":null,"abstract":"Social networks are considered as the most abundant sources of affective information for sentiment and emotion classification. Emotion classification is the challenging task of classifying emotions into different types. Emotions being universal, the automatic exploration of emotion is considered as a difficult task to perform. A lot of the research is being conducted in the field of automatic emotion detection in textual data streams. However, very little attention is paid towards capturing semantic features of the text. In this article, the authors present the technique of semantic relatedness for automatic classification of emotion in the text using distributional semantic models. This approach uses semantic similarity for measuring the coherence between the two emotionally related entities. Before classification, data is pre-processed to remove the irrelevant fields and inconsistencies and to improve the performance. The proposed approach achieved the accuracy of 71.795%, which is competitive considering as no training or annotation of data is done.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"27 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132124623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
An Approach to Opinion Mining in Community Graph Using Graph Mining Techniques 基于图挖掘技术的社区图意见挖掘方法
Int. J. Synth. Emot. Pub Date : 2018-07-01 DOI: 10.4018/IJSE.2018070106
B. Rao
{"title":"An Approach to Opinion Mining in Community Graph Using Graph Mining Techniques","authors":"B. Rao","doi":"10.4018/IJSE.2018070106","DOIUrl":"https://doi.org/10.4018/IJSE.2018070106","url":null,"abstract":"Opinions are the central theme to almost all human activities, as well the key influencers of our behaviours. Opinions related to sentiments, evaluations, attitudes, and emotions are the features of studying of opinion mining. It is important to study peoples of various communities sentiments about the schemes implemented by the government agencies as well as NGOs. The opinion mining is about the opinions of various communities of villages of a Panchayat about various social schemes implemented by the government of India. This article proposes an algorithm for opinion mining in a community graph for various social schemes run by the Panchayat using graph mining techniques. The algorithm has been implemented in C++ programming language.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117081874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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