Surjya Kanta Daimary, Vishal Goyal, Madhumita Barbora, Umrinderpal Singh
{"title":"Development of Part of Speech Tagger for Assamese Using HMM","authors":"Surjya Kanta Daimary, Vishal Goyal, Madhumita Barbora, Umrinderpal Singh","doi":"10.4018/IJSE.2018010102","DOIUrl":"https://doi.org/10.4018/IJSE.2018010102","url":null,"abstract":"This article presents the work on the Part-of-Speech Tagger for Assamese based on Hidden Markov Model (HMM). Over the years, a lot of language processing tasks have been done for Western and South-Asian languages. However, very little work is done for Assamese language. So, with this point of view, the POS Tagger for Assamese using Stochastic Approach is being developed. Assamese is a free word-order, highly agglutinate and morphological rich language, thus developing POS Tagger with good accuracy will help in development of other NLP task for Assamese. For this work, an annotated corpus of 271,890 words with a BIS tagset consisting of 38 tag labels is used. The model is trained on 256,690 words and the remaining words are used in testing. The system obtained an accuracy of 89.21% and it is being compared with other existing stochastic models.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128470024","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}
Zuber Shaikh, Antara Mohadikar, Rachana Nayak, Rohith Padamadan
{"title":"Security and Verification of Server Data Using Frequent Itemset Mining in Ecommerce","authors":"Zuber Shaikh, Antara Mohadikar, Rachana Nayak, Rohith Padamadan","doi":"10.4018/IJSE.2017010103","DOIUrl":"https://doi.org/10.4018/IJSE.2017010103","url":null,"abstract":"Frequentitemsetsrefertoasetofdatavalues(e.g.,productitems)whosenumberofco-occurrences exceedsagiventhreshold.Thechallengeisthatthedesignofproofsandverificationobjectshasto becustomizedfordifferentdataminingalgorithms.Intendedmethodwillimplementabasicideaof completenessverificationandauthenticationapproachinwhichtheclientwillusesasetoffrequent itemsetsastheevidence,andcheckswhethertheserverhasmissedanyfrequentitemsetasevidence initsreturnedresult.Itwillhelpclientdetectuntrustedserverandsystemwillbecomemuchmore efficiencybyreducingtime.InauthenticationprocessCaRPisbothacaptchaandagraphicalpassword scheme.CaRPaddressesanumberofsecurityproblemsaltogether,suchasonlineguessingattacks, relayattacks,and,ifcombinedwithdual-viewtechnologies,shoulder-surfingattacks. KEywoRDS Authentication, CaRP, Data Mining, Frequent Item Set, Security, Verification","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"25 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131862333","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}
{"title":"Abstract Expressions of Affect","authors":"A. D. Rooij, J. Broekens, Maarten H. Lamers","doi":"10.4018/jse.2013010101","DOIUrl":"https://doi.org/10.4018/jse.2013010101","url":null,"abstract":"What form should happiness take? And how is disgust shaped? This research investigates how synthetic affective expressions can be designed with minimal reference to the human body. The authors propose that the recognition and attribution of affect expression can be triggered by appropriately presenting the bare essentials used in the mental processes that mediate the recognition and attribution of affect. The novelty of the proposed approach lies in the fact that it is based on mental processes involved in the recognition of affect, independent of the configuration of the human body and face. The approach is grounded in (a) research on the role of abstraction in perception, (b) the elementary processes and features relevant to visual emotion recognition and emotion attribution, and (c) how such features can be used (and combined) to generate a synthetic emotion expression. To further develop the argument for this approach they present a pilot study that shows the feasibility of combining affective features independently of the human configuration by using abstraction to create consistent emotional attributions. Finally, the authors discuss the potential implications of their approach for the design of affective robots. The developed design approach promises a maximization of freedom to integrate intuitively understandable affective expressions with other morphological design factors a technology may require, providing synthetic affective expressions that suit the inherently artificial and applied nature of affective technology.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116255922","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}
{"title":"Advocating a Componential Appraisal Model to Guide Emotion Recognition","authors":"M. Mortillaro, B. Meuleman, K. Scherer","doi":"10.4018/jse.2012010102","DOIUrl":"https://doi.org/10.4018/jse.2012010102","url":null,"abstract":"Most models of automatic emotion recognition use a discrete perspective and a black-box approach, i.e., they output an emotion label chosen from a limited pool of candidate terms, on the basis of purely statistical methods. Although these models are successful in emotion classification, a number of practical and theoretical drawbacks limit the range of possible applications. In this paper, the authors suggest the adoption of an appraisal perspective in modeling emotion recognition. The authors propose to use appraisals as an intermediate layer between expressive features input and emotion labeling output. The model would then be made of two parts: first, expressive features would be used to estimate appraisals; second, resulting appraisals would be used to predict an emotion label. While the second part of the model has already been the object of several studies, the first is unexplored. The authors argue that this model should be built on the basis of both theoretical predictions and empirical results about the link between specific appraisals and expressive features. For this purpose, the authors suggest to use the component process model of emotion, which includes detailed predictions of efferent effects of appraisals on facial expression, voice, and body movements.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127066269","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}
{"title":"Real Time Sentiment Analysis","authors":"Sandip Palit, Soumadip Ghosh","doi":"10.4018/ijse.2020010103","DOIUrl":"https://doi.org/10.4018/ijse.2020010103","url":null,"abstract":"Data is the most valuable resource. We have a lot of unstructured data generated by the social media giants Twitter, Facebook, and Google. Unfortunately, analytics on unstructured data cannot be performed. As the availability of the internet became easier, people started using social media platforms as the primary medium for sharing their opinions. Every day, millions of opinions from different parts of the world are posted on Twitter. The primary goal of Twitter is to let people share their opinion with a big audience. So, if the authors can effectively analyse the tweets, valuable information can be gained. Storing these opinions in a structured manner and then using that to analyse people's reactions and perceptions about buying a product or a service is a very vital step for any corporate firm. Sentiment analysis aims to analyse and discover the sentiments behind opinions of various people on different subjects like commercial products, politics, and daily societal issues. This research has developed a model to determine the polarity of a keyword in real time.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131587574","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}
{"title":"The Emotions of Alan Turing: The Boy Who Explained Einstein's Theory of Relativity Aged 15½ for his Mother","authors":"Huma Shah","doi":"10.4018/ijse.2014010104","DOIUrl":"https://doi.org/10.4018/ijse.2014010104","url":null,"abstract":"This paper makes no apology for its reading like a collection of book reports. It draws mainly on the reminiscences of Sara and John Turing, Alan Turing's mother and elder brother respectively, as well as from Andrew Hodges' extensive research on the man, his work and his impact gathered for the definitive Alan Turing biography. Alan Turing was a complex, talented man bereft of one stable and loyal companion throughout his life. He was the boy who explained Einstein's Theory of Relativity aged 15ai�� for his mother and the tormented outcast who gave us the modern world (Sunday Times, 2011).","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126449536","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}
{"title":"Outwitted by the Hidden: Unsure Emotions","authors":"K. Warwick, Huma Shah","doi":"10.4018/ijse.2014010106","DOIUrl":"https://doi.org/10.4018/ijse.2014010106","url":null,"abstract":"In this paper the authors consider natural, feigned or absence of emotions in text-based dialogues. The dialogues occurred during interactions between human Judges/Interrogators and hidden entities in practical Turing tests implemented at Bletchley Park in June 2012. The authors focus on the interactions that left the Interrogator unable to say whether they were talking to a human or a machine after five minutes of questioning; the hidden interlocutor received an 'unsure' classification. In cases where the Judge has provided post-event feedback the authors present their rationale from three viva voce one-to-one Turing tests. The authors find that emoticons and other visual devices used to express feelings in text-based interaction were missing in the conversations between the Interrogators and hidden interlocutors.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121137983","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}
{"title":"Guidelines for Designing Computational Models of Emotions","authors":"E. Hudlicka","doi":"10.4018/jse.2011010103","DOIUrl":"https://doi.org/10.4018/jse.2011010103","url":null,"abstract":"Rapid growth in computational modeling of emotion and cognitive-affective architectures occurred over the past 15 years. Emotion models and architectures are built to elucidate the mechanisms of emotions and enhance believability and effectiveness of synthetic agents and robots. Despite the many emotion models developed to date, a lack of consistency and clarity regarding what exactly it means to 'model emotions' persists. There are no systematic guidelines for development of computational models of emotions. This paper deconstructs the often vague term 'emotion modeling' by suggesting the view of emotion models in terms of two fundamental categories of processes: emotion generation and emotion effects. Computational tasks necessary to implement these processes are also identified. The paper addresses how computational building blocks provide a basis for the development of more systematic guidelines for affective model development. The paper concludes with a description of an affective requirements analysis and design process for developing affective computational models in agent architectures.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131016895","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}
{"title":"Emotional Models: Types and Applications","authors":"R. Fathalla","doi":"10.4018/IJSE.2020070101","DOIUrl":"https://doi.org/10.4018/IJSE.2020070101","url":null,"abstract":"Emotion modeling has gained attention for almost two decades now due to the rapid growth of affective computing (AC). AC aims to detect and respond to the end-user's emotions by devices and computers. Despite the hard efforts being directed to emotion modeling with numerous tries to build different models of emotions, emotion modeling remains an art with a lack of consistency and clarity regarding the exact meaning of emotion modeling. This review deconstructs the vagueness of the term ‘emotion modeling' by discussing the various types and categories of emotion modeling, including computational models and its categories—emotion generation and emotion effects—and emotion representation models and its categories—categorical, dimensional, and componential models. This review deals with applications associated with each type of emotion model including artificial intelligence and robotics architecture, computer-human interaction applications of the computational models, and emotion classification and affect-aware applications such as video games and tutoring systems applications of emotion representation models.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128591443","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}
{"title":"An Ontology based on the Methodology Proposed by Ushold and King","authors":"Neha Jain, Lalitsen Sharma","doi":"10.4018/IJSE.2016010102","DOIUrl":"https://doi.org/10.4018/IJSE.2016010102","url":null,"abstract":"A number of methodologies are available in literature for ontology development but as the Ontology engineering field is relatively new, it is still unclear how the existing ontology building methodologies can be applied to develop semantic ontology models. In this work, firstly an overview of various ontology building methodologies and their limitations as compared to some standard software development methodologies are presented. Then the methodology proposed by Ushold and King is selected to build an ontology in e-banking domain. The challenge in this domain is to recognize, communicate and steadily improvise the banking solutions. The ontologies are prospective candidates to assist overcome these challenges and enhance interoperability of banking data and services. The study aims to provide direction for the application of existing ontology building methodologies in the Semantic Web Development processes of e-banking domain specific models which would enable their reusability and repeatability in other projects and strengthen the adoption of semantic technologies in the domain.","PeriodicalId":272943,"journal":{"name":"Int. J. Synth. Emot.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130581009","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}