Pub Date : 2019-10-01DOI: 10.4018/ijisss.2019100105
A. Y. Obeng
As part of management's role to respond to threats in the banking industry, the capabilities of information technology are leveraged to devise technology-driven offensive strategies. Participants of the study were drawn from eight universal banks in Ghana. The relationships that exist among managerial roles, managerial roles and participants, and how participants are related were examined. The systematic procedure of grounded theory design and subsequent analysis of the generated frequencies using a quantitative technique of correspondence analysis were followed. The obtained results of p-value = 0.000 indicates a strong dependency in the data. The inertia >.5 indicates strong associations among the categories and participants. The two-dimensional solution obtained accounted for 96.2% of total inertia. Findings of the study show that, the success of leading an information systems (IS)-technological innovation offensive-strategy depends on strong innovation capabilities developed through collaboration between business managers and IS/IT heads.
{"title":"Management Role in Leading IS-Technological Innovation Offensive Strategy among Universal Banks in Ghana","authors":"A. Y. Obeng","doi":"10.4018/ijisss.2019100105","DOIUrl":"https://doi.org/10.4018/ijisss.2019100105","url":null,"abstract":"As part of management's role to respond to threats in the banking industry, the capabilities of information technology are leveraged to devise technology-driven offensive strategies. Participants of the study were drawn from eight universal banks in Ghana. The relationships that exist among managerial roles, managerial roles and participants, and how participants are related were examined. The systematic procedure of grounded theory design and subsequent analysis of the generated frequencies using a quantitative technique of correspondence analysis were followed. The obtained results of p-value = 0.000 indicates a strong dependency in the data. The inertia >.5 indicates strong associations among the categories and participants. The two-dimensional solution obtained accounted for 96.2% of total inertia. Findings of the study show that, the success of leading an information systems (IS)-technological innovation offensive-strategy depends on strong innovation capabilities developed through collaboration between business managers and IS/IT heads.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129768900","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}
Pub Date : 2019-10-01DOI: 10.4018/ijisss.2019100103
Brijesh Sivathanu
This study investigates the factors influencing customer satisfaction with references to on-demand home services, an emerging phenomenon in India. The hypothesized conceptual framework is grounded in the E-SQ and SERVQUAL model. To test the research hypotheses, 382 sample respondents were surveyed using a pre-tested questionnaire. The empirical validation of the proposed framework was performed with the help of PLS-SEM. The results suggest that e-service quality (E-SQ) and service quality (SERVQUAL) contribute to the overall service quality (OSQ) which has a positive influence on customer satisfaction (CS). It is further noted that, with reference to on-demand home services, overall service quality (OSQ) and customer satisfaction (CS) is moderated by value (VL). Further research could investigate the influence of OSQ on other relational constructs such as trust and customer loyalty. This study offers interesting insights to the managers and marketers in the service industry while crafting marketing strategies.
{"title":"An Empirical Study of Service Quality, Value and Customer Satisfaction for On-Demand Home Services","authors":"Brijesh Sivathanu","doi":"10.4018/ijisss.2019100103","DOIUrl":"https://doi.org/10.4018/ijisss.2019100103","url":null,"abstract":"This study investigates the factors influencing customer satisfaction with references to on-demand home services, an emerging phenomenon in India. The hypothesized conceptual framework is grounded in the E-SQ and SERVQUAL model. To test the research hypotheses, 382 sample respondents were surveyed using a pre-tested questionnaire. The empirical validation of the proposed framework was performed with the help of PLS-SEM. The results suggest that e-service quality (E-SQ) and service quality (SERVQUAL) contribute to the overall service quality (OSQ) which has a positive influence on customer satisfaction (CS). It is further noted that, with reference to on-demand home services, overall service quality (OSQ) and customer satisfaction (CS) is moderated by value (VL). Further research could investigate the influence of OSQ on other relational constructs such as trust and customer loyalty. This study offers interesting insights to the managers and marketers in the service industry while crafting marketing strategies.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132630945","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}
Pub Date : 2019-10-01DOI: 10.4018/ijisss.2019100104
Litinthong Kimixay, Cheng Liu, A. Waheed, Lidinthong Kathid
Over the past decades, numerous experts have been investigated the correlation among distinct personality traits and job performance. However, relatively less attention was paid examining the significance of technological tools in sales management, especially in developing countries. This article explores the relationship among the five-factor model (FFM) of personality traits and sales performance (SP) with a moderating role of the technology. To this end, structural equation modeling and Fisher's Z transformation analysis were employed to analyze the hypotheses. The findings revealed that extraversion, conscientiousness, openness to experience, and emotional stability traits are positively correlated to SP. In contrast, agreeableness is not highly correlated with SP relatively than the remainder traits. Additionally, results revealed the significant effect of technology as a moderator which strengthens the association of FFM and SP. This study proposes diverse managerial implications and future directions for practitioners and academicians across the nations.
{"title":"Understanding an Effect of Technology Between the Relationships of the Five-Factor Model and Sales Performance Technology as a Moderating Tool","authors":"Litinthong Kimixay, Cheng Liu, A. Waheed, Lidinthong Kathid","doi":"10.4018/ijisss.2019100104","DOIUrl":"https://doi.org/10.4018/ijisss.2019100104","url":null,"abstract":"Over the past decades, numerous experts have been investigated the correlation among distinct personality traits and job performance. However, relatively less attention was paid examining the significance of technological tools in sales management, especially in developing countries. This article explores the relationship among the five-factor model (FFM) of personality traits and sales performance (SP) with a moderating role of the technology. To this end, structural equation modeling and Fisher's Z transformation analysis were employed to analyze the hypotheses. The findings revealed that extraversion, conscientiousness, openness to experience, and emotional stability traits are positively correlated to SP. In contrast, agreeableness is not highly correlated with SP relatively than the remainder traits. Additionally, results revealed the significant effect of technology as a moderator which strengthens the association of FFM and SP. This study proposes diverse managerial implications and future directions for practitioners and academicians across the nations.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133306716","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}
Pub Date : 2019-07-01DOI: 10.4018/IJISSS.2019070103
R. Alguliyev, R. Aliguliyev, Gunay Y. Niftaliyeva
Nowadays, improvement of governance, ensuring security and timely detection of propaganda against the government are major problems of e-government. The extraction of hidden social networks operating against the state in e-government is one of the key factors to ensure the security in e-government. In this article, a method has been proposed for extracting hidden social networks to improve e-government management, prevent promotion against the government and ensure the security. In this approach, hidden social networks are extracted through the analysis of user's comments via opinion and text mining technologies. The authors assume that all comments are written in one language. Unlike previous methods, to detect social relationships between actors, content analysis technology, namely opinion mining technology was used in the proposed approach.
{"title":"A Method for Social Network Extraction From E-Government","authors":"R. Alguliyev, R. Aliguliyev, Gunay Y. Niftaliyeva","doi":"10.4018/IJISSS.2019070103","DOIUrl":"https://doi.org/10.4018/IJISSS.2019070103","url":null,"abstract":"Nowadays, improvement of governance, ensuring security and timely detection of propaganda against the government are major problems of e-government. The extraction of hidden social networks operating against the state in e-government is one of the key factors to ensure the security in e-government. In this article, a method has been proposed for extracting hidden social networks to improve e-government management, prevent promotion against the government and ensure the security. In this approach, hidden social networks are extracted through the analysis of user's comments via opinion and text mining technologies. The authors assume that all comments are written in one language. Unlike previous methods, to detect social relationships between actors, content analysis technology, namely opinion mining technology was used in the proposed approach.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"107 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":"117249065","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}
Pub Date : 2019-07-01DOI: 10.4018/IJISSS.2019070104
Jinluan Ren, W. Cao, Bo Li, Lihua Liu, Lin Cai, Ruben Xing
Public accounts on social media have become important channels for information dissemination. Well-designed public social media accounts are vital to better communicate science and technology (S-T) achievements. This article defines the S-T communication concept and proposes the analyzing dimensions. In order to measure the communication effect, this research collected 7,246 articles from S-T public accounts on WeChat. We analysis these massive data incorporating neural network (NN) and multivariate linear regression (MLR) model. The evaluation indicator system of communication effect includes three levels indicators. The research found the following factors affecting the S-T communication effect in different degrees: the number of active fans on Science Technology Public Accounts on Social Media (STPA-SM), locations where the articles are published, the authentication status of STPA-SM, and so on. Finally, the article proposes some strategic suggestions for improving the communication effects of S-T achievements through STPA-SM.
社交媒体上的公众账号已经成为信息传播的重要渠道。精心设计的公共社交媒体账户对于更好地传播科技成果至关重要。本文界定了S-T通信的概念，提出了S-T通信的分析维度。为了衡量传播效果，本研究收集了微信S-T公众号的7246篇文章。我们利用神经网络(NN)和多元线性回归(MLR)模型对这些海量数据进行分析。沟通效果评价指标体系包括三个层次的指标。研究发现，科技公众账号(Science Technology Public Accounts on Social Media，简称STPA-SM)的活跃粉丝数量、文章发布地点、STPA-SM的认证状态等因素对科技传播效果有不同程度的影响。最后，本文提出了通过STPA-SM提高科技成果传播效果的策略建议。
{"title":"Big-Data Based Analysis for Communication Effect of Science-Technology Public Accounts on Social Media","authors":"Jinluan Ren, W. Cao, Bo Li, Lihua Liu, Lin Cai, Ruben Xing","doi":"10.4018/IJISSS.2019070104","DOIUrl":"https://doi.org/10.4018/IJISSS.2019070104","url":null,"abstract":"Public accounts on social media have become important channels for information dissemination. Well-designed public social media accounts are vital to better communicate science and technology (S-T) achievements. This article defines the S-T communication concept and proposes the analyzing dimensions. In order to measure the communication effect, this research collected 7,246 articles from S-T public accounts on WeChat. We analysis these massive data incorporating neural network (NN) and multivariate linear regression (MLR) model. The evaluation indicator system of communication effect includes three levels indicators. The research found the following factors affecting the S-T communication effect in different degrees: the number of active fans on Science Technology Public Accounts on Social Media (STPA-SM), locations where the articles are published, the authentication status of STPA-SM, and so on. Finally, the article proposes some strategic suggestions for improving the communication effects of S-T achievements through STPA-SM.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"1 4 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":"128673005","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}
Pub Date : 2019-07-01DOI: 10.4018/IJISSS.2019070105
Hossein Arabi, Vimala Balakrishnan
Personalized Recommendation Systems (RS) provide end users with suggestions about items that are likely to be of their interest based on users' details such as demographics, location, time, and emotion. In this article, a Personalized Hybrid Book Recommender (PHyBR) is presented, which integrates personality traits with users' demographic data and geographical location to improve the quality of recommendations. The Ten Item Personality Inventory (TIPI) was used to determine users' personality traits. PHyBR was evaluated using two metrics, that are, Standardized Root Mean Square Residual (SRMR) and Root Mean Square Error of Approximation (RMSEA). Both metrics revealed PHyBR outperforms the baseline models (without considering personality traits and geographical location factor) in terms of the recommendation accuracies. This study shows that users who are in the same geographical contexts intend to have similar preferences. Therefore, users' personality details along with their geographical locations can be used to provide improved personalized recommendations.
{"title":"Personalized Hybrid Book Recommender","authors":"Hossein Arabi, Vimala Balakrishnan","doi":"10.4018/IJISSS.2019070105","DOIUrl":"https://doi.org/10.4018/IJISSS.2019070105","url":null,"abstract":"Personalized Recommendation Systems (RS) provide end users with suggestions about items that are likely to be of their interest based on users' details such as demographics, location, time, and emotion. In this article, a Personalized Hybrid Book Recommender (PHyBR) is presented, which integrates personality traits with users' demographic data and geographical location to improve the quality of recommendations. The Ten Item Personality Inventory (TIPI) was used to determine users' personality traits. PHyBR was evaluated using two metrics, that are, Standardized Root Mean Square Residual (SRMR) and Root Mean Square Error of Approximation (RMSEA). Both metrics revealed PHyBR outperforms the baseline models (without considering personality traits and geographical location factor) in terms of the recommendation accuracies. This study shows that users who are in the same geographical contexts intend to have similar preferences. Therefore, users' personality details along with their geographical locations can be used to provide improved personalized recommendations.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"59 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":"126316640","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}
Pub Date : 2019-07-01DOI: 10.4018/IJISSS.2019070101
S. Valsamidis, I. Petasakis, Sotirios Kontogiannis, Fotini Perdiki
The Greek taxation information system is now in the second decade of its operation. Although many weaknesses were recorded in the first decade, it has been operating sufficiently well during the last five years. One critical factor for the satisfactory performance for each information system is the acceptance by its users. The purpose of this study is to investigate the parameters affecting the positive or negative intentions in the use of information systems by tax office employees, as well as their contribution to the transactions between the public and private sectors and their effects. This article focuses on three important factors: (1) those that affect the acceptance of e-government systems by employees, (2) those that affect employees' intention to accept the e-government services, and (3) the contribution of information systems to electronic transactions their effects. In particular, research is done to identify the parameters that affect the intentions for using TAXIS platform by tax office employees of four branches in the Region of Eastern Macedonia and Thrace.
{"title":"Factors of Usage Evaluation for a Tax Information System","authors":"S. Valsamidis, I. Petasakis, Sotirios Kontogiannis, Fotini Perdiki","doi":"10.4018/IJISSS.2019070101","DOIUrl":"https://doi.org/10.4018/IJISSS.2019070101","url":null,"abstract":"The Greek taxation information system is now in the second decade of its operation. Although many weaknesses were recorded in the first decade, it has been operating sufficiently well during the last five years. One critical factor for the satisfactory performance for each information system is the acceptance by its users. The purpose of this study is to investigate the parameters affecting the positive or negative intentions in the use of information systems by tax office employees, as well as their contribution to the transactions between the public and private sectors and their effects. This article focuses on three important factors: (1) those that affect the acceptance of e-government systems by employees, (2) those that affect employees' intention to accept the e-government services, and (3) the contribution of information systems to electronic transactions their effects. In particular, research is done to identify the parameters that affect the intentions for using TAXIS platform by tax office employees of four branches in the Region of Eastern Macedonia and Thrace.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"3 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":"134033526","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}
Pub Date : 2019-07-01DOI: 10.4018/IJISSS.2019070102
Sofia Benbelkacem, F. Kadri, B. Atmani, S. Chaabane
Nowadays, emergency department services are confronted to an increasing demand. This situation causes emergency department overcrowding which often increases the length of stay of patients and leads to strain situations. To overcome this issue, emergency department managers must predict the length of stay. In this work, the researchers propose to use machine learning techniques to set up a methodology that supports the management of emergency departments (EDs). The target of this work is to predict the length of stay of patients in the ED in order to prevent strain situations. The experiments were carried out on a real database collected from the pediatric emergency department (PED) in Lille regional hospital center, France. Different machine learning techniques have been used to build the best prediction models. The results seem better with Naive Bayes, C4.5 and SVM methods. In addition, the models based on a subset of attributes proved to be more efficient than models based on the set of attributes.
{"title":"Machine Learning for Emergency Department Management","authors":"Sofia Benbelkacem, F. Kadri, B. Atmani, S. Chaabane","doi":"10.4018/IJISSS.2019070102","DOIUrl":"https://doi.org/10.4018/IJISSS.2019070102","url":null,"abstract":"Nowadays, emergency department services are confronted to an increasing demand. This situation causes emergency department overcrowding which often increases the length of stay of patients and leads to strain situations. To overcome this issue, emergency department managers must predict the length of stay. In this work, the researchers propose to use machine learning techniques to set up a methodology that supports the management of emergency departments (EDs). The target of this work is to predict the length of stay of patients in the ED in order to prevent strain situations. The experiments were carried out on a real database collected from the pediatric emergency department (PED) in Lille regional hospital center, France. Different machine learning techniques have been used to build the best prediction models. The results seem better with Naive Bayes, C4.5 and SVM methods. In addition, the models based on a subset of attributes proved to be more efficient than models based on the set of attributes.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"11 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":"126756170","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}
Pub Date : 2019-04-01DOI: 10.4018/IJISSS.2019040102
Mehmet Resul Bilginci, G. Kaya, Ali Turkyilmaz
Risk is an integrated part of the banking functions, which cannot be eliminated completely but it can be reduced by employing appropriate techniques. Credit processing is one of the core functions in the banking system, and its performance is closely related to management of the risks. The aim of this article is to develop a credit scorecard model which can be used as decision support system. A logistic regression with stepwise selection method is used to estimate the model parameters. The data that is used to construct the credit scorecard model is obtained from one of the pioneering banks in Turkish Banking Sector. The performance of the developed model is tested using statistical metrics including Receiver Operator Characteristic (ROC) curve and Gini statistics. The result reveals that the model performs well and it can be used as a decision support system for managing the credit risk by managers of the banks.
{"title":"Decision Support System for Credit Risk Management: An Empirical Study","authors":"Mehmet Resul Bilginci, G. Kaya, Ali Turkyilmaz","doi":"10.4018/IJISSS.2019040102","DOIUrl":"https://doi.org/10.4018/IJISSS.2019040102","url":null,"abstract":"Risk is an integrated part of the banking functions, which cannot be eliminated completely but it can be reduced by employing appropriate techniques. Credit processing is one of the core functions in the banking system, and its performance is closely related to management of the risks. The aim of this article is to develop a credit scorecard model which can be used as decision support system. A logistic regression with stepwise selection method is used to estimate the model parameters. The data that is used to construct the credit scorecard model is obtained from one of the pioneering banks in Turkish Banking Sector. The performance of the developed model is tested using statistical metrics including Receiver Operator Characteristic (ROC) curve and Gini statistics. The result reveals that the model performs well and it can be used as a decision support system for managing the credit risk by managers of the banks.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"1999 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123790147","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}
Pub Date : 2019-04-01DOI: 10.4018/IJISSS.2019040101
Christian R. Llano, Yuan Ren, N. I. Shaikh
Object and human tracking in streaming videos are one of the most challenging problems in vision computing. In this article, we review some relevant machine learning algorithms and techniques for human identification and tracking in videos. We provide details on metrics and methods used in the computer vision literature for monitoring and propose a state-space representation of the object tracking problem. A proof of concept implementation of the state-space based object tracking using particle filters is presented as well. The proposed approach enables tracking objects/humans in a video, including foreground/background separation for object movement detection.
{"title":"Object Detection and Tracking in Real Time Videos","authors":"Christian R. Llano, Yuan Ren, N. I. Shaikh","doi":"10.4018/IJISSS.2019040101","DOIUrl":"https://doi.org/10.4018/IJISSS.2019040101","url":null,"abstract":"Object and human tracking in streaming videos are one of the most challenging problems in vision computing. In this article, we review some relevant machine learning algorithms and techniques for human identification and tracking in videos. We provide details on metrics and methods used in the computer vision literature for monitoring and propose a state-space representation of the object tracking problem. A proof of concept implementation of the state-space based object tracking using particle filters is presented as well. The proposed approach enables tracking objects/humans in a video, including foreground/background separation for object movement detection.","PeriodicalId":151306,"journal":{"name":"Int. J. Inf. Syst. Serv. Sect.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124700527","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}
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