Pub Date : 2019-09-17DOI: 10.5220/0008480504120418
V. Tripathi
In this paper, we survey the current known applications of Machine Learning based Data Analytics and automation in finance industry. We look into the challenges involved in furthering this technology, particularly in employing more Deep Learning approaches proven for successful automation in other domains. We enumerate observations on some of the barriers faced by the industry in effectively adopting and accelerating use of AI techniques, and finally propose more areas that we believe could further benefit from application of Machine Learning.
{"title":"On Present Use of Machine Learning based Automation in Finance","authors":"V. Tripathi","doi":"10.5220/0008480504120418","DOIUrl":"https://doi.org/10.5220/0008480504120418","url":null,"abstract":"In this paper, we survey the current known applications of Machine Learning based Data Analytics and automation in finance industry. We look into the challenges involved in furthering this technology, particularly in employing more Deep Learning approaches proven for successful automation in other domains. We enumerate observations on some of the barriers faced by the industry in effectively adopting and accelerating use of AI techniques, and finally propose more areas that we believe could further benefit from application of Machine Learning.","PeriodicalId":133533,"journal":{"name":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128619882","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 : 2019-09-17DOI: 10.5220/0008065501760186
J. Gupta, H. Kärkkäinen, Karan Menon, Jukka Huhtamäki, R. Mukkamala, Abid Hussain, Ravikiran Vatrapu, J. Jussila, H. Pirkkalainen, Thomas Olsson
Tie strength is an essential concept in identifying different kind of social ties - strong ties and weak ties. Most present studies that evaluated tie strength from social media were carried out in a controlled environment and used private/closed social media data. Even though social media has become a very important way of networking in professional events, access to such private social media data in those events is almost impossible. There is very limited research on how to facilitate networking between event participants and especially on how to automate this networking aspect in events using social media. Tie strength evaluated using social media will be key in automating this process of networking. To create such tie strength based event participant recommendation systems and tools in the future, first, we need to understand how to evaluate tie strength using publicly available social media data. The purpose of this study is to evaluate tie strength from publicly available social media data in the context of a professional event. Our case study environment is community managers’ online discussions in social media (Twitter and Facebook) about the CMAD2016 event in Finland. In this work, we analyzed social media data from that event to evaluate tie strength and compared the social media analysis-based findings with the individuals’ perceptions of the actual tie strengths of the event participants using a questionnaire. We present our findings and conclude with directions for future work.
{"title":"Identifying Different Types of Social Ties in Events from Publicly Available Social Media Data","authors":"J. Gupta, H. Kärkkäinen, Karan Menon, Jukka Huhtamäki, R. Mukkamala, Abid Hussain, Ravikiran Vatrapu, J. Jussila, H. Pirkkalainen, Thomas Olsson","doi":"10.5220/0008065501760186","DOIUrl":"https://doi.org/10.5220/0008065501760186","url":null,"abstract":"Tie strength is an essential concept in identifying different kind of social ties - strong ties and weak ties. Most present studies that evaluated tie strength from social media were carried out in a controlled environment and used private/closed social media data. Even though social media has become a very important way of networking in professional events, access to such private social media data in those events is almost impossible. There is very limited research on how to facilitate networking between event participants and especially on how to automate this networking aspect in events using social media. Tie strength evaluated using social media will be key in automating this process of networking. To create such tie strength based event participant recommendation systems and tools in the future, first, we need to understand how to evaluate tie strength using publicly available social media data. The purpose of this study is to evaluate tie strength from publicly available social media data in the context of a professional event. Our case study environment is community managers’ online discussions in social media (Twitter and Facebook) about the CMAD2016 event in Finland. In this work, we analyzed social media data from that event to evaluate tie strength and compared the social media analysis-based findings with the individuals’ perceptions of the actual tie strengths of the event participants using a questionnaire. We present our findings and conclude with directions for future work.","PeriodicalId":133533,"journal":{"name":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115211252","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 : 2019-09-17DOI: 10.5220/0008348803980404
Patrick Tinz, Janik Tinz, Stefan Zander
This paper analyses current and well-known knowledge management models regarding their applicability to smart factories and the Industry 4.0. In form of a literature study, we surveyed the specific challenges and requirements that smart factories and the ongoing digital transition in the industrial sector introduce to knowledge management systems and models. In the second part, we then expound the extent to which those requirements are supported by well-established knowledge management models in form of a comparative analysis. A central result of this work is that an Industry 4.0 compliant knowledge management needs to incorporate aspects that emphasize human-machine and machine-machine interaction together with data protection and privacy concerns, besides other well-researched and established aspects.
{"title":"Knowledge Management Models for the Smart Factory: A Comparative Analysis of Current Approaches","authors":"Patrick Tinz, Janik Tinz, Stefan Zander","doi":"10.5220/0008348803980404","DOIUrl":"https://doi.org/10.5220/0008348803980404","url":null,"abstract":"This paper analyses current and well-known knowledge management models regarding their applicability to smart factories and the Industry 4.0. In form of a literature study, we surveyed the specific challenges and requirements that smart factories and the ongoing digital transition in the industrial sector introduce to knowledge management systems and models. In the second part, we then expound the extent to which those requirements are supported by well-established knowledge management models in form of a comparative analysis. A central result of this work is that an Industry 4.0 compliant knowledge management needs to incorporate aspects that emphasize human-machine and machine-machine interaction together with data protection and privacy concerns, besides other well-researched and established aspects.","PeriodicalId":133533,"journal":{"name":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121757933","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 : 2019-09-17DOI: 10.5220/0008067501870194
J. Gupta, H. Kärkkäinen, Osku Torro, R. Mukkamala
The strength of social ties has an impact on how information is transferred and processed in a social network. Many studies have used social media data to evaluate tie strength. However, many of these studies were done at a time when social media data could be accessed legally without using the social media platform API. In the past few years, there have been significant changes in the data access policies of these platforms, which has led to a considerable reduction in the possibilities of using social media data for tie strength evaluation. The paper aims to study the impact of the data access policy changes of major social media platforms on the existing social media based tie strength models. The findings of this study show that the existing social media based tie strength models can no longer be utilized in their current form. Our study suggests that there is either a need to modify the existing social media based tie strength models or to develop new social media based tie strength models that reflect the recent changes in the data access policies.
{"title":"Revisiting Social Media Tie Strength in the Era of Data Access Restrictions","authors":"J. Gupta, H. Kärkkäinen, Osku Torro, R. Mukkamala","doi":"10.5220/0008067501870194","DOIUrl":"https://doi.org/10.5220/0008067501870194","url":null,"abstract":"The strength of social ties has an impact on how information is transferred and processed in a social network. Many studies have used social media data to evaluate tie strength. However, many of these studies were done at a time when social media data could be accessed legally without using the social media platform API. In the past few years, there have been significant changes in the data access policies of these platforms, which has led to a considerable reduction in the possibilities of using social media data for tie strength evaluation. The paper aims to study the impact of the data access policy changes of major social media platforms on the existing social media based tie strength models. The findings of this study show that the existing social media based tie strength models can no longer be utilized in their current form. Our study suggests that there is either a need to modify the existing social media based tie strength models or to develop new social media based tie strength models that reflect the recent changes in the data access policies.","PeriodicalId":133533,"journal":{"name":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126480499","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 : 2019-09-17DOI: 10.5220/0008353603330340
K. Rabuzin, Nikola Modrusan
The protection of citizens’ public financial resources through advanced corruption detection models in public procurement has become an almost inevitable topic and the subject of numerous studies. Since it almost always focuses on the prediction of corrupt competition, the calculation of various indices and indications of corruption to the data itself are very difficult to come by. These data sets usually have very few observations, especially accurately labelled ones. The prevention or detection of compromised public procurement processes is definitely a crucial step, related to the initial phase of public procurement, i.e., the phase of publication of the notice. The aim of this paper is to compare prediction models using text-mining techniques and machine-learning methods to detect suspicious tenders, and to develop a model to detect suspicious one-bid tenders. Consequently, we have analyzed tender documentation for particular tenders, extracted the content of interest about the levels of all bids and grouped it by procurement lots using machine-learning methods. A model that includes the aforementioned components uses the most common text classification algorithms for the purpose of prediction: naive Bayes, logistic regression and support vector machines. The results of the research showed that knowledge in the tender documentation can be used for detection suspicious tenders.
{"title":"Prediction of Public Procurement Corruption Indices using Machine Learning Methods","authors":"K. Rabuzin, Nikola Modrusan","doi":"10.5220/0008353603330340","DOIUrl":"https://doi.org/10.5220/0008353603330340","url":null,"abstract":"The protection of citizens’ public financial resources through advanced corruption detection models in public procurement has become an almost inevitable topic and the subject of numerous studies. Since it almost always focuses on the prediction of corrupt competition, the calculation of various indices and indications of corruption to the data itself are very difficult to come by. These data sets usually have very few observations, especially accurately labelled ones. The prevention or detection of compromised public procurement processes is definitely a crucial step, related to the initial phase of public procurement, i.e., the phase of publication of the notice. The aim of this paper is to compare prediction models using text-mining techniques and machine-learning methods to detect suspicious tenders, and to develop a model to detect suspicious one-bid tenders. Consequently, we have analyzed tender documentation for particular tenders, extracted the content of interest about the levels of all bids and grouped it by procurement lots using machine-learning methods. A model that includes the aforementioned components uses the most common text classification algorithms for the purpose of prediction: naive Bayes, logistic regression and support vector machines. The results of the research showed that knowledge in the tender documentation can be used for detection suspicious tenders.","PeriodicalId":133533,"journal":{"name":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","volume":"311 15","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120875640","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 : 2019-09-17DOI: 10.5220/0008332502190224
Kenzaburo Miyawaki, Soichi Okabe
Mixed Reality (MR) is a technique to represent scenes which make virtual objects exist in the real world. MR is different from Augmented Reality (AR) and Virtual Reality (VR). For example, in MR scenes, a user can put a virtual Computer Graphics (CG) object on a desk of the real world. The virtual object can interact with the real desk physically, and the user can see the virtual object from every direction. However, MR only uses position and shape information of real world objects. Therefore, we present a new MR scene generator considering real world objects’ physical characteristics such as friction, repulsion and so on, by using material recognition based on a deep neural network.
{"title":"Material Recognition for Mixed Reality Scene including Objects' Physical Characteristics","authors":"Kenzaburo Miyawaki, Soichi Okabe","doi":"10.5220/0008332502190224","DOIUrl":"https://doi.org/10.5220/0008332502190224","url":null,"abstract":"Mixed Reality (MR) is a technique to represent scenes which make virtual objects exist in the real world. MR is different from Augmented Reality (AR) and Virtual Reality (VR). For example, in MR scenes, a user can put a virtual Computer Graphics (CG) object on a desk of the real world. The virtual object can interact with the real desk physically, and the user can see the virtual object from every direction. However, MR only uses position and shape information of real world objects. Therefore, we present a new MR scene generator considering real world objects’ physical characteristics such as friction, repulsion and so on, by using material recognition based on a deep neural network.","PeriodicalId":133533,"journal":{"name":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121524748","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 : 2019-09-17DOI: 10.5220/0008343802250230
A. Goy, Cristina Accornero, Dunia Astrologo, Davide Colla, M. D'Ambrosio, R. Damiano, Marco Leontino, Antonio Lieto, F. Loreto, Diego Magro, Enrico Mensa, Alice Montanaro, Valeria Mosca, S. Musso, Daniele P. Radicioni, Christopher Ré
In this paper we present the mid-term results of the PRiSMHA project, aimed to contribute in building a digital “smart archivist”, i.e., a web-based system providing an innovative access to historical archives. Such a system is endowed with a semantic layer over existing archival metadata, including computational ontologies and a knowledge base, containing a formal description of the content of the documents stored in the archives. The paper focuses on the fruitful synergies employed to reach its goal. In particular, it explains the steps of the “spiral” process implemented for creating a full-fledged formal semantic model, through the interaction between computer scientists, historians, and archivists. The paper also presents some “core side-effects” of this process: an analytical card for each document has been produced, all selected documents have been digitized, OCR-ized (when possible), and linked to a record on the archival platform. This experience enabled us to define a virtuous procedural model, from the paper documents up to the digital “smart archivist”, based on a close collaboration between universities and cultural and historical institutions.
{"title":"Fruitful Synergies between Computer Science, Historical Studies and Archives: The Experience in the PRiSMHA Project","authors":"A. Goy, Cristina Accornero, Dunia Astrologo, Davide Colla, M. D'Ambrosio, R. Damiano, Marco Leontino, Antonio Lieto, F. Loreto, Diego Magro, Enrico Mensa, Alice Montanaro, Valeria Mosca, S. Musso, Daniele P. Radicioni, Christopher Ré","doi":"10.5220/0008343802250230","DOIUrl":"https://doi.org/10.5220/0008343802250230","url":null,"abstract":"In this paper we present the mid-term results of the PRiSMHA project, aimed to contribute in building a digital “smart archivist”, i.e., a web-based system providing an innovative access to historical archives. Such a system is endowed with a semantic layer over existing archival metadata, including computational ontologies and a knowledge base, containing a formal description of the content of the documents stored in the archives. The paper focuses on the fruitful synergies employed to reach its goal. In particular, it explains the steps of the “spiral” process implemented for creating a full-fledged formal semantic model, through the interaction between computer scientists, historians, and archivists. The paper also presents some “core side-effects” of this process: an analytical card for each document has been produced, all selected documents have been digitized, OCR-ized (when possible), and linked to a record on the archival platform. This experience enabled us to define a virtuous procedural model, from the paper documents up to the digital “smart archivist”, based on a close collaboration between universities and cultural and historical institutions.","PeriodicalId":133533,"journal":{"name":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","volume":"204 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123372611","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 : 2019-09-17DOI: 10.5220/0008349902990306
F. Pani, Giacomo Ibba, M. Marchesi, A. Pinna, S. Porru, R. Tonelli, Bartolomeo Valcalda
Ever-growing digitalization and increasingly competitive markets are driving industry and the public sector into fast-paced transformation. Competitive advantage is being acquired through technology investments made possible by previously unavailable resources, freed by process automation, simplification, and rationalization. Under these contingencies, we propose an innovative document management platform, featuring a collaborative document editing technique and a blockchain certification procedure. The two proposing parties - a private company and an academic organization - mutually agreed on employing open-source technologies as a strategic means to promote software reuse and developer communities’ support, and consequently reduce implementation costs and ensure interoperability.
{"title":"Blockchain Certification and Granular Editing Permissions in Document Management System","authors":"F. Pani, Giacomo Ibba, M. Marchesi, A. Pinna, S. Porru, R. Tonelli, Bartolomeo Valcalda","doi":"10.5220/0008349902990306","DOIUrl":"https://doi.org/10.5220/0008349902990306","url":null,"abstract":"Ever-growing digitalization and increasingly competitive markets are driving industry and the public sector into fast-paced transformation. Competitive advantage is being acquired through technology investments made possible by previously unavailable resources, freed by process automation, simplification, and rationalization. Under these contingencies, we propose an innovative document management platform, featuring a collaborative document editing technique and a blockchain certification procedure. The two proposing parties - a private company and an academic organization - mutually agreed on employing open-source technologies as a strategic means to promote software reuse and developer communities’ support, and consequently reduce implementation costs and ensure interoperability.","PeriodicalId":133533,"journal":{"name":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116844726","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 : 2019-09-17DOI: 10.5220/0008069201950202
J. M. V. Cedeño, L. Hannola, V. Ojanen
Recent research have addressed the topic of smart services from distinct angles, covering both technical and business aspects. However, a holistic approach in development processes of such services have yet to be fully covered. Therefore, this paper proposes an elicitation of requirements process as the initial step of a smart service design approach. The process takes information and knowledge needs as its core element for development, also considering customer centricity, service lifecycle, and sustainability concerns. A text mining tool was used to discover the unknown knowledge requirements from different text-data sources presented in a case ecosystem. After a co-occurrence analysis performed by our text mining software, we extracted the most relevant natural linguistic elements, which are expressed as knowledge requirements. The proposed elicitation process aims to lay the foundations for further propositions with a holistic point of view. Future research could aim the application of other technologies and methods for service design, as well as a broader approach in business processes and interdisciplinary cooperation.
{"title":"Knowledge Requirements for Sustainable Smart Service Design","authors":"J. M. V. Cedeño, L. Hannola, V. Ojanen","doi":"10.5220/0008069201950202","DOIUrl":"https://doi.org/10.5220/0008069201950202","url":null,"abstract":"Recent research have addressed the topic of smart services from distinct angles, covering both technical and business aspects. However, a holistic approach in development processes of such services have yet to be fully covered. Therefore, this paper proposes an elicitation of requirements process as the initial step of a smart service design approach. The process takes information and knowledge needs as its core element for development, also considering customer centricity, service lifecycle, and sustainability concerns. A text mining tool was used to discover the unknown knowledge requirements from different text-data sources presented in a case ecosystem. After a co-occurrence analysis performed by our text mining software, we extracted the most relevant natural linguistic elements, which are expressed as knowledge requirements. The proposed elicitation process aims to lay the foundations for further propositions with a holistic point of view. Future research could aim the application of other technologies and methods for service design, as well as a broader approach in business processes and interdisciplinary cooperation.","PeriodicalId":133533,"journal":{"name":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126227557","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 : 2019-09-17DOI: 10.5220/0008119902030211
Tareq Salahi Almigheerbi, David Ramsey, Anna Lamek
Evaluating the performance of information systems (ISs) has emerged from the increasing influence of information technology on the effectiveness and efficiency of work processes in an organization (Bryman and Bell 2007). The aim of the overall study is to overcome a lack in the literature regarding the assessment of information systems (IS) in Libyan Higher Education (LHE), especially universities. The aim of this initial article is to focus on the University of Tripoli (UOT), a study that will be extended to other Libyan public universities. A description of the study, its significance and objectives and the methodology followed are presented, together with an analysis of the findings on the basis of appropriately chosen models. Finally, we assess the current level of ISs implemented in UOT by analyzing the findings based on these models.
信息技术对组织中工作流程的有效性和效率的影响越来越大，信息系统(ISs)的性能评估也随之出现(Bryman and Bell 2007)。整体研究的目的是克服文献中关于利比亚高等教育(LHE)，特别是大学信息系统(is)评估的不足。本文最初的目的是关注的黎波里大学(UOT)，这项研究将扩展到其他利比亚公立大学。介绍了这项研究的描述，其意义和目标以及所采用的方法，并根据适当选择的模型对研究结果进行了分析。最后，通过分析基于这些模型的结果，我们评估了当前UOT中实施的ISs水平。
{"title":"Evaluation of the Performance of Information Systems Implemented at the University of Tripoli, Libya","authors":"Tareq Salahi Almigheerbi, David Ramsey, Anna Lamek","doi":"10.5220/0008119902030211","DOIUrl":"https://doi.org/10.5220/0008119902030211","url":null,"abstract":"Evaluating the performance of information systems (ISs) has emerged from the increasing influence of information technology on the effectiveness and efficiency of work processes in an organization (Bryman and Bell 2007). The aim of the overall study is to overcome a lack in the literature regarding the assessment of information systems (IS) in Libyan Higher Education (LHE), especially universities. The aim of this initial article is to focus on the University of Tripoli (UOT), a study that will be extended to other Libyan public universities. A description of the study, its significance and objectives and the methodology followed are presented, together with an analysis of the findings on the basis of appropriately chosen models. Finally, we assess the current level of ISs implemented in UOT by analyzing the findings based on these models.","PeriodicalId":133533,"journal":{"name":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121825480","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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