Pub Date : 2019-03-01DOI: 10.1109/INFOCT.2019.8711319
A. Mubarakali, A. Alqahtani
Nowadays, the Software-Defined Networking (SDN) is the most important part of research work. SDN offers numerous benefits including on-demand provisioning, automated load balancing, streamlined physical infrastructure and the ability to scale network resources as per the need. SDN has the ability to manage network traffic through software and the administrator gain a much greater degree of control, which provides the ability to change network rules on the fly. In the near future, SDN can replace traditional networking. At the similar time, suspicious awareness necessitates being paid to protection at the early planning phase. In the paper majorly concentrates on the protection attributes of SDN. It starts by examining the architecture of SDN. Along with the design structure, we design the probable protection faults in SDN. Finally discuss various threats and its countermeasures based on three-layer architecture, i.e. data forwarding layer, the control layer, and the application layer. Additionally, those different defensive techniques are highlighted.
{"title":"A Survey: Security Threats and Countermeasures in Software Defined Networking","authors":"A. Mubarakali, A. Alqahtani","doi":"10.1109/INFOCT.2019.8711319","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8711319","url":null,"abstract":"Nowadays, the Software-Defined Networking (SDN) is the most important part of research work. SDN offers numerous benefits including on-demand provisioning, automated load balancing, streamlined physical infrastructure and the ability to scale network resources as per the need. SDN has the ability to manage network traffic through software and the administrator gain a much greater degree of control, which provides the ability to change network rules on the fly. In the near future, SDN can replace traditional networking. At the similar time, suspicious awareness necessitates being paid to protection at the early planning phase. In the paper majorly concentrates on the protection attributes of SDN. It starts by examining the architecture of SDN. Along with the design structure, we design the probable protection faults in SDN. Finally discuss various threats and its countermeasures based on three-layer architecture, i.e. data forwarding layer, the control layer, and the application layer. Additionally, those different defensive techniques are highlighted.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132282081","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 : 2019-03-01DOI: 10.1109/INFOCT.2019.8710894
Meng Zhu, Xudong Yang
In this article, we designed an automatic Chinese text classification system aiming to implement a system for classifying news texts. We propose two improved classification algorithms as two different choices for users to choose and then our system uses the chosen method for the obtaining of the classified result of the input text. There are two improved algorithms, one is k-Bayes using hierarchy conception based on NB method in machine learning field and another one adds attention layer to the convolutional neural network in deep learning field. Through experiments, our results showed that improved classification algorithms had better accuracy than based algorithms and our system is useful for making classifying news texts more reasonably and effectively.
{"title":"Chinese Texts Classification System","authors":"Meng Zhu, Xudong Yang","doi":"10.1109/INFOCT.2019.8710894","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8710894","url":null,"abstract":"In this article, we designed an automatic Chinese text classification system aiming to implement a system for classifying news texts. We propose two improved classification algorithms as two different choices for users to choose and then our system uses the chosen method for the obtaining of the classified result of the input text. There are two improved algorithms, one is k-Bayes using hierarchy conception based on NB method in machine learning field and another one adds attention layer to the convolutional neural network in deep learning field. Through experiments, our results showed that improved classification algorithms had better accuracy than based algorithms and our system is useful for making classifying news texts more reasonably and effectively.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128008765","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 : 2019-03-01DOI: 10.1109/INFOCT.2019.8711413
J. Yang, Kwang Sik Chung
Nowadays, based-on mobile devices and internet, social network services(SNS) are common trends to everyone. Thus, decision of social and public opinions, and polarity about social happenings, political issues, government policies and decision, or commercial products is very important to the government, company, and a person. But, SNS are basically making newly-coined words and emoticons. Especially, emoticons are made by a person or companies. Newly-coined words are mostly made by communities. The SNS big data mainly consists of his kinds of newly-coined words and emoticons so that newly-coined words and emoticons analysis are very important to understand the social and public opinions, and polarity about social happenings, political issues, government policies and decision, or commercial products. Social big data is unstructured data and contains many newly-coined words and various emoticons. Therefore, there is a limitation to guarantee the accuracy and analysis range of social data of emotional analysis. The newly-coined words contains the social phenomena and trends of modern society implicitly. And the emoticons are electronic quasi-languages made up of letters and symbols, and express the emotional state more implicitly. Although the newly-coined words and emoticons are an important part of the emotional analysis, they are excluded from the emotional dictionary and analysis. In this research, newly-coined words and emoticons extracted from the raw twit messages include polarity and weight with pre-built dictionary. The polarity and weight would be calculated for emotional classification. The proposed emotional classification equation adds up the weights among the same polarity(positive or negative) and sums the negative weight value with the positive weight values. The polarity summation result is recorded in the variable. If the polarity summation result is more than threshold value, the twit message is decided as positive. If it is less than threshold value, it is decided as negative and the other values are decided as neutral. The accuracy of social big data analysis is improved by quantifying and analyzing emoticons and new-coined words.
{"title":"Newly-Coined Words and Emoticon Polarity for Social Emotional Opinion Decision","authors":"J. Yang, Kwang Sik Chung","doi":"10.1109/INFOCT.2019.8711413","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8711413","url":null,"abstract":"Nowadays, based-on mobile devices and internet, social network services(SNS) are common trends to everyone. Thus, decision of social and public opinions, and polarity about social happenings, political issues, government policies and decision, or commercial products is very important to the government, company, and a person. But, SNS are basically making newly-coined words and emoticons. Especially, emoticons are made by a person or companies. Newly-coined words are mostly made by communities. The SNS big data mainly consists of his kinds of newly-coined words and emoticons so that newly-coined words and emoticons analysis are very important to understand the social and public opinions, and polarity about social happenings, political issues, government policies and decision, or commercial products. Social big data is unstructured data and contains many newly-coined words and various emoticons. Therefore, there is a limitation to guarantee the accuracy and analysis range of social data of emotional analysis. The newly-coined words contains the social phenomena and trends of modern society implicitly. And the emoticons are electronic quasi-languages made up of letters and symbols, and express the emotional state more implicitly. Although the newly-coined words and emoticons are an important part of the emotional analysis, they are excluded from the emotional dictionary and analysis. In this research, newly-coined words and emoticons extracted from the raw twit messages include polarity and weight with pre-built dictionary. The polarity and weight would be calculated for emotional classification. The proposed emotional classification equation adds up the weights among the same polarity(positive or negative) and sums the negative weight value with the positive weight values. The polarity summation result is recorded in the variable. If the polarity summation result is more than threshold value, the twit message is decided as positive. If it is less than threshold value, it is decided as negative and the other values are decided as neutral. The accuracy of social big data analysis is improved by quantifying and analyzing emoticons and new-coined words.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116015667","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 : 2019-03-01DOI: 10.1109/infoct.2019.8711154
Farnaz Arab, M. Zamani, Sofya Poger, Carol Manigault, Songmei Yu
This paper focuses on the current challenging problems of video watermarking techniques, especially the robustness of spatial domain. This paper starts with background of the problem, and then illustrates a framework to evaluate the performance of video watermarking techniques.
{"title":"A Framework to Evaluate the Performance of Video Watermarking Techniques","authors":"Farnaz Arab, M. Zamani, Sofya Poger, Carol Manigault, Songmei Yu","doi":"10.1109/infoct.2019.8711154","DOIUrl":"https://doi.org/10.1109/infoct.2019.8711154","url":null,"abstract":"This paper focuses on the current challenging problems of video watermarking techniques, especially the robustness of spatial domain. This paper starts with background of the problem, and then illustrates a framework to evaluate the performance of video watermarking techniques.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114652445","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 : 2019-03-01DOI: 10.1109/infoct.2019.8710867
Xiao Wenjuan, Mai Xiaoqin
The low voltage ride through capability of wind turbines is an important indicator to measure the ability of wind power systems to be connected to the grid. With traditional control strategy, the low voltage ride-through capability with direct drive permanent magnet synchronous wind power generation system has limited. This paper improves the LVRT capability of DPMG by adding a chopper protection circuit with energy storage device to the DC side of wind power system. In this paper, the control method of Chopper protection circuit with energy storage device, the selection of energy storage components and the control principle of bidirectional converter are analyzed. The improved circuit is simulated by MATLAB/simulink. The result proves that when the grid voltage drops, the existence of the chopper protection circuit with energy storage components can maintain the input and output power balance of the system in a short time, stabilize the DC side voltage, and improve the low voltage ride through capability of the wind turbine.
{"title":"Research on Wind Power Generation Low Voltage Ride-through Protection Circuit Based on Energy Storage Component","authors":"Xiao Wenjuan, Mai Xiaoqin","doi":"10.1109/infoct.2019.8710867","DOIUrl":"https://doi.org/10.1109/infoct.2019.8710867","url":null,"abstract":"The low voltage ride through capability of wind turbines is an important indicator to measure the ability of wind power systems to be connected to the grid. With traditional control strategy, the low voltage ride-through capability with direct drive permanent magnet synchronous wind power generation system has limited. This paper improves the LVRT capability of DPMG by adding a chopper protection circuit with energy storage device to the DC side of wind power system. In this paper, the control method of Chopper protection circuit with energy storage device, the selection of energy storage components and the control principle of bidirectional converter are analyzed. The improved circuit is simulated by MATLAB/simulink. The result proves that when the grid voltage drops, the existence of the chopper protection circuit with energy storage components can maintain the input and output power balance of the system in a short time, stabilize the DC side voltage, and improve the low voltage ride through capability of the wind turbine.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123409350","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 : 2019-03-01DOI: 10.1109/INFOCT.2019.8710891
S. Al-Fedaghi, Mona Al-Otaibi
This paper concerns the intersection of enterprise models and IT services. In particular, it focuses on modeling in IT customer relationship management as a process-oriented control. The paper’s case study relates to an Information Technology Infrastructure Library processes project in a government ministry. The research objective is to model the organization’s customer relationship management system based on a recently proposed conceptual model: an abstract thinging machine. This model is used to depict conceptual (application-independent) machines in customer relationship management systems. The paper’s overarching question is whether thinging machines produce models that are as viable as those produced by methodologies such as Unified Modeling Language and Object-Process Methodology.
{"title":"Service-Oriented Systems as A Thining Machine: A Case Study of Customer Relationship Management","authors":"S. Al-Fedaghi, Mona Al-Otaibi","doi":"10.1109/INFOCT.2019.8710891","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8710891","url":null,"abstract":"This paper concerns the intersection of enterprise models and IT services. In particular, it focuses on modeling in IT customer relationship management as a process-oriented control. The paper’s case study relates to an Information Technology Infrastructure Library processes project in a government ministry. The research objective is to model the organization’s customer relationship management system based on a recently proposed conceptual model: an abstract thinging machine. This model is used to depict conceptual (application-independent) machines in customer relationship management systems. The paper’s overarching question is whether thinging machines produce models that are as viable as those produced by methodologies such as Unified Modeling Language and Object-Process Methodology.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129162892","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 : 2019-03-01DOI: 10.1109/INFOCT.2019.8710851
Yuliska, T. Sakai
Query-focused multi-document summarization aims to produce a single, short document that summarizes a set of documents that are relevant to a given query. During the past few years, deep learning approaches have been utilized to generate summaries in an abstractive or extractive manner. In this study, we employ six deep neural network approaches to solving a query-focused extractive multi-document summarization task and compare their performances. To the best of our knowledge, our study is the first to compare deep learning techniques on extractive query-focused multi-document summarization. Our experiments with DUC 2005–2007 benchmark datasets show that Bi-LSTM with Max-pooling achieves the highest performance among the methods compared.
{"title":"A Comparative Study of Deep Learning Approaches for Query-Focused Extractive Multi-Document Summarization","authors":"Yuliska, T. Sakai","doi":"10.1109/INFOCT.2019.8710851","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8710851","url":null,"abstract":"Query-focused multi-document summarization aims to produce a single, short document that summarizes a set of documents that are relevant to a given query. During the past few years, deep learning approaches have been utilized to generate summaries in an abstractive or extractive manner. In this study, we employ six deep neural network approaches to solving a query-focused extractive multi-document summarization task and compare their performances. To the best of our knowledge, our study is the first to compare deep learning techniques on extractive query-focused multi-document summarization. Our experiments with DUC 2005–2007 benchmark datasets show that Bi-LSTM with Max-pooling achieves the highest performance among the methods compared.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"84 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116372693","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 : 2019-03-01DOI: 10.1109/infoct.2019.8711298
Mohammed A. Gharawi, Khalid M. Al Hamed, Hashim H. Alneami
This study attempts to analyze the content of the National Open Data Platform (NODP) of the Kingdom of Saudi Arabia (KSA) in two time intervals with the aim of identifying the main developments occurred with regard to participants, available datasets and the aspects they cover, as well as the volume, quantity and quality of available data. The researchers attempted, through the study, to evaluate the applicability of the original eight principles of open data (OD) regarding data available on the Platform. The study concluded that the data that are now available through the NODP are timely, accessible, machine processable, non-discriminatory, and license-free. It also concluded that there are three OD principles that are not applied. These three principles relate to the data being complete, primary, and available in open formats. The study concluded with a set of recommendations that should enhance tendency towards implementing OD in the KSA.
{"title":"Compliance with Open Data Principles: A Longitudinal Content Analysis of the Saudi’s National Open Data Platform in 2016 and 2018","authors":"Mohammed A. Gharawi, Khalid M. Al Hamed, Hashim H. Alneami","doi":"10.1109/infoct.2019.8711298","DOIUrl":"https://doi.org/10.1109/infoct.2019.8711298","url":null,"abstract":"This study attempts to analyze the content of the National Open Data Platform (NODP) of the Kingdom of Saudi Arabia (KSA) in two time intervals with the aim of identifying the main developments occurred with regard to participants, available datasets and the aspects they cover, as well as the volume, quantity and quality of available data. The researchers attempted, through the study, to evaluate the applicability of the original eight principles of open data (OD) regarding data available on the Platform. The study concluded that the data that are now available through the NODP are timely, accessible, machine processable, non-discriminatory, and license-free. It also concluded that there are three OD principles that are not applied. These three principles relate to the data being complete, primary, and available in open formats. The study concluded with a set of recommendations that should enhance tendency towards implementing OD in the KSA.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125554036","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 : 2019-03-01DOI: 10.1109/INFOCT.2019.8710921
Long Chen
Natural language processing (NLP) have been recently used to extract clinical information from free text in Electronic Health Record (EHR). In clinical NLP one challenge is that the meaning of clinical entities is heavily affected by assertion modifiers such as negation, uncertain, hypothetical, experiencer and so on. Incorrect assertion assignment could cause inaccurate diagnosis of patients’ condition or negatively influence following study like disease modeling. Thus, clinical NLP systems which can detect assertion status of given target medical findings (e.g. disease, symptom) in clinical context are highly demanded. Here in this work, we propose a deep-learning system based on word embedding, RNN and attention mechanism (more specifically: Attention-based Bidirectional Long Short-Term Memory networks) for assertion detection in clinical notes. Unlike previous state-of-art methods which require knowledge input or feature engineering, our system is a knowledge poor machine learning system and can be easily extended or transferred to other domains. The evaluation of our system on public benchmarking corpora demonstrates that a knowledge poor deep-learning system can also achieve high performance for detecting negation and assertions comparing to state-of-the-art systems.
{"title":"Assertion Detection in Clinical Natural Language Processing: A Knowledge-Poor Machine Learning Approach","authors":"Long Chen","doi":"10.1109/INFOCT.2019.8710921","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8710921","url":null,"abstract":"Natural language processing (NLP) have been recently used to extract clinical information from free text in Electronic Health Record (EHR). In clinical NLP one challenge is that the meaning of clinical entities is heavily affected by assertion modifiers such as negation, uncertain, hypothetical, experiencer and so on. Incorrect assertion assignment could cause inaccurate diagnosis of patients’ condition or negatively influence following study like disease modeling. Thus, clinical NLP systems which can detect assertion status of given target medical findings (e.g. disease, symptom) in clinical context are highly demanded. Here in this work, we propose a deep-learning system based on word embedding, RNN and attention mechanism (more specifically: Attention-based Bidirectional Long Short-Term Memory networks) for assertion detection in clinical notes. Unlike previous state-of-art methods which require knowledge input or feature engineering, our system is a knowledge poor machine learning system and can be easily extended or transferred to other domains. The evaluation of our system on public benchmarking corpora demonstrates that a knowledge poor deep-learning system can also achieve high performance for detecting negation and assertions comparing to state-of-the-art systems.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125185203","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 : 2019-03-01DOI: 10.1109/INFOCT.2019.8711093
Y. Shaev
Rapid development of information technologies has been distinguished in recent years. Neural network technologies, which are using artificial intelligence algorithms, are becoming widespread. In accordance with the nearest futurological predictions, the state of technological singularity is approaching - the unity of man and technologies. In the framework of the approach towards technological singularity, a person tries to understand technologies and to consider them as something human-like, correlated with physicality, participation in everyday practices, and solving a wide variety of tasks. According to experts, artificial intelligence may be developed to such level that it will be harder for the human mind to „understand„ it in the nearest future. Even now, a computer is capable to solve very complicated intellectual problems, many of which previously were considered the sphere of action of the human mind. The problem of a possible „hermeneutic gap„ between the capabilities of artificial intelligence and the human mind appears - whether a person will be able to use the results of the work of artificial intelligence and understand them. Here we can fix „understanding„ in the hermeneutic sense, as one of the fundamental properties of human existence, which makes it possible to build the vital world of a person full of meanings. Whether a person will be able to understand artificial intelligence and vice versa - whether artificial intelligence can „understand„ a person, become an organic part of the living space and diverse human practices is an urgent issue that requires rethinking within the framework of philosophy. A philosophical analysis of this problem should include a deep understanding of the connection between the life world and the body, practices, mental mechanisms (including unconscious aspects) of a person in the universe of the technological future.
{"title":"Machine Learning and the Problem of the Hermeneutic Gap","authors":"Y. Shaev","doi":"10.1109/INFOCT.2019.8711093","DOIUrl":"https://doi.org/10.1109/INFOCT.2019.8711093","url":null,"abstract":"Rapid development of information technologies has been distinguished in recent years. Neural network technologies, which are using artificial intelligence algorithms, are becoming widespread. In accordance with the nearest futurological predictions, the state of technological singularity is approaching - the unity of man and technologies. In the framework of the approach towards technological singularity, a person tries to understand technologies and to consider them as something human-like, correlated with physicality, participation in everyday practices, and solving a wide variety of tasks. According to experts, artificial intelligence may be developed to such level that it will be harder for the human mind to „understand„ it in the nearest future. Even now, a computer is capable to solve very complicated intellectual problems, many of which previously were considered the sphere of action of the human mind. The problem of a possible „hermeneutic gap„ between the capabilities of artificial intelligence and the human mind appears - whether a person will be able to use the results of the work of artificial intelligence and understand them. Here we can fix „understanding„ in the hermeneutic sense, as one of the fundamental properties of human existence, which makes it possible to build the vital world of a person full of meanings. Whether a person will be able to understand artificial intelligence and vice versa - whether artificial intelligence can „understand„ a person, become an organic part of the living space and diverse human practices is an urgent issue that requires rethinking within the framework of philosophy. A philosophical analysis of this problem should include a deep understanding of the connection between the life world and the body, practices, mental mechanisms (including unconscious aspects) of a person in the universe of the technological future.","PeriodicalId":369231,"journal":{"name":"2019 IEEE 2nd International Conference on Information and Computer Technologies (ICICT)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116402520","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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