Identifying the vehicle in front of road is an important research topic for active safety and intelligent driving of vehicles. A vehicle identification algorithm is proposed based on computer vision using supervised machine learning algorithm AdaBoost and Haar-like features. Firstly, in terms of feature selection, dimension reduction processing is performed from two aspects of feature type and feature size, and integral graph is applied to accelerate the calculation of Haar-like eigenvalues. Secondly, a more efficient classifier is constructed based on a small number of effective features, and a single strong classifier is used to identify and verify the vehicle in front. Finally, the whole vehicle identification algorithm is tested with the test data including 350 frames captured from the highway video set and 450 frames captured from the urban road video set. The result shows that the vehicle identification algorithm have a high detection rate and Lower detection error rate.
{"title":"Research on Vehicle Identification Method Based on Computer Vision","authors":"Zhou Yan, Deming Yuan, Zhou Jun","doi":"10.1145/3335656.3335700","DOIUrl":"https://doi.org/10.1145/3335656.3335700","url":null,"abstract":"Identifying the vehicle in front of road is an important research topic for active safety and intelligent driving of vehicles. A vehicle identification algorithm is proposed based on computer vision using supervised machine learning algorithm AdaBoost and Haar-like features. Firstly, in terms of feature selection, dimension reduction processing is performed from two aspects of feature type and feature size, and integral graph is applied to accelerate the calculation of Haar-like eigenvalues. Secondly, a more efficient classifier is constructed based on a small number of effective features, and a single strong classifier is used to identify and verify the vehicle in front. Finally, the whole vehicle identification algorithm is tested with the test data including 350 frames captured from the highway video set and 450 frames captured from the urban road video set. The result shows that the vehicle identification algorithm have a high detection rate and Lower detection error rate.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115182338","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}
Public bicycles are a healthy and environmentally friendly means of transportation that facilitates people's travel. However, due to the uncertainty of urban travel, especially the tidal phenomenon, public bicycles often "difficult to borrow a car" and "return the car". This will result in unreasonable distribution of the site during the operation of the public bicycle system, unbalanced bicycle processes at various sites during peak hours, and unbalanced operation and management, which restricts the development of public bicycles. This paper uses the data of the San Francisco Bay Area as the experimental data of this paper, using Spark SQL and Spark Dataframe to analyze the use of public bicycle users and sites, according to the impact of different user types on the use of public bicycles, using K-means clustering algorithm Analyze the use of the site. Based on the Spark MLlib machine learning library, the gradient usage algorithm is used to predict daily usage.
{"title":"Analysis and Research on the Use Situation of Public Bicycles Based on Spark Machine Learning","authors":"Chengang Li, Yu Liu, Chengcheng Li","doi":"10.1145/3335656.3335704","DOIUrl":"https://doi.org/10.1145/3335656.3335704","url":null,"abstract":"Public bicycles are a healthy and environmentally friendly means of transportation that facilitates people's travel. However, due to the uncertainty of urban travel, especially the tidal phenomenon, public bicycles often \"difficult to borrow a car\" and \"return the car\". This will result in unreasonable distribution of the site during the operation of the public bicycle system, unbalanced bicycle processes at various sites during peak hours, and unbalanced operation and management, which restricts the development of public bicycles. This paper uses the data of the San Francisco Bay Area as the experimental data of this paper, using Spark SQL and Spark Dataframe to analyze the use of public bicycle users and sites, according to the impact of different user types on the use of public bicycles, using K-means clustering algorithm Analyze the use of the site. Based on the Spark MLlib machine learning library, the gradient usage algorithm is used to predict daily usage.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127294637","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}
In order to improve the current air-conditioning APP interface, the function is simple and simple, the operation convenience is insufficient, and the interface is not beautiful. Through the research and analysis of user needs, the primary and secondary requirements are obtained, and the user experience is taken as the main consideration of APP interface design. At the same time, the intelligent and minimalist design principles are integrated into the interface design, and the prototype design of the interface is completed. According to the user's functional experience evaluation of the design prototype, perfect the design prototype and product development design, and finally test the product satisfaction. Overall user satisfaction increased from 72% to 81%. Conclusion The intelligent air conditioner APP basically meets the design requirements, especially the monitoring of energy consumption.
{"title":"Research on Interface Design of Air Conditioning Intelligent APP Based on User Experience","authors":"Ruifang Zhang, Yangxue Liu","doi":"10.1145/3335656.3335685","DOIUrl":"https://doi.org/10.1145/3335656.3335685","url":null,"abstract":"In order to improve the current air-conditioning APP interface, the function is simple and simple, the operation convenience is insufficient, and the interface is not beautiful. Through the research and analysis of user needs, the primary and secondary requirements are obtained, and the user experience is taken as the main consideration of APP interface design. At the same time, the intelligent and minimalist design principles are integrated into the interface design, and the prototype design of the interface is completed. According to the user's functional experience evaluation of the design prototype, perfect the design prototype and product development design, and finally test the product satisfaction. Overall user satisfaction increased from 72% to 81%. Conclusion The intelligent air conditioner APP basically meets the design requirements, especially the monitoring of energy consumption.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"13 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129772661","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}
In order to promote the integration of automobile network and Internet, Internet of Vehicles gateway plays an important role in connecting vehicle-borne network and Internet. In view of the current developers using traditional development methods to achieve Internet of Vehicles gateway software, a new implementation scheme -- real-time Java technology is introduced. This paper takes the AMD Opteron 1150 processor based on the ARM Cortex-A57 architecture as the core to build the hardware platform of the Internet of Vehicles gateway, and gives the overall structure diagram and hardware connection scheme of the Internet of Vehicles system. The gateway adopts the networking scheme of "4G+ sensor network technology/field bus" and realizes wireless data interaction on the basis of real-time operating system. In addition, the data communication of Internet of Vehicles (three-layer communication structure) is realized on the WebSphere Real Time development platform that is fully compatible with RTSJ, so as to realize data sharing between the automobile bus network and the Internet. Finally, the implementation technology and system verification of the design are given.
为了促进车联网与互联网的融合，车联网网关在连接车联网与互联网方面发挥着重要作用。针对目前开发人员采用传统开发方法实现车联网网关软件的现状，介绍了一种新的实现方案——实时Java技术。本文以基于ARM Cortex-A57架构的AMD Opteron 1150处理器为核心构建了车联网网关的硬件平台，并给出了车联网系统的总体结构图和硬件连接方案。网关采用“4G+传感器网络技术/现场总线”的组网方案，在实时操作系统的基础上实现无线数据交互。此外，车联网的数据通信(三层通信结构)在完全兼容RTSJ的WebSphere Real Time开发平台上实现，从而实现汽车总线网络与互联网之间的数据共享。最后给出了设计的实现技术和系统验证。
{"title":"Research on Internet of Vehicles Gateway based on RTSJ","authors":"Teng Haikun, Liu Xinsheng, Li Lunbin","doi":"10.1145/3335656.3335705","DOIUrl":"https://doi.org/10.1145/3335656.3335705","url":null,"abstract":"In order to promote the integration of automobile network and Internet, Internet of Vehicles gateway plays an important role in connecting vehicle-borne network and Internet. In view of the current developers using traditional development methods to achieve Internet of Vehicles gateway software, a new implementation scheme -- real-time Java technology is introduced. This paper takes the AMD Opteron 1150 processor based on the ARM Cortex-A57 architecture as the core to build the hardware platform of the Internet of Vehicles gateway, and gives the overall structure diagram and hardware connection scheme of the Internet of Vehicles system. The gateway adopts the networking scheme of \"4G+ sensor network technology/field bus\" and realizes wireless data interaction on the basis of real-time operating system. In addition, the data communication of Internet of Vehicles (three-layer communication structure) is realized on the WebSphere Real Time development platform that is fully compatible with RTSJ, so as to realize data sharing between the automobile bus network and the Internet. Finally, the implementation technology and system verification of the design are given.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121259263","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}
Teng Haikun, W. Shiying, Liu Xinsheng, Xiaodong Yue
In order to improve the performance of the speech recognition and pronunciation quality evaluation system, the deep learning-based computer aided foreign language pronunciation evaluation and learning system has become a research focus of current artificial intelligence technology. Combining with the current advanced voice information technology theory, based on the previous research results, proposed to sparse since the encoder deep learning neural network is applied to speech recognition, using sparse automatic encoder based on MFCC features in-depth study, the imitation of the auditory nerve sparse touches the depth of feature extracting signal, beneficial to the improvement of the HMM model for speech recognition accuracy, meet the needs of the current computer assisted English teaching. The simulation results show that the recognition rate of the deep learning neural network is obviously superior to that of the traditional speech recognition algorithm, which realizes more accurate human-computer interaction and improves the reliability of the evaluation of the quality of foreign language pronunciation.
{"title":"Speech Recognition Model Based on Deep Learning And Application in Pronunciation Quality Evaluation System","authors":"Teng Haikun, W. Shiying, Liu Xinsheng, Xiaodong Yue","doi":"10.1145/3335656.3335657","DOIUrl":"https://doi.org/10.1145/3335656.3335657","url":null,"abstract":"In order to improve the performance of the speech recognition and pronunciation quality evaluation system, the deep learning-based computer aided foreign language pronunciation evaluation and learning system has become a research focus of current artificial intelligence technology. Combining with the current advanced voice information technology theory, based on the previous research results, proposed to sparse since the encoder deep learning neural network is applied to speech recognition, using sparse automatic encoder based on MFCC features in-depth study, the imitation of the auditory nerve sparse touches the depth of feature extracting signal, beneficial to the improvement of the HMM model for speech recognition accuracy, meet the needs of the current computer assisted English teaching. The simulation results show that the recognition rate of the deep learning neural network is obviously superior to that of the traditional speech recognition algorithm, which realizes more accurate human-computer interaction and improves the reliability of the evaluation of the quality of foreign language pronunciation.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132079894","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}
Carl Timothy Tolentino, F. Panganiban, F. D. de Leon
The classical guitar is described as a "miniature orchestra" due to the various tone colors that it can produce. One parameter that can control the timbre on the guitar is the excitation point on the string. In this study, a machine learning model was built to determine the excitation point on the string given an audio signal. It was noted that including the mel-frequency cepstral coefficients in the feature set yields outstanding performance. Furthermore, principal component analysis can be used to reduce the dimensions without sacrificing much on performance. Among three well-known algorithms, it was observed that the multi-layer perceptron yields the best performance in terms of classification and regression. Lastly, the models were trained and tested on different subjects and it was noted that each subject has a unique model of its own since different subjects have different physiological parameters that can affect the produced guitar tone.
{"title":"Machine Learning Methods for Estimating the Excitation Point on a Plucked String of a Classical Guitar","authors":"Carl Timothy Tolentino, F. Panganiban, F. D. de Leon","doi":"10.1145/3335656.3335683","DOIUrl":"https://doi.org/10.1145/3335656.3335683","url":null,"abstract":"The classical guitar is described as a \"miniature orchestra\" due to the various tone colors that it can produce. One parameter that can control the timbre on the guitar is the excitation point on the string. In this study, a machine learning model was built to determine the excitation point on the string given an audio signal. It was noted that including the mel-frequency cepstral coefficients in the feature set yields outstanding performance. Furthermore, principal component analysis can be used to reduce the dimensions without sacrificing much on performance. Among three well-known algorithms, it was observed that the multi-layer perceptron yields the best performance in terms of classification and regression. Lastly, the models were trained and tested on different subjects and it was noted that each subject has a unique model of its own since different subjects have different physiological parameters that can affect the produced guitar tone.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128892860","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}
In order to measure the creepage distance of the post insulator, this paper proposes a method for calculating the length of curve which without equation, and chose two typical photographic equipment like cellphone and camera, to research the experimental results of this method when use different equipment. The first, two equipment are used to take pictures in the same environment, and then preprocess this images to get creepage path of the insulator, finally, the actual creepage distance of the insulator is counted by calculating the length of the path in picture. The experimental results show that the method in this paper is able to calculate the creepage distance, and the error is low, so it can be used in different photographic equipment.
{"title":"Research on Insulator Creepage Distance Measurement Based on Different Photographic Equipment","authors":"Hanmin Ye, Ziyi Zhong, ShiMing Huang","doi":"10.1145/3335656.3335702","DOIUrl":"https://doi.org/10.1145/3335656.3335702","url":null,"abstract":"In order to measure the creepage distance of the post insulator, this paper proposes a method for calculating the length of curve which without equation, and chose two typical photographic equipment like cellphone and camera, to research the experimental results of this method when use different equipment. The first, two equipment are used to take pictures in the same environment, and then preprocess this images to get creepage path of the insulator, finally, the actual creepage distance of the insulator is counted by calculating the length of the path in picture. The experimental results show that the method in this paper is able to calculate the creepage distance, and the error is low, so it can be used in different photographic equipment.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133827697","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}
The big data of tourism has exploded with the rapid development of social media, providing a new data source for the emotion analysis of tourism. Based on online comments, this paper proposes an emotion analysis model that combines tourism domain ontology and semantic-based method to mine the fine-grained emotion of tourists and designs specific formulas to quantify the emotion of tourists. Finally, the Palace Museum is used as an example to verify the validity of the model. The analysis results show that: 1) Tourists pay more attention to the attributes such as "scenery", "tourist flow", "ticket", etc. in their travel activities. 2) The emotional score of the attributes such as "lodging environment", "scenery", "culture", "environment quality", etc. are higher, but the attributes such as "safety", "tourist flow", "toilet" and cost-related attributes are lower. The main reasons are: "low security", "massive tourists", "less and small toilets" and "high costs". 3) Due to the excessive number of tourists during the holiday, which leads poor travel experience to the tourists, the emotional score of tourists are lower in the 5th, 7th, 8th and 10th months. The analysis results can provide reference for tourists' travel decisions and the development and optimization of tourism.
{"title":"Emotion Analysis of Tourists Based on Domain Ontology","authors":"Jiabin Pan, Naixia Mou, Wenbao Liu","doi":"10.1145/3335656.3335701","DOIUrl":"https://doi.org/10.1145/3335656.3335701","url":null,"abstract":"The big data of tourism has exploded with the rapid development of social media, providing a new data source for the emotion analysis of tourism. Based on online comments, this paper proposes an emotion analysis model that combines tourism domain ontology and semantic-based method to mine the fine-grained emotion of tourists and designs specific formulas to quantify the emotion of tourists. Finally, the Palace Museum is used as an example to verify the validity of the model. The analysis results show that: 1) Tourists pay more attention to the attributes such as \"scenery\", \"tourist flow\", \"ticket\", etc. in their travel activities. 2) The emotional score of the attributes such as \"lodging environment\", \"scenery\", \"culture\", \"environment quality\", etc. are higher, but the attributes such as \"safety\", \"tourist flow\", \"toilet\" and cost-related attributes are lower. The main reasons are: \"low security\", \"massive tourists\", \"less and small toilets\" and \"high costs\". 3) Due to the excessive number of tourists during the holiday, which leads poor travel experience to the tourists, the emotional score of tourists are lower in the 5th, 7th, 8th and 10th months. The analysis results can provide reference for tourists' travel decisions and the development and optimization of tourism.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131657755","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}
The development of fire is often unpredictable, and the scale of fire spread is so large that fire rescue is difficult to grasp the whole site. This paper mainly predicts the area of fire spread based on the idea of DBSCAN algorithm, and simulates the spread trend of the disaster, with the image of open source scene. The particle system of OSG (Open Scene Graph) simulates the fire and its situation in three-dimensional scenes. Through the VS2017 and OSG development environment, the algorithm is simulated by the program to verify the practicability of the fire situation in the virtual simulation. This provides a feasible way to establish a realistic prediction of fire spread situation, and implements the fire suppression. The program provides a new reference.
火灾的发展往往是不可预测的，而且火势蔓延的规模如此之大，以至于消防救援很难掌握整个现场。本文主要基于DBSCAN算法的思想对火灾蔓延区域进行预测，并利用开源场景图像对火灾蔓延趋势进行模拟。OSG (Open Scene Graph)的粒子系统在三维场景中模拟火灾及其情况。通过VS2017和OSG开发环境，对该算法进行了程序仿真，验证了该算法在火灾情况虚拟仿真中的实用性。这为建立真实的火灾蔓延情况预测，实现火灾扑灭提供了可行的途径。该方案提供了新的参考。
{"title":"The Simulation and Research of Fire Spread Situation Based on OSG","authors":"X. Xie, Jianwei Wang, Han Qin, Xiaochun Cheng","doi":"10.1145/3335656.3335703","DOIUrl":"https://doi.org/10.1145/3335656.3335703","url":null,"abstract":"The development of fire is often unpredictable, and the scale of fire spread is so large that fire rescue is difficult to grasp the whole site. This paper mainly predicts the area of fire spread based on the idea of DBSCAN algorithm, and simulates the spread trend of the disaster, with the image of open source scene. The particle system of OSG (Open Scene Graph) simulates the fire and its situation in three-dimensional scenes. Through the VS2017 and OSG development environment, the algorithm is simulated by the program to verify the practicability of the fire situation in the virtual simulation. This provides a feasible way to establish a realistic prediction of fire spread situation, and implements the fire suppression. The program provides a new reference.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130499614","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}
In recent years, predicting the popularity of articles in the news has become a more urgent task for authors, online resources and advertisers. In the order of this task, we propose a new method based on the Online Deep Neural network with Bottleneck compression, what predicts the article popularity with only its headline. The proposed methodology evaluated on the Chinese and Russian language-based datasets with over than 800 000 samples in total. We describe the challenges and solutions related to the popularity prediction and the headline analysis. We show that the provided method can reach acceptable results even with different languages, news source popularity dynamics.
{"title":"Forecasting popularity of news article by title analyzing with BN-LSTM network","authors":"Anton Voronov, Yao Shen, Pritom Kumar Mondal","doi":"10.1145/3335656.3335679","DOIUrl":"https://doi.org/10.1145/3335656.3335679","url":null,"abstract":"In recent years, predicting the popularity of articles in the news has become a more urgent task for authors, online resources and advertisers. In the order of this task, we propose a new method based on the Online Deep Neural network with Bottleneck compression, what predicts the article popularity with only its headline. The proposed methodology evaluated on the Chinese and Russian language-based datasets with over than 800 000 samples in total. We describe the challenges and solutions related to the popularity prediction and the headline analysis. We show that the provided method can reach acceptable results even with different languages, news source popularity dynamics.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128984577","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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