Pub Date : 2020-11-18DOI: 10.1109/ICIIBMS50712.2020.9336199
E. Postnikov, M. Dogonadze, A. Lavrova
We present a toolbox for automatized processing files, which contain output data on mycobacterial growth from BACTEC MGIT 960 system, and mathematical models addressed to peculiarities in the growth dynamics revealed from high-resolution records. The data processing includes reading a standardised spreadsheet, its formatting into datasets with respect to the hours of recording and BACTEC intensity units prepared for the subsequent analysis. The case studies reveal the combination of a general trend satisfying the Gompertz growth curve and a series of repeating growth shapes hypothesised as an exhibition of bacterial synchronization phenomena.
{"title":"A MATLAB/OCTAVE toolbox for analysis of BACTEC MGIT 960 data for mycobacterial growth","authors":"E. Postnikov, M. Dogonadze, A. Lavrova","doi":"10.1109/ICIIBMS50712.2020.9336199","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336199","url":null,"abstract":"We present a toolbox for automatized processing files, which contain output data on mycobacterial growth from BACTEC MGIT 960 system, and mathematical models addressed to peculiarities in the growth dynamics revealed from high-resolution records. The data processing includes reading a standardised spreadsheet, its formatting into datasets with respect to the hours of recording and BACTEC intensity units prepared for the subsequent analysis. The case studies reveal the combination of a general trend satisfying the Gompertz growth curve and a series of repeating growth shapes hypothesised as an exhibition of bacterial synchronization phenomena.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"326 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123578948","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 : 2020-11-18DOI: 10.1109/ICIIBMS50712.2020.9336207
Rafael H. A. de Castro, M. Peña-Sarmiento, Ervyn Norza, Camilo A. Sanchez, Erick Gillen, Yeizon A. Duarte, Luis O. Jimenez
The purpose of this document is to assess Electroencephalographic (EEG) signal frequency dynamics in visual stimuli related to crime deterrence from an inexpensive device. The signals were acquired from 4 participants, with an EMOTIV EPOC 14 channel EEG device, while visual stimuli (deterrence and neutral) were presented, also an eye-tracking device was used to follow the participants visual path through the images, the experimental design was developed in the Paradigm software and the signal processing in Python using MNE for the EEG data analysis. Methods: The signal pass by a preprocessing which includes filtering, denoising and ICA object rejection, then the Global Field Power (GFP) is calculated to track the temporal dynamics of frequency bands theta, alpha, beta and gamma, finally differential GFP for theta and alpha bands is calculated and maximal temporal frequency responses are represented. The process applied shows dynamic characteristics of frequency bands and allows maximal localization of its responses.
本文件的目的是评估脑电图(EEG)信号频率动态在视觉刺激相关的犯罪威慑从一个廉价的设备。实验采用EMOTIV EPOC 14通道脑电仪采集4名被试的脑电信号，同时提供视觉刺激(威慑和中性)，并使用眼动仪跟踪被试在图像中的视觉路径，实验设计采用Paradigm软件开发，信号处理采用Python语言，使用MNE进行脑电数据分析。方法:对信号进行滤波、去噪和ICA目标抑制等预处理，然后计算全局场强(Global Field Power, GFP)来跟踪theta、alpha、beta和gamma频段的时间动态，最后计算theta和alpha频段的差分GFP，并表示最大时间频率响应。所应用的过程显示了频段的动态特性，并允许最大限度地定位其响应。
{"title":"Assessing of frequency dynamics of EEG signals in a visualization experiment related to crime deterrence","authors":"Rafael H. A. de Castro, M. Peña-Sarmiento, Ervyn Norza, Camilo A. Sanchez, Erick Gillen, Yeizon A. Duarte, Luis O. Jimenez","doi":"10.1109/ICIIBMS50712.2020.9336207","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336207","url":null,"abstract":"The purpose of this document is to assess Electroencephalographic (EEG) signal frequency dynamics in visual stimuli related to crime deterrence from an inexpensive device. The signals were acquired from 4 participants, with an EMOTIV EPOC 14 channel EEG device, while visual stimuli (deterrence and neutral) were presented, also an eye-tracking device was used to follow the participants visual path through the images, the experimental design was developed in the Paradigm software and the signal processing in Python using MNE for the EEG data analysis. Methods: The signal pass by a preprocessing which includes filtering, denoising and ICA object rejection, then the Global Field Power (GFP) is calculated to track the temporal dynamics of frequency bands theta, alpha, beta and gamma, finally differential GFP for theta and alpha bands is calculated and maximal temporal frequency responses are represented. The process applied shows dynamic characteristics of frequency bands and allows maximal localization of its responses.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121988870","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 : 2020-11-18DOI: 10.1109/iciibms50712.2020.9336422
Zacharie Mbaitiga, Tanaka Shosaku
This paper proposes a practical, robust and efficient new search and detection scheme to quickly detect and locate any person stuck in their home or underground during any disaster and facilitate the rescue team task and consequently save lives The most important thing a bout this new approach is that the person waiting for the rescue team posts outdoor a rescue sign that they can make with any items they can find around them and should not be coincided with any familiar existing sign. Two detection mehodlogy is use. (1) create a maximum color database with value normalization regonition. (2) pattern recognition will be sue for the sign detection, then evaluation
{"title":"Assessment of Disaster Rescue Sign Detection based Image Processing","authors":"Zacharie Mbaitiga, Tanaka Shosaku","doi":"10.1109/iciibms50712.2020.9336422","DOIUrl":"https://doi.org/10.1109/iciibms50712.2020.9336422","url":null,"abstract":"This paper proposes a practical, robust and efficient new search and detection scheme to quickly detect and locate any person stuck in their home or underground during any disaster and facilitate the rescue team task and consequently save lives The most important thing a bout this new approach is that the person waiting for the rescue team posts outdoor a rescue sign that they can make with any items they can find around them and should not be coincided with any familiar existing sign. Two detection mehodlogy is use. (1) create a maximum color database with value normalization regonition. (2) pattern recognition will be sue for the sign detection, then evaluation","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130537420","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 : 2020-11-18DOI: 10.1109/ICIIBMS50712.2020.9336400
Miao Zhang, Y. Wan-jun, Huai-Lin Zhao, Yu Tian, Jun-Yi Tang, M. Zhang
In order to study the effect of panic group behavior on the efficiency of crowd evacuation in emergencies, a crowd emergency evacuation model was constructed based on the theory of big data technology and ant colony algorithm. The panic factor and panic group factor are considered in the model, making the model closer to the actual situation. Based on the complexity of model calculation, the ant colony algorithm is used to solve the model. The research results show that in the emergency evacuation process, attention needs to be paid to the evacuation of key nodes (current restricted areas), and due to the different effects of the panic degree of the evacuated crowd in the evacuation road network on the road sections, attention should be paid to the evacuation process of key road sections to avoid occurrence Crowded stampede and other incidents.
{"title":"Emergency evacuation model of panic group based on Big data","authors":"Miao Zhang, Y. Wan-jun, Huai-Lin Zhao, Yu Tian, Jun-Yi Tang, M. Zhang","doi":"10.1109/ICIIBMS50712.2020.9336400","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336400","url":null,"abstract":"In order to study the effect of panic group behavior on the efficiency of crowd evacuation in emergencies, a crowd emergency evacuation model was constructed based on the theory of big data technology and ant colony algorithm. The panic factor and panic group factor are considered in the model, making the model closer to the actual situation. Based on the complexity of model calculation, the ant colony algorithm is used to solve the model. The research results show that in the emergency evacuation process, attention needs to be paid to the evacuation of key nodes (current restricted areas), and due to the different effects of the panic degree of the evacuated crowd in the evacuation road network on the road sections, attention should be paid to the evacuation process of key road sections to avoid occurrence Crowded stampede and other incidents.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"31 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125702763","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 : 2020-11-18DOI: 10.1109/iciibms50712.2020.9336203
Shinto Takahashi, H. Higa
This paper presents an EMG (electromyogram)-based input interface using machine learning for people with physical disabilities of the extremities. We have developed a virtual hand that can be operated in virtual environment using EMG signals. In this paper, we performed a lifting object task and box and block test task with the virtual hand. From the experimental results of the lifting object tasks, it was confirmed that six wrist joint movements were classified, and that an experimental subject appropriately lifted objects with the virtual hand in the virtual space. In the box and block tests task, it was confirmed that he moved block(s) to the opposite side of the box 9 times within 60 sec.
{"title":"EMG-Based Interface Using Machine Learning","authors":"Shinto Takahashi, H. Higa","doi":"10.1109/iciibms50712.2020.9336203","DOIUrl":"https://doi.org/10.1109/iciibms50712.2020.9336203","url":null,"abstract":"This paper presents an EMG (electromyogram)-based input interface using machine learning for people with physical disabilities of the extremities. We have developed a virtual hand that can be operated in virtual environment using EMG signals. In this paper, we performed a lifting object task and box and block test task with the virtual hand. From the experimental results of the lifting object tasks, it was confirmed that six wrist joint movements were classified, and that an experimental subject appropriately lifted objects with the virtual hand in the virtual space. In the box and block tests task, it was confirmed that he moved block(s) to the opposite side of the box 9 times within 60 sec.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"2006 21","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132678031","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 : 2020-11-18DOI: 10.1109/ICIIBMS50712.2020.9336388
Muhammad Bagus Andra, T. Usagawa
Compared to the more established languages, such as English, Bahasa Indonesia, which is still considered a low-resource language, remains deficient in terms of communication-assisting technology development. This research paper proposes a new method for automatically transcribing simultaneous speech in Bahasa Indonesia. The proposed method could be used as an assistive tool in situations that involve simultaneous speech, such as online discussions and remote conferences. The proposed method uses pitch-aware gain-based speech separation to distinguish the speech between speakers, and a recurrent neural network (RNN) is used to generate a transcription of the speech. This method can detect and transcribe a mixed speech signal of up to three speakers and demonstrates enhanced performance in single-speaker situations compared to the baseline method.
{"title":"Automatic Transcription and Captioning System for Bahasa Indonesia in Multi-Speaker Environment","authors":"Muhammad Bagus Andra, T. Usagawa","doi":"10.1109/ICIIBMS50712.2020.9336388","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336388","url":null,"abstract":"Compared to the more established languages, such as English, Bahasa Indonesia, which is still considered a low-resource language, remains deficient in terms of communication-assisting technology development. This research paper proposes a new method for automatically transcribing simultaneous speech in Bahasa Indonesia. The proposed method could be used as an assistive tool in situations that involve simultaneous speech, such as online discussions and remote conferences. The proposed method uses pitch-aware gain-based speech separation to distinguish the speech between speakers, and a recurrent neural network (RNN) is used to generate a transcription of the speech. This method can detect and transcribe a mixed speech signal of up to three speakers and demonstrates enhanced performance in single-speaker situations compared to the baseline method.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131268545","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 : 2020-11-18DOI: 10.1109/ICIIBMS50712.2020.9336394
Tang Jun-Yi, Zhang Min, Z. Miao, Y. Wan-jun, Tian Yu
Apply artificial intelligence methods to solve underground engineering problems. First, the factors affecting the displacement of the surrounding rock of the mine roadway are analyzed, and the four indexes that affect the displacement of the roadway are used as the input layer of the neural network. Then, the approach rate of the roadway is used as the output layer of the network to construct the neural network prediction model of the roadway surrounding rock displacement. Finally, learn and train the model. The prediction result shows that it has a certain practical value.
{"title":"Applying Neural Network to Predict Roadway Surrounding Rock Displacement","authors":"Tang Jun-Yi, Zhang Min, Z. Miao, Y. Wan-jun, Tian Yu","doi":"10.1109/ICIIBMS50712.2020.9336394","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336394","url":null,"abstract":"Apply artificial intelligence methods to solve underground engineering problems. First, the factors affecting the displacement of the surrounding rock of the mine roadway are analyzed, and the four indexes that affect the displacement of the roadway are used as the input layer of the neural network. Then, the approach rate of the roadway is used as the output layer of the network to construct the neural network prediction model of the roadway surrounding rock displacement. Finally, learn and train the model. The prediction result shows that it has a certain practical value.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116405065","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 : 2020-11-18DOI: 10.1109/ICIIBMS50712.2020.9336419
Qianyu Li, Bei Wang, Jing Jin, Xingyu Wang
Sleep staging is an effective method for diagnosing sleep disorder and monitoring sleep quality. With the rapid development of machine learning technology, the automatic staging methods of sleep gradually replace the traditional manual interpretation which can improve the efficiency on sleep staging for medical research. LSTM networks can save the historical information as a reference for the current moment, which is undoubtedly a good way to improve sleep staging performance. In this paper, a convolutional neural network (CNN) is constructed to extract the features from a single-channel EEG. The Uni-directional Long Short-Term Memory (Uni-LSTM) network and Bi-directional Long Short-Term Memory (Bi-LSTM) network are combined with CNN to realize automatic sleep staging. The obtained results showed that the two presented network frameworks are effective and feasible on sleep staging. The Bi-LSTM which has more enriched sequence information got better classification performance than the Uni-LSTM.
{"title":"Comparison of CNN-Uni-LSTM and CNN-Bi-LSTM based on single-channel EEG for sleep staging","authors":"Qianyu Li, Bei Wang, Jing Jin, Xingyu Wang","doi":"10.1109/ICIIBMS50712.2020.9336419","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336419","url":null,"abstract":"Sleep staging is an effective method for diagnosing sleep disorder and monitoring sleep quality. With the rapid development of machine learning technology, the automatic staging methods of sleep gradually replace the traditional manual interpretation which can improve the efficiency on sleep staging for medical research. LSTM networks can save the historical information as a reference for the current moment, which is undoubtedly a good way to improve sleep staging performance. In this paper, a convolutional neural network (CNN) is constructed to extract the features from a single-channel EEG. The Uni-directional Long Short-Term Memory (Uni-LSTM) network and Bi-directional Long Short-Term Memory (Bi-LSTM) network are combined with CNN to realize automatic sleep staging. The obtained results showed that the two presented network frameworks are effective and feasible on sleep staging. The Bi-LSTM which has more enriched sequence information got better classification performance than the Uni-LSTM.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123064465","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 : 2020-11-18DOI: 10.1109/ICIIBMS50712.2020.9336403
Chin-Yi Cheng, Y. Heryanto, Ryo Yamada
To understand the life cycle, status and mechanisms of cells, the analyses of cell shape, morphology, deformation, features on the cell membrane and movement play very important roles in those studies. With the growth of imaging, scanning, microscopy, and computational technologies, we now can obtain the image data of the cells and then reconstruct the 3D mesh models of the cells in quicker and more convenient ways. However, due to some limitations, the high-resolution cell image cannot be obtained and it will cause the low-resolution of the 3D cell mesh model after the 3D mesh model reconstruction. On the other hand, too much high resolution of the cell image will turn out to be largely time-consuming when analyzing the membrane or morphology of the cells. To study the changes of cell membrane or morphology like protrusions in the different time points, the vertex and face numbers consistency of the 3D cell mesh models will greatly help to reduce the efforts of data preprocessing. In this study, we proposed the method that applied spherical harmonic, a widely applied method to cell morphology study, to increase and decrease the resolution of cell mesh model from the low- or high-resolution cell images, and reconstruct the 3D cell mesh models with the consistence numbers of vertex and face.
{"title":"The spherical harmonic based resolution increase and decrease method for cell mesh model with the vertex and face numbers consistency","authors":"Chin-Yi Cheng, Y. Heryanto, Ryo Yamada","doi":"10.1109/ICIIBMS50712.2020.9336403","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336403","url":null,"abstract":"To understand the life cycle, status and mechanisms of cells, the analyses of cell shape, morphology, deformation, features on the cell membrane and movement play very important roles in those studies. With the growth of imaging, scanning, microscopy, and computational technologies, we now can obtain the image data of the cells and then reconstruct the 3D mesh models of the cells in quicker and more convenient ways. However, due to some limitations, the high-resolution cell image cannot be obtained and it will cause the low-resolution of the 3D cell mesh model after the 3D mesh model reconstruction. On the other hand, too much high resolution of the cell image will turn out to be largely time-consuming when analyzing the membrane or morphology of the cells. To study the changes of cell membrane or morphology like protrusions in the different time points, the vertex and face numbers consistency of the 3D cell mesh models will greatly help to reduce the efforts of data preprocessing. In this study, we proposed the method that applied spherical harmonic, a widely applied method to cell morphology study, to increase and decrease the resolution of cell mesh model from the low- or high-resolution cell images, and reconstruct the 3D cell mesh models with the consistence numbers of vertex and face.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122700036","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 : 2020-11-18DOI: 10.1109/ICIIBMS50712.2020.9336401
Y. Liu, Qi Xu, Chunya Wang
with the rapid development of big data technology, text classification plays an important role in practical application, its applications span a wide range of activities such as sentiment analysis, spam detection, etc. Traditionally, we model the relationship between document and label. However, in many scenarios, document have specific relationship with corresponding title. Inspired by this, a text classification model based on title Semantic Information is proposed in this study. In our model, long short-term memory(LSTM)is used to learn title embedding, document embedding is obtained by using promoted LSTM(TS-LSTM) which take into account the title information. The experimental results on the standard text classification datasets show that its performance is better than the existing state-of-the-art text classification algorithms.
{"title":"Text Classification Based on Title Semantic Information","authors":"Y. Liu, Qi Xu, Chunya Wang","doi":"10.1109/ICIIBMS50712.2020.9336401","DOIUrl":"https://doi.org/10.1109/ICIIBMS50712.2020.9336401","url":null,"abstract":"with the rapid development of big data technology, text classification plays an important role in practical application, its applications span a wide range of activities such as sentiment analysis, spam detection, etc. Traditionally, we model the relationship between document and label. However, in many scenarios, document have specific relationship with corresponding title. Inspired by this, a text classification model based on title Semantic Information is proposed in this study. In our model, long short-term memory(LSTM)is used to learn title embedding, document embedding is obtained by using promoted LSTM(TS-LSTM) which take into account the title information. The experimental results on the standard text classification datasets show that its performance is better than the existing state-of-the-art text classification algorithms.","PeriodicalId":243033,"journal":{"name":"2020 5th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121777140","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：