Pub Date : 2019-09-01DOI: 10.1109/ICCT46177.2019.8969070
Aditya Yadav, Ishan Garg, Dr. Pratistha Mathur
Programmers face situations where they have to rely on messy documentation, other developers and online search for basic programming commands and queries when they encounter any new programming environment. This leads to the waste of time of developers and decreases productivity. In this paper, we present, “PACT”, a chat bot which assists the programmers with basic programming queries that they face when they are new to a programming environment. We use Neural Machine Translation architecture to generate coherent, non-rule based responses to a programmer’s query. The data that is fed to the neural machine translation model is collected from websites like StackOverflow, technical sub-reddits and technical StackExchanges.
{"title":"PACT - Programming Assistant ChaTbot","authors":"Aditya Yadav, Ishan Garg, Dr. Pratistha Mathur","doi":"10.1109/ICCT46177.2019.8969070","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969070","url":null,"abstract":"Programmers face situations where they have to rely on messy documentation, other developers and online search for basic programming commands and queries when they encounter any new programming environment. This leads to the waste of time of developers and decreases productivity. In this paper, we present, “PACT”, a chat bot which assists the programmers with basic programming queries that they face when they are new to a programming environment. We use Neural Machine Translation architecture to generate coherent, non-rule based responses to a programmer’s query. The data that is fed to the neural machine translation model is collected from websites like StackOverflow, technical sub-reddits and technical StackExchanges.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121129549","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8969071
J. Pavanija, G. Jyothi, B. Dhanraj, G. Kumar, A. Bose, Pratibha Verma
In this paper, an effort to reduce the position error obtained from GNSS receivers-using Iterative Least Square Method (ILSM) and Particle Swarm Optimization (PSO) based algorithms for IRNSS and GPS constellation is presented. RINEX data from GNSS receiver is used as input for algorithms presented in the work. First satellite selection algorithm to obtain best GDOP is implemented to select best satellite set to prevent unnecessary navigational signals reception from multiple satellite constellations. Then ILSM and PSO algorithms are applied individually to the receiver coordinates obtained. Results are compared those show that PSO algorithm has better efficiency than iterative algorithm to minimize the position error solution in terms of precision. GNSS receiver coordinates within ± 10m error range is obtained,
{"title":"Reduction of Position Error in GNSS receiver Coordinates using Iterative and PSO based Algorithms","authors":"J. Pavanija, G. Jyothi, B. Dhanraj, G. Kumar, A. Bose, Pratibha Verma","doi":"10.1109/ICCT46177.2019.8969071","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969071","url":null,"abstract":"In this paper, an effort to reduce the position error obtained from GNSS receivers-using Iterative Least Square Method (ILSM) and Particle Swarm Optimization (PSO) based algorithms for IRNSS and GPS constellation is presented. RINEX data from GNSS receiver is used as input for algorithms presented in the work. First satellite selection algorithm to obtain best GDOP is implemented to select best satellite set to prevent unnecessary navigational signals reception from multiple satellite constellations. Then ILSM and PSO algorithms are applied individually to the receiver coordinates obtained. Results are compared those show that PSO algorithm has better efficiency than iterative algorithm to minimize the position error solution in terms of precision. GNSS receiver coordinates within ± 10m error range is obtained,","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121139717","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 : 2019-09-01DOI: 10.1109/icct46177.2019.8969056
{"title":"ICCT 2019 Keynote Speakers","authors":"","doi":"10.1109/icct46177.2019.8969056","DOIUrl":"https://doi.org/10.1109/icct46177.2019.8969056","url":null,"abstract":"","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121259065","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8969068
Crystal Dias, Astha Jagetiya, Sandeep Chaurasia
Automatic license plate recognition is being widely used for numerous applications since its inception. The ability to procure license plate numbers accurately has been beneficial in maintaining traffic rules, parking enforcement, and security. In this paper, we have discussed the results of using ALPR for recognition of anonymous vehicles entering our university campus. We used deep learning for license plate localization and Tesseract OCR for license plate recognition. By doing so we could read the license plates of vehicles entering a particular campus and verify if the vehicle is authorized by comparing it with a predefined list of authorized vehicles. To efficiently extract these number plates we have trained our model using Faster RCNN and tuned it to get the best output. The results of which have been discussed in this paper. Further, the image processing techniques used for preprocessing the identified number plate have been mentioned here. For character segmentation and character recognition, we have used tesseract. While training our model for number plate extraction the minimum loss obtained was 0.011 with RMSprop optimizer at initial learning rate 0.002.
{"title":"Anonymous Vehicle Detection for Secure Campuses: A Framework for License Plate Recognition using Deep Learning","authors":"Crystal Dias, Astha Jagetiya, Sandeep Chaurasia","doi":"10.1109/ICCT46177.2019.8969068","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969068","url":null,"abstract":"Automatic license plate recognition is being widely used for numerous applications since its inception. The ability to procure license plate numbers accurately has been beneficial in maintaining traffic rules, parking enforcement, and security. In this paper, we have discussed the results of using ALPR for recognition of anonymous vehicles entering our university campus. We used deep learning for license plate localization and Tesseract OCR for license plate recognition. By doing so we could read the license plates of vehicles entering a particular campus and verify if the vehicle is authorized by comparing it with a predefined list of authorized vehicles. To efficiently extract these number plates we have trained our model using Faster RCNN and tuned it to get the best output. The results of which have been discussed in this paper. Further, the image processing techniques used for preprocessing the identified number plate have been mentioned here. For character segmentation and character recognition, we have used tesseract. While training our model for number plate extraction the minimum loss obtained was 0.011 with RMSprop optimizer at initial learning rate 0.002.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125086911","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8969046
Satabdi Nayak, San Kumar, Mahesh Jangid
With about 200 million global instances and over 400,000 fatalities a year, malaria continues an enormous strain on global health. Modern information technology plays a major part in many attempts to combat the disease, along with biomedical research and political efforts. In specific, insufficient malaria diagnosis was one of the obstacles to a promising mortality decrease. The paper offers an outline of these methods and explores present advancement in the field of microscopic malaria detection and we have ventured into utilization of deep learning for detection of Malaria Parasite. Deep Learning over the years has proven to be much faster and much more accurate as it automates feature extraction of the dataset. In this research paper, we investigated various models of Deep Learning and monitored which of these models provided a better accuracy and faster resolution than previously used deep learning models. Our results show that Resnet 50 model gave the highest accuracy of 0.975504.
{"title":"Malaria Detection Using Multiple Deep Learning Approaches","authors":"Satabdi Nayak, San Kumar, Mahesh Jangid","doi":"10.1109/ICCT46177.2019.8969046","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969046","url":null,"abstract":"With about 200 million global instances and over 400,000 fatalities a year, malaria continues an enormous strain on global health. Modern information technology plays a major part in many attempts to combat the disease, along with biomedical research and political efforts. In specific, insufficient malaria diagnosis was one of the obstacles to a promising mortality decrease. The paper offers an outline of these methods and explores present advancement in the field of microscopic malaria detection and we have ventured into utilization of deep learning for detection of Malaria Parasite. Deep Learning over the years has proven to be much faster and much more accurate as it automates feature extraction of the dataset. In this research paper, we investigated various models of Deep Learning and monitored which of these models provided a better accuracy and faster resolution than previously used deep learning models. Our results show that Resnet 50 model gave the highest accuracy of 0.975504.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133009308","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8968781
S. Padhi, Suvendu Rup, Sanjay Saxena, Figlu Mohanty
Being the prime reason, after skin cancer, of high mortality rate among women in present day, breast cancer requires correct diagnosis and precise treatment at its earliest stage. From the time of the advent of diagnosis tools, medical practitioners have left no stone unturned in their efforts of delivering timely medication to the patients; but often human error has resulted in either death due to dosage of medicines resulting from wrongly detected malignancies or due to negligence arising from not detecting the tumors at the right time. Hence, computer-aided diagnosis (CADx) has come into light as a key tool in statistically analyzing medical images obtained from various imaging machines and classifying the specimens into the categories of normal, benign, and malignant. A major step involved in it is the segmentation of the medical image into various regions and determining the required region-of-interest (ROI) from them. Automated image segmentation is quintessential today in order to extract the correct suspicious regions for diagnosis, instead of relying on erroneous human eye judgment. The following study aims to compare and analyze the effectiveness of some existing segmentation methods used to extract the ROIs for analysis of digital mammograms for breast cancer detection.
{"title":"Mammogram Segmentation Methods: A Brief Review","authors":"S. Padhi, Suvendu Rup, Sanjay Saxena, Figlu Mohanty","doi":"10.1109/ICCT46177.2019.8968781","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8968781","url":null,"abstract":"Being the prime reason, after skin cancer, of high mortality rate among women in present day, breast cancer requires correct diagnosis and precise treatment at its earliest stage. From the time of the advent of diagnosis tools, medical practitioners have left no stone unturned in their efforts of delivering timely medication to the patients; but often human error has resulted in either death due to dosage of medicines resulting from wrongly detected malignancies or due to negligence arising from not detecting the tumors at the right time. Hence, computer-aided diagnosis (CADx) has come into light as a key tool in statistically analyzing medical images obtained from various imaging machines and classifying the specimens into the categories of normal, benign, and malignant. A major step involved in it is the segmentation of the medical image into various regions and determining the required region-of-interest (ROI) from them. Automated image segmentation is quintessential today in order to extract the correct suspicious regions for diagnosis, instead of relying on erroneous human eye judgment. The following study aims to compare and analyze the effectiveness of some existing segmentation methods used to extract the ROIs for analysis of digital mammograms for breast cancer detection.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129848801","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8969033
N. Sharma, Kavita, G. Agarwal
Security of a network has got a major importance in a wide range of systems. These days every place is connected to a network or via a network e.g. hospitals, offices, universities, finance sector etc. and almost everyone whether young or old is connected to social networking and community media. Though many systems are there that can secure any network, this attacking phenomenon keeps on increasing day by day. This paper focusses on some fundamentals like what basically a network attack is, how to prevent it, its types, preventive measures and current procedures that are focusing on this paradigm. Basically this paper is an attempt to help people understand the concept of attacks so as to avoid them.
{"title":"Network Attacks and Intrusion Detection System: A Brief","authors":"N. Sharma, Kavita, G. Agarwal","doi":"10.1109/ICCT46177.2019.8969033","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969033","url":null,"abstract":"Security of a network has got a major importance in a wide range of systems. These days every place is connected to a network or via a network e.g. hospitals, offices, universities, finance sector etc. and almost everyone whether young or old is connected to social networking and community media. Though many systems are there that can secure any network, this attacking phenomenon keeps on increasing day by day. This paper focusses on some fundamentals like what basically a network attack is, how to prevent it, its types, preventive measures and current procedures that are focusing on this paradigm. Basically this paper is an attempt to help people understand the concept of attacks so as to avoid them.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133811099","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 : 2019-09-01DOI: 10.1109/ICCT46177.2019.8969008
Mahesh Kumar Tripathi, H. Govil, P. Diwan
The larger synoptic view and contiguous channels arrangement of Hyperion hyperspectral remote sensing data enhance the minor spectral identification of earth’s features such as minerals, atmospheric gasses, vegetation and so on. Hydrothermal alteration minerals mostly associated with vicinity of geological structural features such as lineaments and fractures. In this study Hyperion data is used for identification of hydrothermally altered minerals and alteration facies near Chhabadiya village of Jahajpur area, Bhilwara, Rajasthan. There are some minerals such as talc minerals identified through Hyperion imagery. The identified talc minerals correlated and evaluated through petrographic analysis, XRD analysis and spectroscopic analysis. The validation of identified minerals completed by field survey, field sample spectra and USGS spectral library talc mineral spectra. The conclusion is that Hyperion hyperspectral remote sensing data have capability to identify the minerals, mineral assemblage, alteration minerals and alteration facies.
{"title":"Petrography, XRD Analysis and Identification of Talc Minerals near Chhabadiya Village of Jahajpur Region, Bhilwara, India through Hyperion Hyperspectral Remote Sensing Data","authors":"Mahesh Kumar Tripathi, H. Govil, P. Diwan","doi":"10.1109/ICCT46177.2019.8969008","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969008","url":null,"abstract":"The larger synoptic view and contiguous channels arrangement of Hyperion hyperspectral remote sensing data enhance the minor spectral identification of earth’s features such as minerals, atmospheric gasses, vegetation and so on. Hydrothermal alteration minerals mostly associated with vicinity of geological structural features such as lineaments and fractures. In this study Hyperion data is used for identification of hydrothermally altered minerals and alteration facies near Chhabadiya village of Jahajpur area, Bhilwara, Rajasthan. There are some minerals such as talc minerals identified through Hyperion imagery. The identified talc minerals correlated and evaluated through petrographic analysis, XRD analysis and spectroscopic analysis. The validation of identified minerals completed by field survey, field sample spectra and USGS spectral library talc mineral spectra. The conclusion is that Hyperion hyperspectral remote sensing data have capability to identify the minerals, mineral assemblage, alteration minerals and alteration facies.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127837029","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}
We are well aware of the many problems that our current generations are facing. From all these new enhancements in the real world it has been quite hard for them to keep up with everything evolving around them. Keeping all this in mind they work day in and out to make sure that their knowledge on their surroundings up to date, however we believe that they fail to properly take care of themselves in the process. No matter how much a certain individual may withstand in terms of workload, stress, or other mental & emotional barriers our physical body will always be the key aspect to overcoming them. Most people believe that working out and maintaining physical fitness are the major aspects to sustain a healthy physical form but they simply overlook the most important aspect which are their eating habits. Although our body may be physically fit, the nourishment of our body depends on the eating styles that we follow on a day to day basis. Food is what nourishes our body with most of the proteins & minerals that we require, without it we wouldn't be able to accomplish much. On conducting a worldwide research on people's lifestyles we were able to conclude that over the past 33 years the obesity rate among human beings has increased by a mere 27.5%. What seems to be the most thoughtful yet intriguing fact is that although many people are overweight as well as obese they still believe that their eating habits are healthy. Most people are living in the dilemma of the fact that they maintain a healthy lifestyle. We aim to study the views on a healthy lifestyle as per the norms of our current generation. We would like to analyse their daily eating habits as well as their own thoughts on their lifestyle. So the question that remains is… “What exactly is a Healthy Eating Lifestyle?”
{"title":"Food Survey using Exploratory Data Analysis","authors":"Rayapati RamyaSri, Shaik IshaSanjida, Dhanush Parasa, Shahana Bano","doi":"10.1109/ICCT46177.2019.8969016","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969016","url":null,"abstract":"We are well aware of the many problems that our current generations are facing. From all these new enhancements in the real world it has been quite hard for them to keep up with everything evolving around them. Keeping all this in mind they work day in and out to make sure that their knowledge on their surroundings up to date, however we believe that they fail to properly take care of themselves in the process. No matter how much a certain individual may withstand in terms of workload, stress, or other mental & emotional barriers our physical body will always be the key aspect to overcoming them. Most people believe that working out and maintaining physical fitness are the major aspects to sustain a healthy physical form but they simply overlook the most important aspect which are their eating habits. Although our body may be physically fit, the nourishment of our body depends on the eating styles that we follow on a day to day basis. Food is what nourishes our body with most of the proteins & minerals that we require, without it we wouldn't be able to accomplish much. On conducting a worldwide research on people's lifestyles we were able to conclude that over the past 33 years the obesity rate among human beings has increased by a mere 27.5%. What seems to be the most thoughtful yet intriguing fact is that although many people are overweight as well as obese they still believe that their eating habits are healthy. Most people are living in the dilemma of the fact that they maintain a healthy lifestyle. We aim to study the views on a healthy lifestyle as per the norms of our current generation. We would like to analyse their daily eating habits as well as their own thoughts on their lifestyle. So the question that remains is… “What exactly is a Healthy Eating Lifestyle?”","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114583830","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}
Sentiment analysis of social media data consists of attitudes, assessments, and emotions which can be considered a way human think. Understanding and classifying the large collection of documents into positive and negative aspects are a very difficult task. Social networks such as Twitter, Facebook, and Instagram provide a platform in order to gather information about people’s sentiments and opinions. Considering the fact that people spend hours daily on social media and share their opinion on various different topics helps us analyze sentiments better. More and more companies are using social media tools to provide various services and interact with customers. Sentiment Analysis (SA) classifies the polarity of given tweets to positive and negative tweets in order to understand the sentiments of the public. This paper aims to perform sentiment analysis of real-time 2019 election twitter data using the feature selection model word2vec and the machine learning algorithm random forest for sentiment classification. Word2vec with Random Forest improves the accuracy of sentiment analysis significantly compared to traditional methods such as BOW and TF-IDF. Word2vec improves the quality of features by considering contextual semantics of words in a text hence improving the accuracy of machine learning and sentiment analysis.
{"title":"Real-Time Sentiment Analysis of 2019 Election Tweets using Word2vec and Random Forest Model","authors":"Msr Hitesh, Vedhosi Vaibhav, Y.J Abhishek Kalki, Suraj Harsha Kamtam, S. Kumari","doi":"10.1109/ICCT46177.2019.8969049","DOIUrl":"https://doi.org/10.1109/ICCT46177.2019.8969049","url":null,"abstract":"Sentiment analysis of social media data consists of attitudes, assessments, and emotions which can be considered a way human think. Understanding and classifying the large collection of documents into positive and negative aspects are a very difficult task. Social networks such as Twitter, Facebook, and Instagram provide a platform in order to gather information about people’s sentiments and opinions. Considering the fact that people spend hours daily on social media and share their opinion on various different topics helps us analyze sentiments better. More and more companies are using social media tools to provide various services and interact with customers. Sentiment Analysis (SA) classifies the polarity of given tweets to positive and negative tweets in order to understand the sentiments of the public. This paper aims to perform sentiment analysis of real-time 2019 election twitter data using the feature selection model word2vec and the machine learning algorithm random forest for sentiment classification. Word2vec with Random Forest improves the accuracy of sentiment analysis significantly compared to traditional methods such as BOW and TF-IDF. Word2vec improves the quality of features by considering contextual semantics of words in a text hence improving the accuracy of machine learning and sentiment analysis.","PeriodicalId":118655,"journal":{"name":"2019 2nd International Conference on Intelligent Communication and Computational Techniques (ICCT)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128773100","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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