Pub Date : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204043
S. Gazzah, O. Bencharef
The coronavirus first outbreak in Wuhan city of China by December 2019. Due to its highly contagious power, they spread promptly in the four continents. Moreover, it devastating our daily lives and cause huge economic damage. Therefore, it is urgent to detect the positive cases at the earliest and put then under isolation. Automatic virus detection using Machine Learning will be a valuable contribution to prevent the spread of this epidemic. The purpose of this paper is to present short reviews on the coronavirus detection. In reviewing the existing works, we summarized and compared some related works performed on a collection of CT and X-ray images provided from infected patients. We conclude the paper with some discussions on how computer vision can response to urgent need to contribute in pandemics and to investigate many aspects of new viral replication and pathogenesis.
{"title":"A Survey on how computer vision can response to urgent need to contribute in COVID-19 pandemics","authors":"S. Gazzah, O. Bencharef","doi":"10.1109/ISCV49265.2020.9204043","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204043","url":null,"abstract":"The coronavirus first outbreak in Wuhan city of China by December 2019. Due to its highly contagious power, they spread promptly in the four continents. Moreover, it devastating our daily lives and cause huge economic damage. Therefore, it is urgent to detect the positive cases at the earliest and put then under isolation. Automatic virus detection using Machine Learning will be a valuable contribution to prevent the spread of this epidemic. The purpose of this paper is to present short reviews on the coronavirus detection. In reviewing the existing works, we summarized and compared some related works performed on a collection of CT and X-ray images provided from infected patients. We conclude the paper with some discussions on how computer vision can response to urgent need to contribute in pandemics and to investigate many aspects of new viral replication and pathogenesis.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114267418","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204214
Hicham Lamtougui, H. E. Moubtahij, Hassan Fouadi, Ali Yahyaouy, K. Satori
By virtue of advances in machine learning, handwriting recognition is considered as one of the main research topics in this field. Many studies have been proposed to improve this recognition of handwritten texts for different languages such as Latin and Chinese. Yet, the processing of Arabic texts remains a particularly distinctive problem due to the complicated nature of the Arabic script compared to other scripts. In this work, we display a study and an evaluation of relevant articles recently published in conferences and indexed journals. The core of the problem is to relatively find out an efficient method capable of recognizing the handwritten text by any user via digital devices. In this article, we study the various works interested in the recognition of handwritten Arabic script implemented by deep learning. We thouroughly discuss different classification approaches like CNN, RNN and DBN. The pros and cons of each approach will be presented, as well as their different results.
{"title":"Offline Arabic Handwriting Recognition Using Deep Learning: Comparative Study","authors":"Hicham Lamtougui, H. E. Moubtahij, Hassan Fouadi, Ali Yahyaouy, K. Satori","doi":"10.1109/ISCV49265.2020.9204214","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204214","url":null,"abstract":"By virtue of advances in machine learning, handwriting recognition is considered as one of the main research topics in this field. Many studies have been proposed to improve this recognition of handwritten texts for different languages such as Latin and Chinese. Yet, the processing of Arabic texts remains a particularly distinctive problem due to the complicated nature of the Arabic script compared to other scripts. In this work, we display a study and an evaluation of relevant articles recently published in conferences and indexed journals. The core of the problem is to relatively find out an efficient method capable of recognizing the handwritten text by any user via digital devices. In this article, we study the various works interested in the recognition of handwritten Arabic script implemented by deep learning. We thouroughly discuss different classification approaches like CNN, RNN and DBN. The pros and cons of each approach will be presented, as well as their different results.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134408853","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204120
H. Benbrahim, A. Merzouki, K. Minaoui
The purpose of this study is to quantify soil moisture variability in agriculture fields at field scale resolution using the Sentinel data (Sentinel-1 and Sentinel-2) based on a change detection technique. For calibration and validation of our model, ground measurements at 40 sampling sites in southern Manitoba, Canada, were carried out during the field campaign of SMAP Validation Experiment 2016 in Manitoba (SMAPVEX16-MB). The developed method is based on modelling soil moisture change by combining the difference in backscattered signal with that of NDVI observed on two consecutive acquisition days. This approach makes the assumption that the change in Normalized Difference Vegetation Index (NDVI) could better represent the attenuation of the backscattered signal resulting from the vegetation. Our model was evaluated over mature crop fields (canola, soybeans, wheat, corn and oats) using ground measurements and the agreement between satellite estimates and ground measurements was found satisfactory (RMSE lower than 0.093 m3/m3).
{"title":"Quantification of soil moisture variability over agriculture fields using Sentinel imagery","authors":"H. Benbrahim, A. Merzouki, K. Minaoui","doi":"10.1109/ISCV49265.2020.9204120","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204120","url":null,"abstract":"The purpose of this study is to quantify soil moisture variability in agriculture fields at field scale resolution using the Sentinel data (Sentinel-1 and Sentinel-2) based on a change detection technique. For calibration and validation of our model, ground measurements at 40 sampling sites in southern Manitoba, Canada, were carried out during the field campaign of SMAP Validation Experiment 2016 in Manitoba (SMAPVEX16-MB). The developed method is based on modelling soil moisture change by combining the difference in backscattered signal with that of NDVI observed on two consecutive acquisition days. This approach makes the assumption that the change in Normalized Difference Vegetation Index (NDVI) could better represent the attenuation of the backscattered signal resulting from the vegetation. Our model was evaluated over mature crop fields (canola, soybeans, wheat, corn and oats) using ground measurements and the agreement between satellite estimates and ground measurements was found satisfactory (RMSE lower than 0.093 m3/m3).","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128328340","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204164
Abderrezzak Sebbah, B. Kadri
the internet of things (IoT) is consisting of many complementary elements which have their own specificities and capacities. These elements are gaining new application and use cases in our lives. Nevertheless, they open a negative horizon of security and privacy issues which must be treated delicately before the deployment of any IoT. Recently, different works emerged dealing with the same branch of issues, like the work of Yuwen Chen et al. that is called LightPriAuth. LightPriAuth has several drawbacks and weakness against various popular attacks such as Insider attack and stolen smart card. Our objective in this paper is to propose a novel solution which is “authentication scheme with three factor using ECC and fuzzy extractor” to ensure security and privacy. The obtained results had proven the superiority of our scheme’s performances compared to that of LightPriAuth which, additionally, had defeated the weaknesses left by LightPriAuth.
{"title":"A Privacy and Authentication Scheme for IoT Environments Using ECC and Fuzzy Extractor","authors":"Abderrezzak Sebbah, B. Kadri","doi":"10.1109/ISCV49265.2020.9204164","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204164","url":null,"abstract":"the internet of things (IoT) is consisting of many complementary elements which have their own specificities and capacities. These elements are gaining new application and use cases in our lives. Nevertheless, they open a negative horizon of security and privacy issues which must be treated delicately before the deployment of any IoT. Recently, different works emerged dealing with the same branch of issues, like the work of Yuwen Chen et al. that is called LightPriAuth. LightPriAuth has several drawbacks and weakness against various popular attacks such as Insider attack and stolen smart card. Our objective in this paper is to propose a novel solution which is “authentication scheme with three factor using ECC and fuzzy extractor” to ensure security and privacy. The obtained results had proven the superiority of our scheme’s performances compared to that of LightPriAuth which, additionally, had defeated the weaknesses left by LightPriAuth.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":"124 25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134522744","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204022
F. Ngom, Ibrahima Fall, M. Camara, A. Bah
Heart disease causes millions of deaths worldwide. Many approaches have been proposed for the prediction of heart disease. Several machine learning, deep learning, and data mining algorithms are used in the detection and diagnosis of heart disease based on parameters or risk factors. The most used algorithms are Naïve Bayes, Machine Vector Support, decision tree, KNNs, and artificial neural networks. The most frequently used parameters or risk factors are the 14 attributes of the UCI Cleveland standard. In this article, a study on these different approaches is carried out. This study shows diversity in relation to the choices and the use of different attributes in the prediction of cardiovascular diseases.
{"title":"A study on predicting and diagnosing non-communicable diseases: case of cardiovascular diseases","authors":"F. Ngom, Ibrahima Fall, M. Camara, A. Bah","doi":"10.1109/ISCV49265.2020.9204022","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204022","url":null,"abstract":"Heart disease causes millions of deaths worldwide. Many approaches have been proposed for the prediction of heart disease. Several machine learning, deep learning, and data mining algorithms are used in the detection and diagnosis of heart disease based on parameters or risk factors. The most used algorithms are Naïve Bayes, Machine Vector Support, decision tree, KNNs, and artificial neural networks. The most frequently used parameters or risk factors are the 14 attributes of the UCI Cleveland standard. In this article, a study on these different approaches is carried out. This study shows diversity in relation to the choices and the use of different attributes in the prediction of cardiovascular diseases.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":"10887 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124491825","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204167
Azdad Nabila, E. Mohamed
In this paper, we consider an IEEE 802.15.4-based Wireless Body Area Network (WBAN), where different biomedical sensors are distributed on a human body and have to send the measured data to a coordinator node. Focusing on the Slotted Carrier Sense Multiple Access with Collision Avoidance algorithm (Slotted CSMA/CA) defined by the IEEE 802.15.4 norm in the beacon-enabled mode, we propose an enhanced backoff strategy to provide nodes an equitable access to the communication medium. Then we analyze its performance over realistic requirements of the considered sensors using the latest version of Castalia Simulator. The obtained results reveal the efficiency of our proposal as compared to the traditional profile of the norm in terms of reliability, timeliness and throughput.
{"title":"An enhanced backoff strategy for fair channel access in WBAN-based health monitoring systems","authors":"Azdad Nabila, E. Mohamed","doi":"10.1109/ISCV49265.2020.9204167","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204167","url":null,"abstract":"In this paper, we consider an IEEE 802.15.4-based Wireless Body Area Network (WBAN), where different biomedical sensors are distributed on a human body and have to send the measured data to a coordinator node. Focusing on the Slotted Carrier Sense Multiple Access with Collision Avoidance algorithm (Slotted CSMA/CA) defined by the IEEE 802.15.4 norm in the beacon-enabled mode, we propose an enhanced backoff strategy to provide nodes an equitable access to the communication medium. Then we analyze its performance over realistic requirements of the considered sensors using the latest version of Castalia Simulator. The obtained results reveal the efficiency of our proposal as compared to the traditional profile of the norm in terms of reliability, timeliness and throughput.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124242692","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204237
M. El bakkali, Said Elkhaldi, H. Elftouh, N. Touhami
In this paper 16 elements small-signal equivalent circuit for GaAs pHEMT is presented. ED02AH process based on III-V materiel is chosen. This process is used in the improvement of telecommunication systems, space and defense applications. This work presents the results of direct extraction of the small signal or linear model based on an analytical method and measurements of the dispersion parameters [S]. The extraction of the parameters of the small signal equivalent scheme is done for an ED02AH (6x15$mu$m) process of GaAs technology, a transistor of 6 gate fingers, each with a width of 15 $mu$m. A good agreement between the simulated and measured parameters S confirms the validity of the proposed method.
{"title":"Small-Signal Modeling of GaAs – pHEMT Using Direct Extraction Method","authors":"M. El bakkali, Said Elkhaldi, H. Elftouh, N. Touhami","doi":"10.1109/ISCV49265.2020.9204237","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204237","url":null,"abstract":"In this paper 16 elements small-signal equivalent circuit for GaAs pHEMT is presented. ED02AH process based on III-V materiel is chosen. This process is used in the improvement of telecommunication systems, space and defense applications. This work presents the results of direct extraction of the small signal or linear model based on an analytical method and measurements of the dispersion parameters [S]. The extraction of the parameters of the small signal equivalent scheme is done for an ED02AH (6x15$mu$m) process of GaAs technology, a transistor of 6 gate fingers, each with a width of 15 $mu$m. A good agreement between the simulated and measured parameters S confirms the validity of the proposed method.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115164039","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204054
Souhaila Ben Haddi, A. Zugari, A. Zakriti, Soufiane Achraou
In this paper, we introduce a compact wideband microstrip band pass filter for 3.5GHz, with excellent performance for the next generation mobile standards “5G”. The frequency band also includes the frequencies of the WIMAX (Worldwide Interoperability for Microwave Access) and WLAN (wireless local area network) applications. The proposed band pass filter is based on a rectangular T-Shaped resonator. Their dimensions are equal to 9×5mm2. The proposed compact microstrip band pass filter has been designed by software CST Microwave Studio using FR4 substrate having relative permittivity (εr) of 4.3. This filter has a center frequency of 4,75GHz and 3dB bandwidth from 3 to 6GHz, an insertion loss low than 1dB, a return loss better than 30dB and also a fractional bandwidth more than 70%. This results are in good agreement with those accomplished by Advanced Design System “ADS”.
{"title":"A Compact Microstrip T-Shaped Resonator Band Pass Filter for 5G Applications","authors":"Souhaila Ben Haddi, A. Zugari, A. Zakriti, Soufiane Achraou","doi":"10.1109/ISCV49265.2020.9204054","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204054","url":null,"abstract":"In this paper, we introduce a compact wideband microstrip band pass filter for 3.5GHz, with excellent performance for the next generation mobile standards “5G”. The frequency band also includes the frequencies of the WIMAX (Worldwide Interoperability for Microwave Access) and WLAN (wireless local area network) applications. The proposed band pass filter is based on a rectangular T-Shaped resonator. Their dimensions are equal to 9×5mm2. The proposed compact microstrip band pass filter has been designed by software CST Microwave Studio using FR4 substrate having relative permittivity (εr) of 4.3. This filter has a center frequency of 4,75GHz and 3dB bandwidth from 3 to 6GHz, an insertion loss low than 1dB, a return loss better than 30dB and also a fractional bandwidth more than 70%. This results are in good agreement with those accomplished by Advanced Design System “ADS”.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116445676","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204250
Abderrahim Ezzine, H. Satori, Mohamed Hamidi, K. Satori
The main aim of an Automatic Speech Recognition system (ASR) is to produce a system that is able to simulate the human listener based on the learning approach and speech data of a studied language. In this paper, we describe the Darija Moroccan Dialect speech recognition system that is implemented to recognize the ten first Arabic digits spoken in Moroccan dialect (Darija) collected from 20 speakers including both males and females. This system is designed based on the CMU Sphinx tools through the ASR Hidden Markov Model method with small data and the Mel frequency spectral coefficients (MFCCs) that are used in the feature extraction phase. Our best-obtained accuracy is 96.27 % found with 8 GMMs.
{"title":"Moroccan Dialect Speech Recognition System Based on CMU SphinxTools","authors":"Abderrahim Ezzine, H. Satori, Mohamed Hamidi, K. Satori","doi":"10.1109/ISCV49265.2020.9204250","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204250","url":null,"abstract":"The main aim of an Automatic Speech Recognition system (ASR) is to produce a system that is able to simulate the human listener based on the learning approach and speech data of a studied language. In this paper, we describe the Darija Moroccan Dialect speech recognition system that is implemented to recognize the ten first Arabic digits spoken in Moroccan dialect (Darija) collected from 20 speakers including both males and females. This system is designed based on the CMU Sphinx tools through the ASR Hidden Markov Model method with small data and the Mel frequency spectral coefficients (MFCCs) that are used in the feature extraction phase. Our best-obtained accuracy is 96.27 % found with 8 GMMs.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":"319 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126805367","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 : 2020-06-01DOI: 10.1109/ISCV49265.2020.9204288
S. Iftikhar, F. Jabeen, Hira Nasir, Shahwana Fida
The tagging process involves use of labels to provide content with further information using a set of keywords (tags). A tag is a keyword or phrase used to provide metadata about a resource. Resource can be image, web page, video, audio etc., which are available on Web. In this research article the issue of polysemy (a word or phrase with multiple meanings) in tagging is analyzed because it creates a lot of confusion and is cause of ambiguity, redundancy and incorrect search results. In particular if a user looks at URLs the user can’t guess about what sort of resource it refers. By looking at tag set associated with a resource a user can guess about the resource, but the guess can be ambiguous if tag set contains polysemy tags. A novel solution is proposed for the detection of polysemy tags in folk tag set. The capabilities of Word Net, Wikipedia and visual tag dictionary are exploited. Experiments are performed on tag sets that is taken from Delicious. This approach can detect many common types of polysemy that appears in folksonomies like contrastive and complementary polysemy.
{"title":"WordNet and Wiki Based Approach for Finding Polysemy Tags in a Tag Set","authors":"S. Iftikhar, F. Jabeen, Hira Nasir, Shahwana Fida","doi":"10.1109/ISCV49265.2020.9204288","DOIUrl":"https://doi.org/10.1109/ISCV49265.2020.9204288","url":null,"abstract":"The tagging process involves use of labels to provide content with further information using a set of keywords (tags). A tag is a keyword or phrase used to provide metadata about a resource. Resource can be image, web page, video, audio etc., which are available on Web. In this research article the issue of polysemy (a word or phrase with multiple meanings) in tagging is analyzed because it creates a lot of confusion and is cause of ambiguity, redundancy and incorrect search results. In particular if a user looks at URLs the user can’t guess about what sort of resource it refers. By looking at tag set associated with a resource a user can guess about the resource, but the guess can be ambiguous if tag set contains polysemy tags. A novel solution is proposed for the detection of polysemy tags in folk tag set. The capabilities of Word Net, Wikipedia and visual tag dictionary are exploited. Experiments are performed on tag sets that is taken from Delicious. This approach can detect many common types of polysemy that appears in folksonomies like contrastive and complementary polysemy.","PeriodicalId":313743,"journal":{"name":"2020 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129781407","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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