{"title":"Improving Question Analysis for Arabic Question Answering in the Medical Domain","authors":"Sondes Dardour, Héla Fehri, K. Haddar","doi":"10.13053/cys-26-3-4345","DOIUrl":"https://doi.org/10.13053/cys-26-3-4345","url":null,"abstract":"","PeriodicalId":333706,"journal":{"name":"Computación Y Sistemas","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132647984","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}
Manuela Nayantara Jeyaraj, S. Perera, Malith Jayasinghe, Nadheesh Jihan
{"title":"Probabilistic Error Detection Model for Knowledge Graph Refinement","authors":"Manuela Nayantara Jeyaraj, S. Perera, Malith Jayasinghe, Nadheesh Jihan","doi":"10.13053/cys-26-3-4346","DOIUrl":"https://doi.org/10.13053/cys-26-3-4346","url":null,"abstract":"","PeriodicalId":333706,"journal":{"name":"Computación Y Sistemas","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115551406","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}
O. E. Ojo, Thang Ta Hoang, A. Gelbukh, Hiram Calvo, G. Sidorov, O. O. Adebanji
{"title":"Automatic Hate Speech Detection Using CNN Model and Word Embedding","authors":"O. E. Ojo, Thang Ta Hoang, A. Gelbukh, Hiram Calvo, G. Sidorov, O. O. Adebanji","doi":"10.13053/cys-26-2-4107","DOIUrl":"https://doi.org/10.13053/cys-26-2-4107","url":null,"abstract":"","PeriodicalId":333706,"journal":{"name":"Computación Y Sistemas","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125256029","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}
Alberto Castro-Hernández, Verónica Pérez-Rosas, K. Swigger
{"title":"Effect of Temporal Patterns on Task Cohesion in Global Software Development Teams","authors":"Alberto Castro-Hernández, Verónica Pérez-Rosas, K. Swigger","doi":"10.13053/cys-26-2-4256","DOIUrl":"https://doi.org/10.13053/cys-26-2-4256","url":null,"abstract":"","PeriodicalId":333706,"journal":{"name":"Computación Y Sistemas","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129837343","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}
F. E. Miranda-Perea, Sammantha Omana Silva, Lourdes Del Carmen González-Huesca
{"title":"A Dual-Context Sequent Calculus for S4 Modal Lambda-Term Synthesis","authors":"F. E. Miranda-Perea, Sammantha Omana Silva, Lourdes Del Carmen González-Huesca","doi":"10.13053/cys-26-2-4238","DOIUrl":"https://doi.org/10.13053/cys-26-2-4238","url":null,"abstract":"","PeriodicalId":333706,"journal":{"name":"Computación Y Sistemas","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131651823","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 investigate the two agents approximate agreement problem in a dynamic network in which topology may change unpredictably, and where consensus is not solvable. It is known that the number of rounds necessary and sufficient to guarantee that the two agents output values 1 /k 3 away from each other is k . We distil ideas from previous papers to provide a self-contained, elementary introduction, that explains this result from the epistemic logic perspective.
{"title":"Two-Agent Approximate Agreement from an Epistemic Logic Perspective","authors":"J. Armenta-Segura, J. Ledent, S. Rajsbaum","doi":"10.13053/cys-26-2-4234","DOIUrl":"https://doi.org/10.13053/cys-26-2-4234","url":null,"abstract":"We investigate the two agents approximate agreement problem in a dynamic network in which topology may change unpredictably, and where consensus is not solvable. It is known that the number of rounds necessary and sufficient to guarantee that the two agents output values 1 /k 3 away from each other is k . We distil ideas from previous papers to provide a self-contained, elementary introduction, that explains this result from the epistemic logic perspective.","PeriodicalId":333706,"journal":{"name":"Computación Y Sistemas","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116867619","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 understanding person's sentiments for catastrophic events has been a major subject of research. In recent times COVID19 has raised psychological issues in people's minds across world. Sentiment analysis has played significant role in analysing reviews across wide array of real-life situations. With constant development of deep learning based language models, this has become an active investigation area. With COVID19 pandemic different countries have faced several peaks resulting in lockdowns. During this time people have placed their sentiments in social media. As review data corpora grows it becomes necessary to develop robust sentiment analysis models capable of extracting people's viewpoints and sentiments. In this paper, we present a computational framework which uses deep learning based language models through delayed recurrent neural networks (d-RNN) and hierarchical version of d-RNN (Hd-RNN) for sentiment analysis catering to rise of COVID19 cases in different parts of India. Sentiments are reviewed considering time window spread across 2020 and 2021. Multi-label sentiment classification is used where more than one sentiment are expressed at once. Both d-RNN and Hd-RNN are optimized by fine tuning different network parameters and compared with BERT variants, LSTM as well as traditional methods. The methods are evaluated with highly skewed data as well as using precision, recall and F1 scores. The results on experimental datasets indicate superiority of Hd-RNN considering other techniques.
{"title":"Sentiment Analysis of COVID19 Reviews Using Hierarchical Version of d-RNN","authors":"A. Chaudhuri","doi":"10.13053/CyS-26-2-4143","DOIUrl":"https://doi.org/10.13053/CyS-26-2-4143","url":null,"abstract":"In recent years understanding person's sentiments for catastrophic events has been a major subject of research. In recent times COVID19 has raised psychological issues in people's minds across world. Sentiment analysis has played significant role in analysing reviews across wide array of real-life situations. With constant development of deep learning based language models, this has become an active investigation area. With COVID19 pandemic different countries have faced several peaks resulting in lockdowns. During this time people have placed their sentiments in social media. As review data corpora grows it becomes necessary to develop robust sentiment analysis models capable of extracting people's viewpoints and sentiments. In this paper, we present a computational framework which uses deep learning based language models through delayed recurrent neural networks (d-RNN) and hierarchical version of d-RNN (Hd-RNN) for sentiment analysis catering to rise of COVID19 cases in different parts of India. Sentiments are reviewed considering time window spread across 2020 and 2021. Multi-label sentiment classification is used where more than one sentiment are expressed at once. Both d-RNN and Hd-RNN are optimized by fine tuning different network parameters and compared with BERT variants, LSTM as well as traditional methods. The methods are evaluated with highly skewed data as well as using precision, recall and F1 scores. The results on experimental datasets indicate superiority of Hd-RNN considering other techniques.","PeriodicalId":333706,"journal":{"name":"Computación Y Sistemas","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124463660","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}
{"title":"wPOI: Weather-Aware POI Recommendation Engine","authors":"Rajani Trivedi, Bibudhendu Pati, C. Panigrahi","doi":"10.13053/cys-26-2-4261","DOIUrl":"https://doi.org/10.13053/cys-26-2-4261","url":null,"abstract":"","PeriodicalId":333706,"journal":{"name":"Computación Y Sistemas","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128307336","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}
{"title":"How Much Deep Is Deep Enough?","authors":"Diego Uribe, Enrique Cuan","doi":"10.13053/cys-26-2-4260","DOIUrl":"https://doi.org/10.13053/cys-26-2-4260","url":null,"abstract":"","PeriodicalId":333706,"journal":{"name":"Computación Y Sistemas","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122312346","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}
A. Manzo-Martinez, F. Gaxiola, Graciela Ramírez Alonso, F. Martínez-Reyes
{"title":"A Comparative Study in Machine Learning and Audio Features for Kitchen Sounds Recognition","authors":"A. Manzo-Martinez, F. Gaxiola, Graciela Ramírez Alonso, F. Martínez-Reyes","doi":"10.13053/cys-26-2-4244","DOIUrl":"https://doi.org/10.13053/cys-26-2-4244","url":null,"abstract":"","PeriodicalId":333706,"journal":{"name":"Computación Y Sistemas","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121717037","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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