{"title":"An efficient Privacy-Preserving Recommender System","authors":"Thi Van Vu, T. Luong, Van Quan Hoang","doi":"10.1109/KSE56063.2022.9953800","DOIUrl":"https://doi.org/10.1109/KSE56063.2022.9953800","url":null,"abstract":"","PeriodicalId":93818,"journal":{"name":"The ... International Conference on Knowledge and Systems Engineering. International Conference on Knowledge and Systems Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80294912","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}
Tien T T Tran, Sy V Nghiem, Van T Le, Tho T Quan, Vinh Nguyen, Hong Yung Yip, Olivier Bodenreider
{"title":"Siamese KG-LSTM: A deep learning model for enriching UMLS Metathesaurus synonymy.","authors":"Tien T T Tran, Sy V Nghiem, Van T Le, Tho T Quan, Vinh Nguyen, Hong Yung Yip, Olivier Bodenreider","doi":"10.1109/kse50997.2020.9287797","DOIUrl":"https://doi.org/10.1109/kse50997.2020.9287797","url":null,"abstract":"<p><p>The Unified Medical Language System, or UMLS, is a repository of medical terminology developed by the U.S. National Library of Medicine for improving the computer system's ability of understanding the biomedical and health languages. The UMLS Metathesaurus is one of the three UMLS knowledge sources, containing medical terms and their relationships. Due to the rapid increase in the number of medical terms recently, the current construction of UMLS Metathesaurus, which heavily depends on lexical tools and human editors, is error-prone and time-consuming. This paper takes advantages of the emerging deep learning models for learning to predict the synonyms and non-synonyms between the pairs of biomedical terms in the Metathesaurus. Our learning approach focuses a subset of specific terms instead of the whole Metathesaurus corpus. Particularly, we train the models with biomedical terms from the Disorders semantic group. To strengthen the models, we enrich the inputs with different strategies, including synonyms and hierarchical relationships from source vocabularies. Our deep learning model adopts the Siamese KG-LSTM (Siamese Knowledge Graph - Long Short-Term Memory) in the architecture. The experimental results show that this approach yields excellent performance when handling the task of synonym detection for Disorders semantic group in the Metathesaurus. This shows the potential of applying machine learning techniques in the UMLS Metathesaurus construction process. Although the work in this paper focuses only on specific semantic group of Disorders, we believe that the proposed method can be applied to other semantic groups in the UMLS Metathesaurus.</p>","PeriodicalId":93818,"journal":{"name":"The ... International Conference on Knowledge and Systems Engineering. International Conference on Knowledge and Systems Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/kse50997.2020.9287797","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40583474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A data-driven approach to evaluate the social media post and its influences on customers","authors":"Pham Thi Viet Huong, Tran Anh Vu","doi":"10.1109/KSE50997.2020.9287648","DOIUrl":"https://doi.org/10.1109/KSE50997.2020.9287648","url":null,"abstract":"","PeriodicalId":93818,"journal":{"name":"The ... International Conference on Knowledge and Systems Engineering. International Conference on Knowledge and Systems Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75497965","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":"Airline Stock Performance: PRASM, RASM or Profit?","authors":"Le Duc Thinh, N. Lam","doi":"10.1109/KSE50997.2020.9287787","DOIUrl":"https://doi.org/10.1109/KSE50997.2020.9287787","url":null,"abstract":"","PeriodicalId":93818,"journal":{"name":"The ... International Conference on Knowledge and Systems Engineering. International Conference on Knowledge and Systems Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75943595","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}
Thi Minh Phuong Ha, Duy Hung Tran, L. Hạnh, N. Binh
{"title":"Experimental Study on Software Fault Prediction Using Machine Learning Model","authors":"Thi Minh Phuong Ha, Duy Hung Tran, L. Hạnh, N. Binh","doi":"10.1109/KSE.2019.8919429","DOIUrl":"https://doi.org/10.1109/KSE.2019.8919429","url":null,"abstract":"Faults are the leading cause of time consuming and cost wasting during software life cycle. Predicting faults in early stage improves the quality and reliability of the system and also reduces cost for software development. Many researches proved that software metrics are effective elements for software fault prediction. In addition, many machine learning techniques have been developed for software fault prediction. It is important to determine which set of metrics are effective for predicting fault by using machine learning techniques. In this paper, we conduct an experimental study to evaluate the performance of seven popular techniques including Logistic Regression, K-nearest Neighbors, Decision Tree, Random Forest, Naive Bayes, Support Vector Machine and Multilayer Perceptron using software metrics from Promise repository dataset usage. Our experiment is performed on both method-level and class-level datasets. The experimental results show that Support Vector Machine archives a higher performance in class-level datasets and Multilayer Perception produces a better accuracy in method-level datasets among seven techniques above.","PeriodicalId":93818,"journal":{"name":"The ... International Conference on Knowledge and Systems Engineering. International Conference on Knowledge and Systems Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77135269","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":"Building a Specific Amino Acid Substitution Model for Dengue Viruses","authors":"Thu Le Kim, C. C. Dang, L. Vinh","doi":"10.1109/KSE.2018.8573341","DOIUrl":"https://doi.org/10.1109/KSE.2018.8573341","url":null,"abstract":"","PeriodicalId":93818,"journal":{"name":"The ... International Conference on Knowledge and Systems Engineering. International Conference on Knowledge and Systems Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83770224","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":"Bidirectional programming and software adaptation: Towards a happy marriage","authors":"Zhenjiang Hu","doi":"10.1109/KSE.2017.8119422","DOIUrl":"https://doi.org/10.1109/KSE.2017.8119422","url":null,"abstract":"Bidirectional transformations and bidirectional programming have been attracting a lot of attention lately, both in the programming languages community, and in the software engineering community. As bidirectional programming languages are growing more mature, they are getting easier to use for software engineers, more efficient, and more reliable. The strongest argument in favor of bidirectional programming is its ability to provide a synchronization mechanisms between a source and a view, that is guaranteed to be correct by construction. On the other hand, software adaptation is an ability to adapt at run-time to changing user needs, system intrusions or faults, and changing operational environment. In this talk, we shall explain the essence of bidirectional transformation, introduce a powerful language for bidirectional programming, and show how bidirectional programming can provide a powerful mechanism to modularize adaptive software. This mechanism would be very useful not only for reusing a adaptive software for different target systems, but also for maintaining separation of concerns when developing complex adaptive software.","PeriodicalId":93818,"journal":{"name":"The ... International Conference on Knowledge and Systems Engineering. International Conference on Knowledge and Systems Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85637821","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":"A multi-objective ensemble learning approach based on the non-dominated sorting differential evolution for forecasting currency exchange rates","authors":"T. Dinh, V. Vu, L. Bui","doi":"10.1109/KSE.2016.7758036","DOIUrl":"https://doi.org/10.1109/KSE.2016.7758036","url":null,"abstract":"Currency exchange rates forecasting is paid a considerable attention of the researchers in the field of forecasting. The neural network is a well-known tool in machine learning. However, two issues are always interested by the scientists: getting toward to global convergence of extreme solutions and determining the optimal weight of the network. This paper proposes the multi-objective method of ensemble learning techniques based on the non-dominated sorting differential evolution (NSDE, a kind of direction-based methods) for training neural networks and application in Foreign Exchange forecasting problems. Two objectives of the selected model are defined based on the Mean Squared Errors and Diversity respectively, in which we used the concept of fitness-sharing based diversity. We experimented the model on four data sets of currency and compared with some of the others that the research community has announced. Through the performance forecasting indicators to show that our new method gives outstanding forecasting results.","PeriodicalId":93818,"journal":{"name":"The ... International Conference on Knowledge and Systems Engineering. International Conference on Knowledge and Systems Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/KSE.2016.7758036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72410367","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}
M. R. Hasan, M. Ibrahimy, S. Motakabber, S. Shahid
{"title":"Classification of Multichannel EEG Signal by Linear Discriminant Analysis","authors":"M. R. Hasan, M. Ibrahimy, S. Motakabber, S. Shahid","doi":"10.1007/978-3-319-08422-0_42","DOIUrl":"https://doi.org/10.1007/978-3-319-08422-0_42","url":null,"abstract":"","PeriodicalId":93818,"journal":{"name":"The ... International Conference on Knowledge and Systems Engineering. International Conference on Knowledge and Systems Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87334748","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":"Knowledge and Systems Engineering - Proceedings of the Sixth International Conference KSE 2014, Hanoi, Vietnam, 9-11 October 2014","authors":"","doi":"10.1007/978-3-319-11680-8","DOIUrl":"https://doi.org/10.1007/978-3-319-11680-8","url":null,"abstract":"","PeriodicalId":93818,"journal":{"name":"The ... International Conference on Knowledge and Systems Engineering. International Conference on Knowledge and Systems Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86211904","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}