{"title":"Named entity recognition using point prediction and active learning","authors":"Koga Kobayashi, Kei Wakabayashi","doi":"10.1145/3366030.3366072","DOIUrl":"https://doi.org/10.1145/3366030.3366072","url":null,"abstract":"Named entity recognition (NER) research has been spreading into specialty domains. A specialty domain corpus is smaller than a general domain corpus. Moreover, annotating a specialty domain corpus is more expensive than annotating a general corpus. Therefore, in this paper, we introduce a model that uses point-wise prediction and active learning to achieve a high extraction performance even in a small annotation corpus. We demonstrate the effectiveness of our approach through a simulation of active learning.","PeriodicalId":446280,"journal":{"name":"Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128578680","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":"Conversational AI for Corporate e-Learning","authors":"Bernhard Göschlberger, Christoph Brandstetter","doi":"10.1145/3366030.3366115","DOIUrl":"https://doi.org/10.1145/3366030.3366115","url":null,"abstract":"Natural language tutors have been an active research topic for decades and the widespread use of chat interfaces lead to a high level of acceptance of chatbots. Despite that, conversational AI has not found its way into the practice of corporate e-learning yet. In this paper we present a novel approach to leverage the advances in the field of conversational AI for corporate e-learning. Following a design science approach, we identify the pivotal stakeholders and design objectives. We propose a service architecture and demonstrate its feasibility with a prototypical implementation. Finally, we conclude that the proposed approach has the potential to lower entry barriers for conversational AI for the practice of corporate e-learning.","PeriodicalId":446280,"journal":{"name":"Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125954174","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 Blocks of Negotiating Agents for Healthcare Data","authors":"S. Boudko, W. Leister","doi":"10.1145/3366030.3366108","DOIUrl":"https://doi.org/10.1145/3366030.3366108","url":null,"abstract":"The healthcare market demands advanced, flexible, and secure solutions for personal health data sharing. In our paper, we present preliminary work that proposes a distributed infrastructure of negotiating agents for the healthcare domain. This infrastructure will support healthcare stakeholders to share and access patient health data in a secure way, thus providing benefits for patients and their treatment. Distributed ledger technologies and smart contracts can be considered as a basis for negotiations between distributed agents that carry health-related data. We present an overview of related work and outline the research methodology.","PeriodicalId":446280,"journal":{"name":"Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122641684","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":"Security Issues in Mobile Healthcare Applications","authors":"Alexander Feldner, Youna Jung","doi":"10.1145/3366030.3366106","DOIUrl":"https://doi.org/10.1145/3366030.3366106","url":null,"abstract":"Mobile healthcare applications, in short mHealth apps, are an efficient and more affordable way for patients to communicate with medical doctors and receive treatment using their mobile devices. However, the security of mHealth apps has become obstacle because many of mHealth apps deal with sensitive personal information including health-related data. To promote the developments of secure and trustworthy mHealth apps, in this paper, we survey mHealth-related security issues, not only general security issues but also mHealth-specific issues, and explore potential solutions to each issue.","PeriodicalId":446280,"journal":{"name":"Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125025130","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}
K. Radzikowski, Mateusz Forc, Le Wang, O. Yoshie, R. Nowak
{"title":"Accent neutralization for speech recognition of non-native speakers","authors":"K. Radzikowski, Mateusz Forc, Le Wang, O. Yoshie, R. Nowak","doi":"10.1145/3366030.3366083","DOIUrl":"https://doi.org/10.1145/3366030.3366083","url":null,"abstract":"These days, automatic speech recognition (ASR) systems achieve higher and higher accuracy rates. The score drops significantly, in case when the ASR system is being used with a non-native speaker of the language to be recognized. The main reason is specific pronunciation and accent features. A limited volume of labeled non-native speech datasets makes it difficult to train new ASR systems for non-native speakers. In our research, we tried tackling the problem and its influence on the accuracy of ASR systems, using the style transfer methodology. We designed a pipeline for modifying the speech of a non-native speaker, so that it resembles the native speech to a higher extent. Our methodology can be used as a wrapper for any existing ASR system, which reduces the necessity of training new algorithms for non-native speech. The modification can be thus performed before passing the data forward to the speech recognition system itself.","PeriodicalId":446280,"journal":{"name":"Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122827150","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 Hybrid Machine Learning Approach for Improving Mortality Risk Prediction on Imbalanced Data","authors":"Araek Tashkandi, L. Wiese","doi":"10.1145/3366030.3366040","DOIUrl":"https://doi.org/10.1145/3366030.3366040","url":null,"abstract":"The efficiency of Machine Learning (ML) models has widely been acknowledged in the healthcare area. However, the quality of the underlying medical data is a major challenge when applying ML in medical decision making. In particular, the imbalanced class distribution problem causes the ML model to be biased towards the majority class. Furthermore, the accuracy will be biased, too, which produces the Accuracy Paradox. In this paper, we identify an optimal ML model for predicting mortality risk for Intensive Care Units (ICU) patients. We comprehensively assess an approach that leverages the efficiency of ML ensemble learning (in particular, Gradient Boosting Decision Tree) and clustering-based data sampling to handle the imbalanced data problem that this model faces. We comprehensively compare different competitors (in terms of ML models as well as clustering methods) on a big real-world ICU dataset achieving a maximum area under the curve value of 0.956.","PeriodicalId":446280,"journal":{"name":"Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121529411","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":"Movie Genres Classification using Collaborative Filtering","authors":"Raji Ghawi, J. Pfeffer","doi":"10.1145/3366030.3366034","DOIUrl":"https://doi.org/10.1145/3366030.3366034","url":null,"abstract":"In this paper, we present an approach for classifying movie genres based on user-ratings. Our approach is based on collaborative filtering (CF), a common technique used in recommendation systems, where the similarity between movies based on user-ratings, is used to predict the genres of movies. The results of conducted experiments show that our genres classification approach outperforms many existing approaches, by achieving an F1-score of 0.70, and a hit-rate of 94%.","PeriodicalId":446280,"journal":{"name":"Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121639308","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":"Gamifying Human Behavior in Urban Crowdsourcing for a Sustainable Smart City","authors":"Risa Kimura, T. Nakajima","doi":"10.1145/3366030.3366031","DOIUrl":"https://doi.org/10.1145/3366030.3366031","url":null,"abstract":"One of the most important topics in future crowdsourcing is how to influence and coordinate collective people to perform micro-tasks towards their common goal achieved through crowdsourcing activities. For achieving the goal, crowdsourcing needs to take into account coordinating collective people not only encouraging individual people. This paper presents the Game as Rhetoric model that is a framework for designing digital rhetoric, which is embedded in the real world and influences participants' behavior. We then present Collective Action Crowdsourcing and its IoT-based prototype system as an example using the Game as Rhetoric model.","PeriodicalId":446280,"journal":{"name":"Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131969979","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}
Xinnan Chen, Muhammad Haseeb U. R. Rehman Khan, Kei Wakabayashi
{"title":"Estimation Method of L2 Learners' Second Language Ability by using Features in Conversation","authors":"Xinnan Chen, Muhammad Haseeb U. R. Rehman Khan, Kei Wakabayashi","doi":"10.1145/3366030.3366037","DOIUrl":"https://doi.org/10.1145/3366030.3366037","url":null,"abstract":"We are conducting a research to train second language(L2) learners's second language ability by utilizing chat system. The main problem of existing chat systems is that it is not possible to chat with learners to adapt their second language level. In this research, in order to add a function to an existing chat system we need to measure the learner's second language level. So, to extract learners' second language capability, we propose a method to predict the language examination score of learners from chat context. This research investigates, first whether the number of utterances, number of sentences, word tokens and word types per utterance of chat context are correlated with second language examination score. Second, we build a predicting model to see the relationship between the chat context and second language examination score. As feature values of regression model for predicting the language examination score, we use variables chat time, sentence time, word token and word type. Also the unnatural sentence structure as a variable. For evaluation we use the root mean square error to check the results of prediction model, we use this model with Japanese and English chat and compare the results. We show how this chat context data is affecting the second language examination score and discuss strategies for future enhancements.","PeriodicalId":446280,"journal":{"name":"Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131982675","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}
G. A. Schreiner, Denio Duarte, Guilherme Dal Bianco, R. Mello
{"title":"A Hybrid Partitioning Strategy for NewSQL Databases: The VoltDB Case","authors":"G. A. Schreiner, Denio Duarte, Guilherme Dal Bianco, R. Mello","doi":"10.1145/3366030.3366062","DOIUrl":"https://doi.org/10.1145/3366030.3366062","url":null,"abstract":"Several application domains deal with the management of massive data volumes and thousands of OLTP transactions per second. Traditional relational databases cannot cope with these requirements. NewSQL is a new generation of databases that provides both high scalability and availability and ACID properties support. Besides, it is a promising solution to handle these application data management needs. Although data partitioning is an essential feature for tuning relational databases, stills an open issue for NewSQL systems. In this paper, we propose a hybrid partitioning approach for NewSQL databases that allows the user to define the vertical and horizontal data partitions. In order to determine what site will store each data fragment, we propose a hash function that considers schema information and data access statistics. Our experimental evaluation compares our hybrid VoltDB version against the standard VoltDB. The results highlight that our strategy increases the number of single-site transactions from 37% to 76%.","PeriodicalId":446280,"journal":{"name":"Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132363662","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}