{"title":"A Pattern and POS Auto-Learning Method for Terminology Extraction from Scientific Text","authors":"Wei Shao , Bolin Hua , Linqi Song","doi":"10.2478/dim-2021-0005","DOIUrl":"10.2478/dim-2021-0005","url":null,"abstract":"<div><p>A lot of new scientific documents are being published on various platforms every day. It is more and more imperative to quickly and efficiently discover new words and meanings from these documents. However, most of the related works rely on labeled data, and it is quite difficult to deal with unlabeled new documents efficiently. For this, we have introduced an unsupervised method based on sentence patterns and part of speech (POS) sequences. Our method just needs a few initial learnable patterns to obtain the initial terminology tokens and their POS sequences. In this process, new patterns are constructed and can match more sentences to find more POS sequences of terminology. Finally, we use obtained POS sequences and sentence patterns to extract terminology terms in new scientific text. Experiments on paper abstracts from Web of Knowledge show that this method is practical and can achieve a good performance on our test data.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"5 3","pages":"Pages 329-335"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2543925122000031/pdfft?md5=def416db2e2762263b15157e5919b4c2&pid=1-s2.0-S2543925122000031-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45670167","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":"Automatic Subject Classification of Public Messages in E-government Affairs","authors":"Pei Pan , Yijin Chen","doi":"10.2478/dim-2021-0004","DOIUrl":"10.2478/dim-2021-0004","url":null,"abstract":"<div><p>Public messages on the Internet political inquiry platform rely on manual classification, which has the problems of heavy workload, low efficiency, and high error rate. A Bi-directional long short-term memory (Bi-LSTM) network model based on attention mechanism was proposed in this paper to realize the automatic classification of public messages. Considering the network political inquiry data set provided by the BdRace platform as samples, the Bi-LSTM algorithm is used to strengthen the correlation between the messages before and after the training process, and the semantic attention to important text features is strengthened in combination with the characteristics of attention mechanism. Feature weights are integrated through the full connection layer to carry out classification calculations. The experimental results show that the F1 value of the message classification model proposed here reaches 0.886 and 0.862, respectively, in the data set of long text and short text. Compared with three algorithms of long short-term memory (LSTM), logistic regression, and naive Bayesian, the Bi-LSTM model can achieve better results in the automatic classification of public message subjects.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"5 3","pages":"Pages 336-347"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2543925122000043/pdfft?md5=9eb8a1ad631981af104c47aa695f8e57&pid=1-s2.0-S2543925122000043-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46034683","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":"Towards a Sustainable Infrastructure for the Preservation of Cultural Heritage and Digital Scholarship","authors":"Peter X. Zhou","doi":"10.2478/dim-2020-0052","DOIUrl":"https://doi.org/10.2478/dim-2020-0052","url":null,"abstract":"<div><p>The digital lifecycle encompasses definitive processes for data curation and management, long-term preservation, and dissemination, all of which are key building blocks in the development of a digital library. Maintaining a complete digital lifecycle workflow is vital to the preservation of digital cultural heritage and digital scholarship. This paper considers digital lifecycle programs for digital libraries, noting similarities between the digital and print lifecycles and referring to the example of the Digital Dunhuang project. Only through a systematic and sustainable digital lifecycle program can platforms for cross-disciplinary research and repositories for large aggregations of digital content be built. Moreover, advancing digital lifecycle development will ensure that knowledge and scholarship created in the digital age will have the same chances for survival that print-and-paper scholarship has had for centuries. It will also ensure that digital library users will have effective access to aggregated content across different domains and platforms.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"5 2","pages":"Pages 253-261"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2543925122000122/pdfft?md5=fc16c10f00b08b6e8a9abc81a05fc721&pid=1-s2.0-S2543925122000122-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92006378","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":"Using Open Data to Monitor the Status of a Metropolitan Area: The Case of the Metropolitan Area of Turin","authors":"Filippo Candela , Paolo Mulassano","doi":"10.2478/dim-2021-0001","DOIUrl":"10.2478/dim-2021-0001","url":null,"abstract":"Abstract The paper presents and discusses the method adopted by Compagnia di San Paolo, one of the largest European philanthropic institutions, to monitor the advancement, despite the COVID-19 situation, in providing specific input to the decision-making process for dedicated projects. An innovative approach based on the use of daily open data was adopted to monitor the metropolitan area with a multidimensional perspective. Several open data indicators related to the economy, society, culture, environment, and climate were identified and incorporated into the decision support system dashboard. Indicators are presented and discussed to highlight how open data could be integrated into the foundation's strategic approach and potentially replicated on a large scale by local institutions. Moreover, starting from the lessons learned from this experience, the paper analyzes the opportunities and critical issues surrounding the use of open data, not only to improve the quality of life during the COVID-19 epidemic but also for the effective regulation of society, the participation of citizens, and their well-being.","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"5 2","pages":"Pages 299-307"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2543925122000158/pdfft?md5=1fc7094b89e3ed7a5941c7bb3679fdf0&pid=1-s2.0-S2543925122000158-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46103804","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":"Hybrid Intelligence in Big Data Environment: Concepts, Architectures, and Applications of Intelligent Service","authors":"Zhenghao Liu , Xi Zeng","doi":"10.2478/dim-2020-0051","DOIUrl":"10.2478/dim-2020-0051","url":null,"abstract":"<div><p>Based on the emerging concept of “Hybrid Intelligence,” this paper aims to explore a new model of human–computer interaction, and deeply research on its development and application of Intelligent Service in the big data environment. It systematically explores the related academic concepts of hybrid intelligence, and establishes its architecture model. The development of hybrid intelligence is faced with cognitive differences, system fragmentation, human–machine digital divide, and other issues. Strengthening the interaction between cognition and perception can be the key to break through the bottleneck. The intelligent service system based on the hybrid intelligent architecture takes knowledge fusion as the core, and “cloud intelligent brain” is making it possible for the human–computer symbiosis driven by hybrid intelligence. The proposed advanced human–computer interaction mode constructs a hybrid intelligent architecture model, enriches the concept system of human–machine hybrid intelligence, and provides a new landing scheme for intelligent services based on complex scenes in the big data environment.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"5 2","pages":"Pages 262-276"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2543925122000134/pdfft?md5=580598a3c66ddc27bada03fbe747df43&pid=1-s2.0-S2543925122000134-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44187516","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":"The Use of Academic Social Networking Sites in Scholarly Communication: Scoping Review","authors":"Milkyas Hailu , Jianhua Wu","doi":"10.2478/dim-2020-0050","DOIUrl":"10.2478/dim-2020-0050","url":null,"abstract":"<div><p>This research provides a systematic analysis of 115 previous literatures on the use of academic social networking sites (ASNs) in scholarly communication. Previous research on the subject has mainly taken a disciplinary and user perspective. This research conceptualizes the use of ASNs in scholarly communication in the space between social interactions and the technologies themselves. Keyword analysis and scoping review approaches have been used to analyze the comprehensive literature in the field. The study found a geographic variation in what motivates academics to use ASNs. Scholar discovery and sharing are the primary driving factors identified in the literature. Four main themes within the research literature are proposed: motivation and uses, impact assessment, features and services, and scholarly big data. The study found that there has been an increase in scholarly big data research in recent years. The paper also discusses the key findings and concepts stated in each theme. This gives academics a better understanding of what ASNs can do and their weaknesses, and identifies gaps in the literature that are worth addressing in future investigations. We suggest that future studies may also extend the existing theoretical framework and epistemological approaches to better predict and clarify the socio-technical dimensions of ASNs use in scholarly communication. In addition, this study has implications for academic and research institutions, libraries and information literacy programs, and future studies on the topic.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"5 2","pages":"Pages 277-298"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2543925122000146/pdfft?md5=27965f1fb0200ffff887f1053f1044c9&pid=1-s2.0-S2543925122000146-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49385890","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 Comparison Study of Measures to Quantify the Evolution of Prolific Research Teams","authors":"Bentao Zou , Yuefen Wang","doi":"10.2478/dim-2020-0028","DOIUrl":"10.2478/dim-2020-0028","url":null,"abstract":"<div><p>Scientific research teams play an increasingly significant role in scientific activities. To better understand the dynamic evolution process of research teams, we explored measures that quantify the evolution of prolific research teams. We collected our data from the Web of Science in the field of artificial intelligence, and applied the label propagation algorithm to identify research teams in the co-authorship network. The Top 1‰ prolific teams were selected as our research object, whose node stability and two types of edge stabilities were measured. The results show that prolific teams are much more stable during the evolution process, in terms of both member and membership stability. The measure of stability has varying degrees of impact on teams with different sizes, and small-sized teams get considerably different stability results by different measures.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"5 1","pages":"Pages 56-64"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2543925122000213/pdfft?md5=f37cf316a71f0ad36d20545073f1e4b9&pid=1-s2.0-S2543925122000213-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42703336","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":"Exploring Occupation Differences in Reactions to COVID-19 Pandemic on Twitter","authors":"Yi Zhao , Haixu Xi , Chengzhi Zhang","doi":"10.2478/dim-2020-0032","DOIUrl":"10.2478/dim-2020-0032","url":null,"abstract":"<div><p>Coronavirus disease 2019 (COVID-19) pandemic-related information are flooded on social media, and analyzing this information from an occupational perspective can help us to understand the social implications of this unprecedented disruption. In this study, using a COVID-19-related dataset collected with the Twitter IDs, we conduct topic and sentiment analysis from the perspective of occupation, by leveraging Latent Dirichlet Allocation (LDA) topic modeling and Valence Aware Dictionary and sEntiment Reasoning (VADER) model, respectively. The experimental results indicate that there are significant topic preference differences between Twitter users with different occupations. However, occupation-linked affective differences are only partly demonstrated in our study; Twitter users with different income levels have nothing to do with sentiment expression on covid-19-related topics.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"5 1","pages":"Pages 110-118"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8969477/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10491312","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":"How Users' Gaze Behavior Is Related to Their Quality Evaluation of a Health Website Based on HONcode Principles?","authors":"Qin Qin , Qing Ke , Jia Tina Du , Yushan Xie","doi":"10.2478/dim-2020-0045","DOIUrl":"10.2478/dim-2020-0045","url":null,"abstract":"<div><p>While the health website is an easily accessible source for patients to use when seeking health information, the quality of online health information has been a critical issue that concerns all stakeholders in healthcare. The aim of this research was to examine the relationship between users' evaluation of the health website quality and their gaze behavior on the web pages. Eye tracking and a self-report questionnaire based on the HONcode principles were used to address the objective. We found that (1) the evaluations of authority, privacy, financial disclosure, and advertising policy are positively correlated with the fixation count and total fixation duration toward corresponding page components, while the evaluations of complementarity and attribution are negatively correlated with the fixation count and total fixation duration to corresponding page components; and (2) the fixation count and total fixation duration toward health information sources are negatively related to the evaluation of health website quality, while the fixation count and total fixation duration to site owner are positively related to the quality evaluation. Users' attention to page components is closely related to the evaluation of principles, and also has a certain impact on the overall quality evaluation of a health website. Based on the findings, our research may serve to improve the health website design and be a foundation to develop an automatic evaluation approach of the health website quality.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"5 1","pages":"Pages 75-85"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2543925122000237/pdfft?md5=505d4cf3826e5cf99091270e3b6e9a62&pid=1-s2.0-S2543925122000237-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42606862","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":"Quality Assessment for Digital Stories by Young Authors","authors":"Joana K.Y. Tse , Stephanie W.Y. Chan , Samuel K.W. Chu","doi":"10.2478/dim-2020-0039","DOIUrl":"10.2478/dim-2020-0039","url":null,"abstract":"<div><p>Digital storytelling, an innovative way of writing, has been introduced to young learners who are taught to construct stories with digital tools to convey their knowledge and ideas. In 2018 and 2019, 31 digital stories created by Hong Kong primary school students were published on a digital story writing platform and linked from an online gamified reading platform. Each book on average gained 4,000+ views from across the globe and received 3,000+ favorable comments in total. While the digital stories are popular in these platforms, their quality and education value are uncertain. A review of the literature shows there is a lack of robust tools for assessing digital stories by young authors. The research team for this paper thus constructed their own framework in evaluating digital stories. An assessment of the stories has been done by two capable assessors, who found that the stories overall were of good quality and suggested room for improvement. This paper made three contributions: (1) “invention” of a digital story assessment framework; (2) it shows that stories created by students (with support from educators) can be an enjoyable and useful educational resource for their peers; and (3) digital storytelling can help foster the development of young authors.</p></div>","PeriodicalId":72769,"journal":{"name":"Data and information management","volume":"5 1","pages":"Pages 174-183"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S254392512200033X/pdfft?md5=560432ac1e68dbe531f2159c20ffad7a&pid=1-s2.0-S254392512200033X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47986720","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}