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Finding sequential patterns with TF-IDF metrics in health-care databases

Mining, Edmonton, Canada, July 2002, pp. 429-435. ⇒291 [4] P. Fournier-Viger, SPMF - an open-source data mining library, 2014. ⇒ 291, 306 [5] T. Z. Gál, G. Kovács, Z. T. Kardkovács, Survey on privacy preserving data mining techniques in health care databases, Acta Univ. Sapientiae, Informatica, 6, 1 (2014) 33-55. ⇒305 [6] L. Geng, H. J. Hamilton, Interestingness measures for data mining: A survey, ACM Computing Surveys (CSUR), 38, 3 (2006) ⇒292, 293, 294 [7] K. Gouda, M. Hassaan, Mining sequential patterns

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A survey on sentiment classification algorithms, challenges and applications

. Kamps, M. Marx, R. J. Mokken, M. D. Rijkel, Using wordnet to measure semantic orientations of adjectives, LREC , 2004, pp. 1115–1118. ⇒ 63 [21] H. Kanayama, T. Nasukawa, Fully automatic lexicon expansion for domain-oriented sentiment analysis, Proc. 2006 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics , 2006, pp. 355–363. ⇒ 64 [22] A. Mudinas, D. Zhang, M. Levene, Combining lexicon and learning based approaches for concept-level sentiment analysis, Proc. of the First Int. Workshop on Issues of

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Data Mining in Elite Beach Volleyball – Detecting Tactical Patterns Using Market Basket Analysis

/ACM Transactions on Networking, 20 (6), 1788-1799. Bray, T. (2017). The JavaScript Object Notation (JSON) Data Interchange Format. RFC 8259, RFC Editor. Cakir, O., & Aras, M. E. (2012). A Recommendation Engine by Using Association Rules. Procedia – Social and Behavioral Sciences , 62, 452-456. World Conference on Business, Economics and Management (BEM-2012), May 4-6 2012, Antalya, Turkey. Cintia, P. U. d. P., Rinzivillo, S. I. N. R. C., & Pappalardo, L. U. d. P. (2015). A network-based approach to evaluate the performance of football teams. In Machine

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An Influence Prediction Model for Microblog Entries on Public Health Emergencies

1 Introduction Public health emergencies generally pose serious threats and significant losses to public health, economic development, and social stability. Since they break out in a short time and spread rapidly, the management departments of public health emergencies often face enormous challenges. They need to take effective measures in time to prevent the spread and upgrade of events, as well as eliminate the source of hazards and subsequent influence promptly. With the continuous development of Web 2.0 and mobile Internet technology, microblog

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Providing Research Data Management (RDM) Services in Libraries: Preparedness, Roles, Challenges, and Training for RDM Practice

1 Introduction Around the world, research data management (RDM) has been becoming an increasingly important service that a variety of information centers and libraries provide. According to Whyte and Tedds (2011) , “Research data management concerns the organization of data, from its entry to the research cycle through to the dissemination and archiving of valuable results” (p. 1). Two years later, in the ARL (Association of Research Libraries) SPEC (Systems and Procedures Exchange Center) Kit 334 entitled “Research Data Management Services,” Fearon et al

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Investigating Weak Supervision in Deep Ranking

measuring the similarities between the two representations. This line of research includes DSSM ( Huang et al., 2013 ), C-DSSM ( Shen, He, Gao, Deng, & Mesnil, 2014 ), and ARC-I (Hu, Lu, Li, & Chen, 2014). 2) Interaction-focused model – ARC-II ( Hu et al., 2014 ), DRMM ( Guo et al., 2016 ), MatchPyramid ( Pang et al., 2016 ), and K-NRM ( Xiong et al., 2017 ) belong to this category. The term-level interactions between queries and candidate documents are calculated first in these models. Then, the neural networks learn query–document matching patterns from these

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Understanding and Evaluating Research and Scholarly Publishing in the Social Sciences and Humanities (SSH)

evaluation. I have experienced increased interest in the evaluation of the SSH in China since then, not only by the invitation to hold the Luojia Lecture in Wuhan but also at meetings and conferences organized by, e.g., The Chinese Academy of Social Sciences Evaluation Studies (CASSES) and the Beijing and Chengdu branches of the National Science Library of the Chinese Academy of Sciences. The School of Information Management at Wuhan University has recently initiated a PhD project supervised by professor Lin Zhang with the aim of studying the publication patterns and

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A Longitudinal Analysis of the Effect of Alphabetization on Academic Careers

that analyzed degree of alphabetization of academic fields mostly agreed upon their measures although they used different datasets and/or methodologies ( Levitt & Thelwall, 2013 ; Waltman, 2012 ; Yuret, 2016 ). Two programs – mathematics and economics – are considered to be alphabetic academic fields. The other three programs – physics, political science, and history – are considered to be “partially academic fields”. In partially academic fields, only some of the publications use alphabetic order in sorting authors. For example, publications in particle physics

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, Austria., p. 5373. Burdet, O.L. & Zanella, J.-L., (2000). Automatic monitoring of bridges using electronic inclinometers. 16th Congress of IABSE , Lucerne, 2000. Burdet, O.L. & Zanella, J.-L., (2002). Automatic monitoring of the Riddes bridges using electronic inclinometers. First International Conference on Bridge Maintenance, Safety and Management IABMAS, Barcelona, 2002. Hou, X., Yang, X. & Huang, Q. (2005). Using Inclinometers to Measure Bridge Deflection. J. Bridge Eng ., 10(5), pp. 564-569. Milev

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Fuzzy Similarity and Fuzzy Inclusion Measures in Polyline Matching: A Case Study of Potential Streams Identification for Archaeological Modelling in GIS

of Energy, Information and Communications, 1, 15-22. Dice, L. R. (1945). Measures of the Amount of Ecologic Association Between Species. Ecology, 26(3), 297-302. doi: 10.2307/1932409. Ewing, G. M. (1985). Calculus of Variations with Applications. Dover Publications, New York. Ford, A., Clarke, K. C. & Raines, G. (2009). Modeling Settlement Patterns of the Late Classic Maya Civilization with Bayesian Methods and Geographic Information Systems. Annals of the Association of American Geographers, 99(3), 1-25. doi: 10

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