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An investigation on the evolution of diabetes data in social Q&A logs

-613). New York: IEEE. Kim J. Yang M. Hwang Y. Jeon S. Kim K. Jung I. S. Choi C. Cho W. Na J. 2012 Customer preference analysis based on SNS data Proceedings of Second International Conference on Cloud and Green Computing/Second International Conference on Social Computing and its Applications (CGC/SCA 2012) 609 613 New York IEEE Lancichinetti, A., & Fortunato, S. (2009). Community detection algorithms: A comparative analysis. Physical Review E , 80 (5), 56117. 10.1103/PhysRevE.80.056117 Lancichinetti A. Fortunato S. 2009 Community detection algorithms: A comparative

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Big Data in Health Care: Applications and Challenges

Informatics Retrieved from https://www.mendeley.com/catalogue/patient-apps-improved-healthcare-novelty-mainstream/ Aitken M. Gauntlett C. 2013 Patient apps for improved healthcare: from novelty to mainstream IMS Institute for Healthcare Informatics Retrieved from https://www.mendeley.com/catalogue/patient-apps-improved-healthcare-novelty-mainstream/ Alyass, A., Turcotte, M., & Meyre, D. (2015). From big data analysis to personalized medicine for all: Challenges and opportunities. BMC Medical Genomics, 8 (1), 33. 10.1186/s12920-015-0108-y Alyass A

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Burgeoning Data Repository Systems, Characteristics, and Development Strategies: Insights of Natural Resources and Environmental Scientists

data practices in habitat ecology In: Gonzalo J., Thanos C., Verdejo M.F., Carrasco R.C. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2006. Lecture Notes in Computer Science vol 4172 Springer, Berlin, Heidelberg Borgman, C.L., Wallis, J.C., & Enyedy, N. (2007a). Little science confronts the data deluge: Habitat ecology, embedded sensor networks, and digital libraries. International Journal on Digital Libraries, 7(1-2): 17-30. https://doi.org/10.1007/s00799-007-0022-9 10.1007/s00799-007-0022-9 Borgman C.L. Wallis J.C. Enyedy N. 2007a Little

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Supporting Book Search: A Comprehensive Comparison of Tags vs. Controlled Vocabulary Metadata

( t (305) = 2.139, p < .05, ES = 0.122, 95% CI [0.0016, 0.0385]). Table 5 Results for the individual metadata elements. Metadata element NDCG@10 Core 0.0533 CV 0.0319 Review 0.0993 Tags 0.0395 Table 6 Results for the combined metadata elements. Metadata elements NDCG@10 Core + CV 0.0540 Core + Reviews 0.1063 Core + Tags 0.0610 Core + Reviews+Tags 0.1114 Core + Reviews + Tags + CV 0

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Improving Publication Pipeline with Automated Biological Entity Detection and Validation Service

., & Nugues, P. (2011). Named entity recognition for short text messages. Procedia: Social and Behavioral Sciences 27, 178–187. Ek T. Kirkegaard C. Jonsson H. Nugues P. 2011 Named entity recognition for short text messages Procedia: Social and Behavioral Sciences 27 178–187 Ekbal, A., & Saha, S. (2011). A multi-objective simulated annealing approach for classifier ensemble: Named entity recognition in Indian languages as case studies. Expert Systems with Applications 38(12), 14760–14772. 10.1016/j.eswa.2011.05.004 Ekbal A. Saha S

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Data-driven Pattern Analysis of Acknowledgments in the Biomedical Domain

, similarity was found to exist among the top 44 authors, who all had more than 100 acknowledgments each ( Figure 10c ). Additionally, analyzing smaller numbers above 25 acknowledgments produced result similar to that of Figure 10c , whereas viewing authors with less than 25 acknowledgments produced results similar to that of Figures 10b and F10d . Our dataset contained 65,500 authors, and 99.41% had less than 25 acknowledgments. This suggests that there is a direct relation between the number of acknowledgments an author receives and that author’s similarity with other

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Structural Analysis of Medical-Terminology Hashtag versus Lay-Language Hashtag Tweet Collections: An Information Theoretical Method with Entropy Matrix

communication: A review of research on attention, comprehension, recall, and adherence. Patient Education and Counseling 61(2), 173–190. 10.1016/j.pec.2005.05.004 Houts P. S. Doak C. C. Doak L. G. & Loscalzo M. J. 2006 The role of pictures in improving health communication: A review of research on attention, comprehension, recall, and adherence Patient Education and Counseling 61 2 173 – 190 Johnson, G. (2001, February 27). Claude Shannon, Mathematician, Dies at 84. The New York Times Retrieved from http://www.nytimes.com/2001/02/27/nyregion

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A Clickstream Data Analysis of the Differences between Visiting Behaviors of Desktop and Mobile Users

,880 14.79 97,013 10.29 20,316 61.36 T 177,921 9.90 59,887 6.35 1,393 4.21 C 18,338 1.02 8,460 0.90 1,118 3.38 H 344 0.02 183 0.02 9 0.03 Total 1,797,349 100.00 943,149 100.00 33,111 100.00 4.2 Core Footprint Analysis Different types of pages take different roles during users’ visiting process. Some pages are designed for achieving users’ goals such as acquiring information and completing the task while other pages are aimed to help users arrive at target pages. In this research, users

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