Relevant bibliographies by topics / Meta-aggregation

Academic literature on the topic 'Meta-aggregation'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Meta-aggregation"

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Pearson, Alan. "Meta-aggregation." JBI Database of Systematic Reviews and Implementation Reports 14, no. 12 (December 2016): 2–3. http://dx.doi.org/10.11124/jbisrir-2016-003257.

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Florczak, Kristine L. "Meta-Aggregation: Just What Is It?" Nursing Science Quarterly 32, no. 1 (December 13, 2018): 11. http://dx.doi.org/10.1177/0894318418807933.

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Ansari, Mohd Zeeshan, and M. M. Sufyan Beg. "Improved Fuzzy Rank Aggregation." International Journal of Rough Sets and Data Analysis 5, no. 4 (October 2018): 74–87. http://dx.doi.org/10.4018/ijrsda.2018100105.

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Rank aggregation is applied on the web to build various applications like meta-search engines, consumer reviews classification, and recommender systems. Meta-searching is the generation of a single list from a collection of the results produced by multiple search engines, together using a rank aggregation technique. It is an efficient and cost-effective technique to retrieve quality results from the internet. The quality of results produced by a meta-searching relies upon the efficiency of rank aggregation technique applied. An effective rank aggregation technique assigns the rank to a document that is closest to all its previous rankings. The newly generated list of documents may be evaluated by the measurement of Spearman footrule distance. In this article, various fuzzy logic techniques for rank aggregation are analyzed and further improvements are proposed in Modified Shimura technique. Consequently, two novel OWA operators are suggested for the calculation of membership values of document ranks in a modified Shimura technique. The performance of proposed improvements is evaluated on the Spearman footrule distance along with execution time. The results show that the anticipated improvements exhibit better performance than other fuzzy techniques.
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Wiśniewski, Piotr, and Krzysztof Stencel. "Query Rewriting Based on Meta-Granular Aggregation." Fundamenta Informaticae 135, no. 4 (2014): 537–51. http://dx.doi.org/10.3233/fi-2014-1139.

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Kaufmann, Esther. "Data Aggregation: A Proposed Psychometric IPD Meta-Analysis." Open Journal of Statistics 08, no. 01 (2018): 38–48. http://dx.doi.org/10.4236/ojs.2018.81004.

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Carr J. Smith Thomas J. Steichen Th. "PLATELET AGGREGATION IN CIGARETTE SMOKERS: A META-ANALYSIS." Inhalation Toxicology 10, no. 8 (January 1998): 765–93. http://dx.doi.org/10.1080/089583798197457.

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Hakoyama, Hiroshi, and Yoh Iwasa. "Extinction risk of a meta-population: aggregation approach." Journal of Theoretical Biology 232, no. 2 (January 2005): 203–16. http://dx.doi.org/10.1016/j.jtbi.2004.08.008.

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Thacker, Evan L., and Alberto Ascherio. "Familial aggregation of Parkinson's disease: A meta-analysis." Movement Disorders 23, no. 8 (June 15, 2008): 1174–83. http://dx.doi.org/10.1002/mds.22067.

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Islam, Mahbub Ul, Fahui Jiang, Zichun Guo, and Xinhua Peng. "Does biochar application improve soil aggregation? A meta-analysis." Soil and Tillage Research 209 (May 2021): 104926. http://dx.doi.org/10.1016/j.still.2020.104926.

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Debray, Thomas P. A., Hendrik Koffijberg, Daan Nieboer, Yvonne Vergouwe, Ewout W. Steyerberg, and Karel G. M. Moons. "Meta-analysis and aggregation of multiple published prediction models." Statistics in Medicine 33, no. 14 (January 14, 2014): 2341–62. http://dx.doi.org/10.1002/sim.6080.

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Dissertations / Theses on the topic "Meta-aggregation"

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Lockwood, Craig. "Critiquing the contested nature of aggregation in qualitative evidence synthesis: an examination of dominant views on interpretivism." Thesis, 2011. http://hdl.handle.net/2440/71974.

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This dissertation examines and explores the assumptions and debates associated with qualitative synthesis within the health sciences. My particular area of interest is the complexities arising from various techniques of qualitative synthesis currently emerging in the field of qualitative systematic review. More specifically, in this study I sought to assess the impact of the choice of theoretical constructs, methodological frameworks or methods on the nature of the findings when undertaking a qualitative synthesis. My intention was to examine the debates and conjecture surrounding claims made in relation to meta ethnography and meta aggregation as underpinning approaches to the systematic review of qualitative evidence, as these have attracted interest and polarised the opinions made of their proponents. In order to achieve this a multi phase study was undertaken, where phase one included the identification of a high quality, published meta ethnographic review and the conduct of a comparator meta aggregative review. Phase two consisted of a comparison between the two reviews, with each phase necessarily consisting of sections that worked to clarify the steps and stages taken in the conduct and reporting of the research that formed the basis of this thesis. The primary results of interest from this process were not the findings of the meta ethnographic review compared with the meta aggregative review, but the subsequent analysis of where and how differences originated. Interpretivism is the catch phrase of meta ethnography, yet it is by no means clear what is meant either by the originators; or by subsequent reviewers who have used the methodology but not explicated its philosophic foundations. Interpretivism is not a unified theory, it is instead a broad church; inclusive of many philosophical perspectives, specifically hermeneutics, phenomenology and symbolic interactionism. The particular claims to interpretivism for ethnographic reviews was examined and found to be a superficial and inadequate representation of the methodology. Specifically, hermeneutic phenomenology has been found to be ontologically and epistemologically congruent with the methodology and methods of meta ethnography. It also became evident that the methods-centric focus of meta aggregation has limited wider understanding of the methodology, leading to an incorrect association with integration. This study maintains that the interpretive foundations of aggregative synthesis are found in Husserlian Transcendental Phenomenology. This study suggests that the approach and purpose are the first two key points of decisionmaking. Therefore, reviewers interested in undertaking qualitative synthesis should first consider what approach is a good fit with their purposes before deciding upon a methodology. Within the ‘interpretive philosophic’ perspective, the two core philosophies [of hermeneutic phenomenology (with fusion of horizons), and transcendental phenomenology] are where we must look to understand both the differences between meta aggregation and meta ethnography and the strengths and weaknesses of each approach.
Thesis (Ph.D.) -- University of Adelaide, The Joanna Briggs Institute, 2011
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Tufanaru, Catalin. "Theoretical foundations of meta-aggregation: insights from Husserlian phenomenology and American pragmatism." Thesis, 2016. http://hdl.handle.net/2440/98255.

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The objectives of the thesis were: 1) to examine the Husserlian phenomenology and American pragmatism philosophical literature and to clarify the validity of the claims that the Joanna Briggs Institute’s meta-aggregation is founded on Husserlian transcendental phenomenology and American pragmatism; 2) to develop an explicit coherent theoretical foundation for the Joanna Briggs Institute’s approach to the meta-aggregation of qualitative studies based on insights from Husserlian phenomenology and American pragmatism. The philosophical/theoretical perspective of the thesis was critical theory with a special focus on the philosophical works of Jurgen Habermas. Philosophical inquiry was used as methodology. Data collection involved critical reading of the Husserlian phenomenology and American pragmatism philosophical literature, the Joanna Briggs Institute’s guidance on meta-aggregation and the international qualitative research literature regarding meta-synthesis of qualitative evidence - specifically meta-aggregation. Data analysis and synthesis used an integrative synthesis of ideas and theoretical framework development. Narrative (text) and graphical/visual approaches (tables; idea maps; diagrams) were used for the presentation of the results. Chapter I of the thesis presents an introduction to the role of qualitative research and systematic reviews of qualitative evidence in evidence-based health care. Chapter II provides the details of the research questions/objectives, methodology, and methods. Chapter III of the thesis examines the Joanna Briggs Institute’s meta-aggregation approach for synthesis of qualitative evidence. Chapter IV explores essential ideas of Husserlian phenomenology. Chapter V examines critically the validity of the claims that the Joanna Briggs Institute’s meta-aggregation is founded on Husserlian transcendental phenomenology. Chapter VI explores fundamental ideas of American pragmatism as reflected in the works of Charles S. Peirce, William James, and John Dewey. Chapter VII examines critically the validity of the claims that the Joanna Briggs Institute’s meta-aggregation is founded on American pragmatism. Chapter VIII provides an original explicit theoretical foundation for the Joanna Briggs Institute’s meta-aggregation based on new insights from Husserlian phenomenology and American pragmatism.
Thesis (Ph.D.) -- University of Adelaide, School of Public Health, 2016.
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Aljafary, Michelle. "Accounting for potential nonlinearity between catch and effort using meta-analysis and applying GLM and GLMM to fishing data from deployments of fixed and mobile gear." 2016. http://hdl.handle.net/1993/31208.

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My thesis examines nonlinearity between catch and effort. I use a meta-analysis of published literature and generalized linear mixed-effects models (GLMM) on both fixed and mobile gear fisheries of Atlantic Canada. The meta-analysis examines the proportionality of catch to effort using the slope of the reduced major axis (RMA) log-log regression, which accounts for “errors-in-variables”. The GLMMs explored proportionality while accounting for variation among fishing vessels. Both analyses found evidence for disproportionality between catch and effort. Catch that increases disproportionally to effort could result from either facilitation or recruitment of effort into the fishery. Catch increases that are less than proportional are expected from competitive interactions among fishers or gear saturation. The GLMM also revealed that the level of aggregation (by set, trip, monthly, or annually) can affect the apparent proportionality between catch and effort. In general, catch and effort should not be considered to be proportional.
May 2016
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Book chapters on the topic "Meta-aggregation"

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Kilinc, Berna. "Meta-analysis as Judgment Aggregation." In EPSA Philosophy of Science: Amsterdam 2009, 123–35. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-2404-4_12.

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Hoon, Gan Keng, Saravadee Sae Tan, Chan Huah Yong, and Tang Enya Kong. "Rank Aggregation Model for Meta Search." In Intelligent Information Processing II, 325–39. Boston, MA: Springer US, 2005. http://dx.doi.org/10.1007/0-387-23152-8_42.

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Feng, Junliang, Junzhong Gu, and Zili Zhou. "An Improved Ranking Aggregation Method for Meta-Search Engine." In Lecture Notes in Electrical Engineering, 193–200. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6738-6_25.

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Fang, Qizhi, Han Xiao, and Shanfeng Zhu. "Top-d Rank Aggregation in Web Meta-search Engine." In Frontiers in Algorithmics, 35–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14553-7_6.

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Škrlj, Blaž, Andraž Repar, and Senja Pollak. "RaKUn: Rank-based Keyword Extraction via Unsupervised Learning and Meta Vertex Aggregation." In Statistical Language and Speech Processing, 311–23. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31372-2_26.

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Võsa, Urmo, Raivo Kolde, Jaak Vilo, Andres Metspalu, and Tarmo Annilo. "Comprehensive Meta-analysis of MicroRNA Expression Using a Robust Rank Aggregation Approach." In RNA Mapping, 361–73. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1062-5_28.

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Gaharwar, R. D., and D. B. Shah. "A Novel Meta Crawling Algorithm for Terrorist Network Knowledge Aggregation from the Internet." In Smart Computing and Informatics, 375–83. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5544-7_36.

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Stuckenschmidt, Heiner, and Frank van Harmelen. "Knowledge-Based Validation, Aggregation, and Visualization of Meta-data: Analyzing a Web-Based Information System." In Web Intelligence: Research and Development, 217–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45490-x_26.

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Hannes, Karin, and Alan Pearson. "Obstacles to the Implementation of Evidence-Based Practice in Belgium: A Worked Example of Meta-Aggregation." In Synthesizing Qualitative Research, 21–39. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119959847.ch2.

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Sutterlütti, Simon, and Stefan Meretz. "Commonism." In Make Capitalism History, 141–89. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-14645-9_6.

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AbstractCommonism is an alternative to market economy and real socialism because it goes beyond their common basis of wage labour, money and private or state property. Products are not produced in the form of commodities that are sold for money, but as commons for the direct satisfaction of needs. The chapter discusses common questions such as “Who cares about waste disposal?” and focuses on the question of coordination and mediation through commoning. Stigmergy, a signal-based coordination mechanism that communicates needs, can be used to create ex-ante planning of re/production. Conflicts are an important part of a free society and are not resolved by a central institution as envisioned by the followers of council theory, but in many places in a polycentric coordination mechanism. This polycentric coordination allows for planning and aggregation as long as the needs of the (care-) workers involved and their (commons-) enterprises are included. It builds on meta-structures providing information such as CO2 emissions or expected shortages or helps negotiate conflicts. It creates a society that can overcome ethics as the basis of solidarity and create a logic of inclusion that makes the inclusion of others the best selfish option.
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Conference papers on the topic "Meta-aggregation"

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Lam, Ka Wai, and Chi Ho Leung. "Rank aggregation for meta-search engines." In the 13th international World Wide Web conference. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/1013367.1013487.

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Zhao, He, Lan Du, Guanfeng Liu, and Wray Buntine. "Leveraging Meta Information in Short Text Aggregation." In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/p19-1396.

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Gordevicius, Juozas, Francisco J. Estrada, Hyun Chul Lee, Periklis Andritsos, and Johann Gamper. "Ranking of evolving stories through meta-aggregation." In the 19th ACM international conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1871437.1871761.

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Smetannikov, Ivan, Alexander Deyneka, and Andrey Filchenkov. "Meta Learning Application in Rank Aggregation Feature Selection." In 2016 3rd International Conference on Soft Computing & Machine Intelligence (ISCMI). IEEE, 2016. http://dx.doi.org/10.1109/iscmi.2016.55.

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Boushih, Beya, and Nahla Ben Amor. "Rank aggregation using active learning in meta-searching." In 2014 Second World Conference on Complex Systems (WCCS). IEEE, 2014. http://dx.doi.org/10.1109/icocs.2014.7060911.

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Meng, Dan, Hongyu Li, Fan Zhu, and Xiaolin Li. "FedMONN: Meta Operation Neural Network for Secure Federated Aggregation." In 2020 IEEE 22nd International Conference on High Performance Computing and Communications; IEEE 18th International Conference on Smart City; IEEE 6th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE, 2020. http://dx.doi.org/10.1109/hpcc-smartcity-dss50907.2020.00073.

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Kolmykov, Semyon K., Yury V. Kondrakhin, Ruslan N. Sharipov, Ivan S. Yevshi, Anna S. Ryabova, and Fedor A. Kolpakov. "Meta-analysis of ChIP-seq Datasets Through the Rank Aggregation Approach." In 2020 Cognitive Sciences, Genomics and Bioinformatics (CSGB). IEEE, 2020. http://dx.doi.org/10.1109/csgb51356.2020.9214614.

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Wagner, Christian, and Derek T. Anderson. "Extracting meta-measures from data for fuzzy aggregation of crowd sourced information." In 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2012. http://dx.doi.org/10.1109/fuzz-ieee.2012.6251281.

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Yan, Liqi, Dongfang Liu, Yaoxian Song, and Changbin Yu. "Multimodal Aggregation Approach for Memory Vision-Voice Indoor Navigation with Meta-Learning." In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2020. http://dx.doi.org/10.1109/iros45743.2020.9341398.

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Huifang Chen, H. Mineno, and T. Mizuno. "A Meta-Data-Based Data Aggregation Scheme in Clustering Wireless Sensor Networks." In 7th International Conference on Mobile Data Management (MDM'06). IEEE, 2006. http://dx.doi.org/10.1109/mdm.2006.7.

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