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Dissertations / Theses on the topic 'Ranking data'

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1

Vanichbuncha, Tita. "Modelling partial ranking data." Thesis, University of Kent, 2017. https://kar.kent.ac.uk/66664/.

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Ranking is one of the most used methods in not only in statistics but also in other field such as computer science and psychology. This method helps us determine order of objects in a group such as preference of animal species, and has very broad applications. However, when the number of objects to be ranked becomes larger, the uncertainty of the ranking typically increases since it is harder for the ranker to express their preference accurately. This leads to the idea of partial ranking which allows rankers to rank just a subset of objects in the group and then combine their results together
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2

Lo, Siu-ming, and 盧小皿. "Factor analysis for ranking data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B30162464.

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Lo, Siu-ming. "Factor analysis for ranking data /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20792967.

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4

林漢坤 and Hon-kwan Lam. "Analysis of ranking data with covariates." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31215476.

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Qi, Fang, and 齊放. "Some topics in modeling ranking data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/209210.

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Many applications of analysis of ranking data arise from different fields of study, such as psychology, economics, and politics. Over the past decade, many ranking data models have been proposed. AdaBoost is proved to be a very successful technique to generate a stronger classifier from weak ones; it can be viewed as a forward stagewise additive modeling using the exponential loss function. Motivated by this, a new AdaBoost algorithm is developed for ranking data. Taking into consideration the ordinal structure of the ranking data, I propose measures based on the Spearman/Kendall distance to e
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Lam, Hon-kwan. "Analysis of ranking data with covariates /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B19943313.

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7

Sun, Mingxuan. "Visualizing and modeling partial incomplete ranking data." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/45793.

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Analyzing ranking data is an essential component in a wide range of important applications including web-search and recommendation systems. Rankings are difficult to visualize or model due to the computational difficulties associated with the large number of items. On the other hand, partial or incomplete rankings induce more difficulties since approaches that adapt well to typical types of rankings cannot apply generally to all types. While analyzing ranking data has a long history in statistics, construction of an efficient framework to analyze incomplete ranking data (with or without ties)
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8

Lee, Hong, and 李匡. "Model-based decision trees for ranking data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B45149707.

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9

Korba, Anna. "Learning from ranking data : theory and methods." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLT009/document.

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Les données de classement, c.à. d. des listes ordonnées d'objets, apparaissent naturellement dans une grande variété de situations, notamment lorsque les données proviennent d’activités humaines (bulletins de vote d'élections, enquêtes d'opinion, résultats de compétitions) ou dans des applications modernes du traitement de données (moteurs de recherche, systèmes de recommendation). La conception d'algorithmes d'apprentissage automatique, adaptés à ces données, est donc cruciale. Cependant, en raison de l’absence de structure vectorielle de l’espace des classements et de sa cardinalité explosiv
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Gregory, Machon. "Shape identication and ranking in temporal data sets." College Park, Md.: University of Maryland, 2009. http://hdl.handle.net/1903/9319.

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Thesis (M.S.) -- University of Maryland, College Park, 2009.<br>Thesis research directed by: Dept. of Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Cai, Yilun, and 蔡奕倫. "Ranking and similarity queries on complex data types." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/209507.

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Ranking queries and similarity queries are elementary operations with many important applications. There are lots of research works investigating efficient evaluation of various ranking and similarity queries in databases over the past few decades. In this thesis, ranking and similarity queries on three interesting complex data types are studied, namely, multidimensional cube, object summary and tree. Efficient and effective solutions are proposed to solve their related applications. First, the evaluation of ranking queries on multidimensional cubes is studied. In exploratory data analysis,
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12

徐兆邦 and Shiu-bong Chui. "Estimation methods for rank data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31222535.

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Chui, Shiu-bong. "Estimation methods for rank data /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B21415110.

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14

Malone, Gwendolyn Joy. "Ranking and Selection Procedures for Bernoulli and Multinomial Data." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/7603.

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Ranking and Selection procedures have been designed to select the best system from a number of alternatives, where the best system is defined by the given problem. The primary focus of this thesis is on experiments where the data are from simulated systems. In simulation ranking and selection procedures, four classes of comparison problems are typically encountered. We focus on two of them: Bernoulli and multinomial selection. Therefore, we wish to select the best system from a number of simulated alternatives where the best system is defined as either the one with the largest probability of s
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15

陳潔妍 and Kit-yin Chan. "Bayesian analysis of wandering vector models for ranking data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31214939.

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16

Chen, Li. "Ranking-Based Methods for Gene Selection in Microarray Data." Scholar Commons, 2006. http://scholarcommons.usf.edu/etd/3888.

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DNA microarrays have been used for the purpose of monitoring expression levels of thousands of genes simultaneously and identifying those genes that are differentially expressed. One of the major goals of microarray data analysis is the detection of differentially expressed genes across two kinds of tissue samples or samples obtained under two experimental conditions. A large number of gene detection methods have been developed and most of them are based on statistical analysis. However the statistical analysis methods have the limitations due to the small sample size and unknown distribution
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Chan, Kit-yin. "Bayesian analysis of wandering vector models for ranking data /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B19977025.

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18

Trailović, Lidija. "Ranking and optimization of target tracking algorithms." online access from Digital Dissertation Consortium access full-text, 2002. http://libweb.cityu.edu.hk/cgi-bin/er/db/ddcdiss.pl?3074810.

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19

Herzig, Daniel Markus [Verfasser]. "Ranking for Web Data Search Using On-The-Fly Data Integration / Daniel Markus Herzig." Karlsruhe : KIT Scientific Publishing, 2014. http://www.ksp.kit.edu.

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20

Hwang, Heasoo. "Dynamic link-based ranking over large-scale graph-structured data." Diss., [La Jolla] : University of California, San Diego, 2010. http://wwwlib.umi.com/cr/ucsd/fullcit?p3404629.

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Thesis (Ph. D.)--University of California, San Diego, 2010.<br>Title from first page of PDF file (viewed June 11, 2010). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (leaves 93-97).
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21

Alsarem, Mazen. "Semantic snippets via query-biased ranking of linked data entities." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI044/document.

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Dans cette thèse, nous introduisons un nouvel artefact interactif pour le SERP: le "Snippet sémantique". Les snippets sémantiques s'appuient sur la coexistence des deux Webs pour faciliter le transfert des connaissances aux utilisateurs grâce a une contextualisation sémantique du besoin d'information de l'utilisateur. Ils font apparaître les relations entre le besoin d'information et les entités les plus pertinentes présentes dans la page Web<br>In this thesis, we introduce a new interactive artifact for the SERP: the "Semantic Snippet". Semantic Snippets rely on the coexistence of the two web
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Stojkovic, Ivan. "Functional Norm Regularization for Margin-Based Ranking on Temporal Data." Diss., Temple University Libraries, 2018. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/522550.

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Computer and Information Science<br>Ph.D.<br>Quantifying the properties of interest is an important problem in many domains, e.g., assessing the condition of a patient, estimating the risk of an investment or relevance of the search result. However, the properties of interest are often latent and hard to assess directly, making it difficult to obtain classification or regression labels, which are needed to learn a predictive models from observable features. In such cases, it is typically much easier to obtain relative comparison of two instances, i.e. to assess which one is more intense (with
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23

BUSCEMI, Simona. "Ensemble methods for ranking data with and without position weights." Doctoral thesis, Università degli Studi di Palermo, 2020. http://hdl.handle.net/10447/395373.

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The main goal of this Thesis is to build suitable Ensemble Methods for ranking data with weights assigned to the items’positions, in the cases of rankings with and without ties. The Thesis begins with the definition of a new rank correlation coefficient, able to take into account the importance of items’position. Inspired by the rank correlation coefficient, τ x , proposed by Emond and Mason (2002) for unweighted rankings and the weighted Kemeny distance proposed by García-Lapresta and Pérez-Román (2010), this work proposes τ x w , a new rank correlation coefficient corresponding to the weighte
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Eryilmaz, Utkan. "Hybrid Ranking Approaches Based On Data Envelopment Analysis And Outranking Relations." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/3/12607999/index.pdf.

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In this study two different hybrid ranking approaches based on data envelopment analysis and outranking relations for ranking alternatives are proposed. Outranking relations are widely used in Multicriteria Decision Making (MCDM) for ranking the alternatives and appropriate in situations when we have limited information on the preference structure of the decision maker. Yet to apply these methods DM should provide exact values for method parameters (weights, thresholds etc.) as well as basic information such as alternative scores. DEA is used for classification of decision making units accordi
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Lee, Chun-fan, and 李俊帆. "Fitting factor models for ranking data using efficient EM-type algorithms." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B31227557.

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26

Wooton, Sharyl Stasser. "DATA ENVELOPMENT ANALYSIS: A TOOL FOR SECONDARY EDUCATION RANKING AND BENCHMARKING." Oxford, Ohio : Miami University, 2003. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=miami1050604854.

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Thesis (M.S.A.)--Miami University, Dept. of Computer Science and Systems Analysis, 2003.<br>Title from first page of PDF document. Document formatted into pages; contains iii, 36 p. Includes bibliographical references (p. 35-36).
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Jiang, Chunyu. "DATA MINING AND ANALYSIS ON MULTIPLE TIME SERIES OBJECT DATA." Wright State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=wright1177959264.

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28

Sutanto, Taufik Edy. "Scalable fine-grained document clustering via ranking." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/107459/1/Taufik%20Edy_Sutanto_Thesis.pdf.

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Dealing with big data, this thesis presents a novel and effective approach of scalable document clustering via ranking. The proposed clustering methods address the high-dimensionality problem in clustering analysis by introducing effective and computationally efficient cluster representations. The clustering via ranking approach is applicable to semi-supervised and unsupervised clustering problems. The proposed methods are applicable to static data as well as streaming data. The methods have been successfully tested with big social media data providing interesting insight.
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Murugesan, Keerthiram. "CLUSTER-BASED TERM WEIGHTING AND DOCUMENT RANKING MODELS." UKnowledge, 2011. http://uknowledge.uky.edu/gradschool_theses/651.

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A term weighting scheme measures the importance of a term in a collection. A document ranking model uses these term weights to find the rank or score of a document in a collection. We present a series of cluster-based term weighting and document ranking models based on the TF-IDF and Okapi BM25 models. These term weighting and document ranking models update the inter-cluster and intra-cluster frequency components based on the generated clusters. These inter-cluster and intra-cluster frequency components are used for weighting the importance of a term in addition to the term and document freque
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30

Trouet, Valerie, Jan Esper, Paul J. Krusic, et al. "Ranking of tree-ring based temperature reconstructions of the past millennium." PERGAMON-ELSEVIER SCIENCE LTD, 2016. http://hdl.handle.net/10150/621352.

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Tree-ring chronologies are widely used to reconstruct high-to low-frequency variations in growing season temperatures over centuries to millennia. The relevance of these timeseries in large-scale climate reconstructions is often determined by the strength of their correlation against instrumental temperature data. However, this single criterion ignores several important quantitative and qualitative characteristics of tree-ring chronologies. Those characteristics are (i) data homogeneity, (ii) sample replication, (iii) growth coherence, (iv) chronology development, and (v) climate signal includ
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Alsaleh, Slah. "Recommending people in social networks using data mining." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/61736/1/Slah_Alsaleh_Thesis.pdf.

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This thesis improves the process of recommending people to people in social networks using new clustering algorithms and ranking methods. The proposed system and methods are evaluated on the data collected from a real life social network. The empirical analysis of this research confirms that the proposed system and methods achieved improvements in the accuracy and efficiency of matching and recommending people, and overcome some of the problems that social matching systems usually suffer.
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Alexandridis, Roxana Antoanela. "Minimum disparity inference for discrete ranked set sampling data." Connect to resource, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1126033164.

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Thesis (Ph. D.)--Ohio State University, 2005.<br>Title from first page of PDF file. Document formatted into pages; contains xi, 124 p.; also includes graphics. Includes bibliographical references (p. 121-124). Available online via OhioLINK's ETD Center
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Tuncer, Ceren. "A Dea-based Approach To Ranking Multi-criteria Alternatives." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607476/index.pdf.

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ABSTRACT A DEA-BASED APPROACH TO RANKING MULTI-CRITERIA ALTERNATIVES Tuncer, Ceren M.Sc., Department of Industrial Engineering Supervisor: Prof. Dr. Murat K&ouml<br>ksalan August 2006, 88 pages This thesis addresses the problem of ranking multi-criteria alternatives. A Data Envelopment Analysis (DEA)-based approach, the Method of the Area of the Efficiency Score Graph (AES) is proposed. Rather than assessing the alternatives with respect to the fixed original alternative set as done in the existing DEA-based ranking methods, AES considers the change in the efficiency scores of the alt
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Smart, Edward. "Detecting abnormalities in aircraft flight data and ranking their impact on the flight." Thesis, University of Portsmouth, 2011. https://researchportal.port.ac.uk/portal/en/theses/detecting-abnormalities-in-aircraft-flight-data-and-ranking-their-impact-on-the-flight(d9678b70-41e6-459a-82fb-ba2d12a0f971).html.

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To the best of the author’s knowledge, this is one of the first times that a large quantity of flight data has been studied in order to improve safety. A two phase novelty detection approach to locating abnormalities in the descent phase of aircraft flight data is presented. It has the ability to model normal time series data by analysing snapshots at chosen heights in the descent, weight individual abnormalities and quantitatively assess the overall level of abnormality of a flight during the descent. The approach expands on a recommendation by the UK Air Accident Investigation Branch to the
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Varadarajan, Ramakrishna R. "Ranked Search on Data Graphs." FIU Digital Commons, 2009. http://digitalcommons.fiu.edu/etd/220.

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Graph-structured databases are widely prevalent, and the problem of effective search and retrieval from such graphs has been receiving much attention recently. For example, the Web can be naturally viewed as a graph. Likewise, a relational database can be viewed as a graph where tuples are modeled as vertices connected via foreign-key relationships. Keyword search querying has emerged as one of the most effective paradigms for information discovery, especially over HTML documents in the World Wide Web. One of the key advantages of keyword search querying is its simplicity – users do not have t
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Paulsson, Anton. "Using clickthrough data to optimize search result ranking : An evaluation of clickthrough data in terms of relevancy and efficiency." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-14098.

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Search engines are in a constant need for improvements as the rapid growth of information is affecting the search engines ability to return documents with high relevance. Search results are being lost in between pages and the search algorithms are being exploited to gain a higher ranking on the documents. This study attempts to minimize those two issues, as well as increasing the relevancy of search results by usage of clickthrough data to add another layer of weighting the search results. Results from the evaluation indicate that clickthrough data in fact can be used to gain more relevant sea
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Romanenkov, Yuri, Viktor Kosenko, Olena Lobach, Evgen Grinchenko, and Marina Grinchenko. "The method for ranking quasi-optimal alternatives in interval game models against nature." Thesis, National Technical University "Kharkiv Polytechnic Institute", 2019. http://repository.kpi.kharkov.ua/handle/KhPI-Press/47215.

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The task of selecting the optimal strategy in the interval game with nature is considered; in particular, the situation when in the interactive dialogue of an analyst and decision support system there are cases of objective ambiguity caused, on the one hand, by interval uncertainty of data, and on the other hand – by the chosen model of the task formalization. The method for ranking quasioptimal alternatives in interval game models against nature is proposed, which enables comparing interval alternatives in cases of classical interval ambiguity. In this case, the function of the analyst prefer
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Leung, Hiu-lan, and 梁曉蘭. "Wandering ideal point models for single or multi-attribute ranking data: a Bayesian approach." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B29552357.

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Ibstedt, Julia, Elsa Rådahl, Erik Turesson, and Voorde Magdalena vande. "Application and Further Development of TrueSkill™ Ranking in Sports." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-384863.

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The aim of this study was to explore the ranking model TrueSkill™ developed by Microsoft, applying it on various sports and constructing extensions to the model. Two different inference methods for TrueSkill was constructed using Gibbs sampling and message passing. Additionally, the sequential method using Gibbs sampling was successfully extended into a batch method, in order to eliminate game order dependency and creating a fairer, although computationally heavier, ranking system. All methods were further implemented with extensions for taking home team advantage, score difference and finally
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40

Alsarem, Mazen [Verfasser], and Harald [Akademischer Betreuer] Kosch. "Semantic Snippets via Query-Biased Ranking of Linked Data Entities / Mazen Alsarem ; Betreuer: Harald Kosch." Passau : Universität Passau, 2017. http://d-nb.info/1124229639/34.

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Triperina, Evangelia. "Visual interactive knowledge management for multicriteria decision making and ranking in linked open data environments." Thesis, Limoges, 2020. http://www.theses.fr/2020LIMO0010.

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Le doctorat impliqués la recherche dans le domaine des représentations visuelles assistées par des technologies sémantiques et des ontologies afin de soutenir les décisions et les procédures d'élaboration des politiques, dans le cadre de la recherche et des systèmes d'information académique. Les visualisations seront également prises en charge par l'exploration de données et les processus d'extraction de connaissances dans l'environnement de données liées. Pour élaborer, les techniques d'analyse visuelle seront utilisées pour l'organisation des visualisations afin de présenter l'information de
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Lee, Myunghyun. "Measuring and Ranking Efficiency of Major Airports in the United States Using Data Envelopment Analysis." Master's thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/46532.

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An airport is an important piece of infrastructure in air transportation system. This project focuses on measuring and ranking the efficiency of airports in the United States using the basic DEA, Ranking DEA, Goal programming and DEA and TOPSIS. In general, airport authorities of relatively inefficient airports are trying to benchmark the operational strategies of efficient airports. This project focuses on evaluating hub airports in the United States. ATL, LAX, and MEM airports are relatively efficient among forty four hub airports in the United States based on the performances and airpo
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Theobald, Martin. "TopX efficient and versatile top-k query processing for text, structured, and semistructured data." Saarbrücken VDM Verlag Dr. Müller, 2006. http://d-nb.info/99139089X/04.

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Mukherjee, Somshree. "Ranking System for IoT Industry Platform." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-204571.

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The Internet of Things (IoT) has seen a huge growth spurt in the last few years which has resulted in the need for more standardised IoT technology. Because of this, numerous IoT platforms have sprung up that offer a variety of features and use different technologies which may not necessarily be compliant with each other or with other technologies. Companies that wish to enter theIoT market are in constant need to find the most suitable IoT platform for their business and have a certain set of requirements that need to be fulfilled by the IoT platforms in order for the application to be fully
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Chen, Haiying. "Ranked set sampling for binary and ordered categorical variables with applications in health survey data." Connect to this title online, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1092770729.

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Thesis (Ph. D.)--Ohio State University, 2004.<br>Title from first page of PDF file. Document formatted into pages; contains xiii, 109 p.; also includes graphics Includes bibliographical references (p. 99-102). Available online via OhioLINK's ETD Center
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Chuck, Lisa. "A PREDICTIVE MODEL FOR BENCHMARKING ACADEMIC PROGRAMS (PBAP)USING U.S. NEWS RANKING DATA FOR ENGINEERING COLLEGES OFFERING GRADU." Doctoral diss., University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2397.

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Improving national ranking is an increasingly important issue for university administrators. While research has been conducted on performance measures in higher education, research designs have lacked a predictive quality. Studies on the U.S. News college rankings have provided insight into the methodology; however, none of them have provided a model to predict what change in variable values would likely cause an institution to improve its standing in the rankings. The purpose of this study was to develop a predictive model for benchmarking academic programs (pBAP) for engineering colleges. Th
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Marby, Josephine, and Ying Chen. "Ranking risks and opportunities of African cities : - A data-driven model to support MNE’s FDI strategies." Thesis, KTH, Industriell Management, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210315.

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The purpose of this paper is to build a model that incorporates current data of Africa, both regarding risks and opportunities into a strategic framework that should enable a more informed foreign direct investment decision for multinational enterprises (MNEs). The parameters used in the model were carefully chosen as determinants to foreign direct investment (FDI) based on extensive literature reviews. The model currently covers 101 major cities in 40 African countries. The model calculates and ranks indexes of African cities in terms of prospective investment opportunities. It is a general m
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MARBY, JOSEPHINE, and YING CHEN. "Ranking risks and opportunities of African cities : A data-driven model to support MNE’s FDI strategies." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-223918.

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Chuck, Lisa Gay Marie. "A Predictive Model for Benchmarking Academic Programs (pBAP) Using U.S. News Ranking Data for Engineering Colleges Offering Graduate Programs." Doctoral diss., University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2396.

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Improving national ranking is an increasingly important issue for university administrators. While research has been conducted on performance measures in higher education, research designs have lacked a predictive quality. Studies on the U.S. News college rankings have provided insight into the methodology; however, none of them have provided a model to predict what change in variable values would likely cause an institution to improve its standing in the rankings. The purpose of this study was to develop a predictive model for benchmarking academic programs (pBAP) for engineering colleges. Th
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50

Snedden, Larry D. "Improving Search Ranking Using a Composite Scoring Approach." UNF Digital Commons, 2017. https://digitalcommons.unf.edu/etd/776.

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In this thesis, the improvement to relevance in computerized search results is studied. Information search tools return ranked lists of documents ordered by the relevance of the documents to the user supplied search. Using a small number of words and phrases to represent complex ideas and concepts causes user search queries to be information sparse. This sparsity challenges search tools to locate relevant documents for users. A review of the challenges to information searches helps to identify the problems and offer suggestions in improving current information search tools. Using the suggestio
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