Relevant bibliographies by topics / Incomplete rankings

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  2. Dissertations / Theses
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Academic literature on the topic 'Incomplete rankings'

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Published: 25 May 2024

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Journal articles on the topic "Incomplete rankings"

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Gyarmati, László, Éva Orbán-Mihálykó, Csaba Mihálykó, and Ágnes Vathy-Fogarassy. "Aggregated Rankings of Top Leagues’ Football Teams: Application and Comparison of Different Ranking Methods." Applied Sciences 13, no. 7 (April 3, 2023): 4556. http://dx.doi.org/10.3390/app13074556.

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In this study, the effectiveness and characteristics of three ranking methods were investigated based on their performance in ranking European football teams. The investigated methods were the Thurstone method with ties, the analytic hierarchy process with logarithmic least squares method, and the RankNet neural network. The methods were analyzed in both complete and incomplete comparison tasks. The ranking based on complete comparison was performed on match results of national leagues, where each team had match results against all the other teams. In the incomplete comparison case, in addition to the national league results, only a few match results from international cups were available to determine the aggregated ranking of the teams playing in the top five European leagues. The rankings produced by the ranking methods were compared with each other, with the official national rankings, and with the UEFA club coefficient rankings. In addition, the correlation between the aggregated rankings and the Transfermarkt financial ranking was also examined for the sake of interest.
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Moreno-Centeno, Erick, and Adolfo R. Escobedo. "Axiomatic aggregation of incomplete rankings." IIE Transactions 48, no. 6 (December 2, 2015): 475–88. http://dx.doi.org/10.1080/0740817x.2015.1109737.

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Pedroche, Francisco, and J. Alberto Conejero. "Corrected Evolutive Kendall’s τ Coefficients for Incomplete Rankings with Ties: Application to Case of Spotify Lists." Mathematics 8, no. 10 (October 18, 2020): 1828. http://dx.doi.org/10.3390/math8101828.

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Mathematical analysis of rankings is essential for a wide range of scientific, public, and industrial applications (e.g., group decision-making, organizational methods, R&D sponsorship, recommender systems, voter systems, sports competitions, grant proposals rankings, web searchers, Internet streaming-on-demand media providers, etc.). Recently, some methods for incomplete aggregate rankings (rankings in which not all the elements are ranked) with ties, based on the classic Kendall’s tau coefficient, have been presented. We are interested in ordinal rankings (that is, we can order the elements to be the first, the second, etc.) allowing ties between the elements (e.g., two elements may be in the first position). We extend a previous coefficient for comparing a series of complete rankings with ties to two new coefficients for comparing a series of incomplete rankings with ties. We make use of the newest definitions of Kendall’s tau extensions. We also offer a theoretical result to interpret these coefficients in terms of the type of interactions that the elements of two consecutive rankings may show (e.g., they preserve their positions, cross their positions, and they are tied in one ranking but untied in the other ranking, etc.). We give some small examples to illustrate all the newly presented parameters and coefficients. We also apply our coefficients to compare some series of Spotify charts, both Top 200 and Viral 50, showing the applicability and utility of the proposed measures.
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Alvo, M., and P. Cabilio. "Analysis of incomplete blocks for rankings." Statistics & Probability Letters 29, no. 2 (August 1996): 177–84. http://dx.doi.org/10.1016/0167-7152(95)00171-9.

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CHEN, TING-YU. "NONLINEAR ASSIGNMENT-BASED METHODS FOR INTERVAL-VALUED INTUITIONISTIC FUZZY MULTI-CRITERIA DECISION ANALYSIS WITH INCOMPLETE PREFERENCE INFORMATION." International Journal of Information Technology & Decision Making 11, no. 04 (July 2012): 821–55. http://dx.doi.org/10.1142/s0219622012500228.

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In the context of interval-valued intuitionistic fuzzy sets, this paper develops nonlinear assignment-based methods to manage imprecise and uncertain subjective ratings under incomplete preference structures and thereby determines the optimal ranking order of the alternatives for multiple criteria decision analysis. By comparing each interval-valued intuitionistic fuzzy number's score function, accuracy function, membership uncertainty index, and hesitation uncertainty index, a ranking procedure is employed to identify criterion-wise preference of alternatives. Based on the criterion-wise rankings and a set of known but incomplete information about criterion weights, a nonlinear assignment model is constructed to estimate criterion weights and to order the priority of various alternatives. Considering multiple criteria evaluation problems with preference conflict about criterion importance, an integrated nonlinear programming model is further established with regard to incomplete and inconsistent weight information. These proposed nonlinear assignment-based methods can obtain an aggregate ranking that effectively combines the relative performance of each alternative in each criterion. In addition, this overall ranking most closely agrees with the criterion-wise rankings. Finally, the feasibility of the proposed method is illustrated by a practical example of selecting a suitable bridge construction method.
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Baklouti, Amir. "Multiple-Attribute Decision Making Based on the Probabilistic Dominance Relationship with Fuzzy Algebras." Symmetry 15, no. 6 (June 2, 2023): 1188. http://dx.doi.org/10.3390/sym15061188.

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In multiple-attribute decision-making (MADM) problems, ranking the alternatives is an important step for making the best decision. Intuitionistic fuzzy numbers (IFNs) are a powerful tool for expressing uncertainty and vagueness in MADM problems. However, existing ranking methods for IFNs do not consider the probabilistic dominance relationship between alternatives, which can lead to inconsistent and inaccurate rankings. In this paper, we propose a new ranking method for IFNs based on the probabilistic dominance relationship and fuzzy algebras. The proposed method is able to handle incomplete and uncertain information and can generate consistent and accurate rankings.
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Alvo, M., and P. Cabilio. "On the Balanced Incomplete Block Design for Rankings." Annals of Statistics 19, no. 3 (September 1991): 1597–613. http://dx.doi.org/10.1214/aos/1176348264.

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R. Rink, David. "Balanced incomplete block designs: selected business-related applications and usage caveats." Innovative Marketing 12, no. 1 (April 27, 2016): 15–28. http://dx.doi.org/10.21511/im.12(1).2016.02.

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Whenever respondents must rank-order a large number of items and/or the reliability of their rankings may be questionable, balanced incomplete block designs (BIBDs) represent a more effective means for doing so than either complete rankings or paired comparisons for business and marketing researchers. By providing a type of balancing and replication across items and respondents, BIBDs significantly reduce the number of subjective evaluations each individual must make. But, at the same time, BIBDs allow a limited number of respondents as a group to rank many items. This balancing and replication in BIBDs also reduces standard deviation, which increases the precision of a study. BIBDs, therefore, can improve response rates as well as increase the accuracy and reliability of the data collected. After discussing the general nature of BIBDs and statistical techniques for analyzing preference data collected by BIBDs, three business-related applications are presented to illustrate the benefits of BIBDs. Next, caveats concerning the use of BIBDs are presented. In the last section, advantages of BIBDs are discussed
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van Ophem, Hans, Piet Stam, and Bernard van Praag. "Multichoice Logit: Modeling Incomplete Preference Rankings of Classical Concerts." Journal of Business & Economic Statistics 17, no. 1 (January 1999): 117. http://dx.doi.org/10.2307/1392243.

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Ophem, Hans Vann, Piet Stam, and Bernard Van Praag. "Multichoice Logit: Modeling Incomplete Preference Rankings of Classical Concerts." Journal of Business & Economic Statistics 17, no. 1 (January 1999): 117–28. http://dx.doi.org/10.1080/07350015.1999.10524801.

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Dissertations / Theses on the topic "Incomplete rankings"

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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) is currently an open problem. This thesis addresses the problem of scalability for visualizing and modeling partial incomplete rankings. In particular, we propose a distance measure for top-k rankings with the following three properties: (1) metric, (2) emphasis on top ranks, and (3) computational efficiency. Given the distance measure, the data can be projected into a low dimensional continuous vector space via multi-dimensional scaling (MDS) for easy visualization. We further propose a non-parametric model for estimating distributions of partial incomplete rankings. For the non-parametric estimator, we use a triangular kernel that is a direct analogue of the Euclidean triangular kernel. The computational difficulties for large n are simplified using combinatorial properties and generating functions associated with symmetric groups. We show that our estimator is computational efficient for rankings of arbitrary incompleteness and tie structure. Moreover, we propose an efficient learning algorithm to construct a preference elicitation system from partial incomplete rankings, which can be used to solve the cold-start problems in ranking recommendations. The proposed approaches are examined in experiments with real search engine and movie recommendation data.
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Ndungu, Alfred Mungai. "A Nonparametric Test for the Non-Decreasing Alternative in an Incomplete Block Design." Thesis, North Dakota State University, 2011. https://hdl.handle.net/10365/29772.

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The purpose of this paper is to present a new nonparametric test statistic for testing against ordered alternatives in a Balanced Incomplete Block Design (BIBD). This test will then be compared with the Durbin test which tests for differences between treatments in a BIBD but without regard to order. For the comparison, Monte Carlo simulations were used to generate the BIBD. Random samples were simulated from: Normal Distribution; Exponential Distribution; T distribution with three degrees of freedom. The number of treatments considered was three, four and five with all the possible combinations necessary for a BIBD. Small sample sizes were 20 or less and large sample sizes were 30 or more. The powers and alpha values were then estimated after 10,000 repetitions.The results of the study show that the new test proposed is more powerful than the Durbin test. Regardless of the distribution, sample size or number of treatments, the new test tended to have higher powers than the Durbin test.
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Books on the topic "Incomplete rankings"

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Schulz, E. Matthew. Controlling for rater effects when comparing survey items with incomplete Likert data. Iowa City, Iowa: ACT, Inc., 2001.

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Depot maintenance: Army report provides incomplete assessment of depot-type capabilities : report to the chairman and ranking minority member, Committee on Armed Services, House of Representatives. Washington, D.C. (P.O. Box 37050, Washington 20013): The Office, 1999.

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Hunter, Walt. Forms of a World. Fordham University Press, 2019. http://dx.doi.org/10.5422/fordham/9780823282227.001.0001.

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Forms of a World: Contemporary Poetry and the Making of Globalization shows how the forms of contemporary poetry are forged through the transformations of globalization from 1970 to the present. The book’s inquiry springs from two related questions: what happens when we think of poetry as a global literary form, and when we think of the global in poetic terms? I argue that analyses of globalization are incomplete without poetry and that contemporary poetry cannot be understood fully without acknowledging the global forces from which it arises. Forms of a World contends that poetry’s role is not only to make visible thematically the violence of global dispossessions, but to renew performatively the missing conditions for intervening within these processes. Poetic acts—in this book, the rhetoric of possessing, belonging, exhorting, and prospecting—address contemporary conditions that render social life ever more precarious. I turn to an eclectic group of Anglophone poets, from Seamus Heaney and Claudia Rankine to Natasha Trethewey and Kofi Awoonor, whose poetry and whose lives are, in different but related ways, inseparable from the contemporary global situation. These poets creatively intervene in global processes by remaking their poetry’s repertoire of forms, from experiments in the sonnet to contemporary inventions of the ode.
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Book chapters on the topic "Incomplete rankings"

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Hnatiienko, Hrygorii, Nataliia Tmienova, and Alexander Kruglov. "Methods for Determining the Group Ranking of Alternatives for Incomplete Expert Rankings." In Advances in Intelligent Systems and Computing, 217–26. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58124-4_21.

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Vetschera, Rudolf. "From Incomplete Information to Strict Rankings: Methods to Exploit Probabilistic Preference Information." In Dynamic Modeling and Econometrics in Economics and Finance, 379–94. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39120-5_21.

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Rendle, Steffen. "Ranking from Incomplete Data." In Context-Aware Ranking with Factorization Models, 19–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16898-7_3.

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Ładyżyński, Paweł P., and Przemysław Grzegorzewski. "On Incomplete Label Ranking with IF-sets." In Strengthening Links Between Data Analysis and Soft Computing, 55–62. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-10765-3_7.

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Schubert, Johan. "Partial Ranking by Incomplete Pairwise Comparisons Using Preference Subsets." In Belief Functions: Theory and Applications, 190–98. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11191-9_21.

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van Bakel, Ruud, Teodor Aleksiev, Daniel Daza, Dimitrios Alivanistos, and Michael Cochez. "Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification." In Lecture Notes in Computer Science, 107–24. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72308-8_8.

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AbstractLarge, heterogeneous datasets are characterized by missing or even erroneous information. This is more evident when they are the product of community effort or automatic fact extraction methods from external sources, such as text. A special case of the aforementioned phenomenon can be seen in knowledge graphs, where this mostly appears in the form of missing or incorrect edges and nodes.Structured querying on such incomplete graphs will result in incomplete sets of answers, even if the correct entities exist in the graph, since one or more edges needed to match the pattern are missing. To overcome this problem, several algorithms for approximate structured query answering have been proposed. Inspired by modern Information Retrieval metrics, these algorithms produce a ranking of all entities in the graph, and their performance is further evaluated based on how high in this ranking the correct answers appear.In this work we take a critical look at this way of evaluation. We argue that performing a ranking-based evaluation is not sufficient to assess methods for complex query answering. To solve this, we introduce Message Passing Query Boxes (MPQB), which takes binary classification metrics back into use and shows the effect this has on the recently proposed query embedding method MPQE.
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Busch, Christoph. "From Algorithmic Transparency to Algorithmic Choice: European Perspectives on Recommender Systems and Platform Regulation." In The International Library of Ethics, Law and Technology, 31–54. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-34804-4_3.

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AbstractAlgorithmic recommendations and rankings have become a key feature of the user experience offered by digital platforms. Recommender systems determine which information and options are prominently presented to users. While there is abundant technical literature on recommender systems, the topic has only recently attracted the attention of the European legislator. This chapter scrutinizes the emerging European regulatory framework for algorithmic rankings and recommendations in the platform economy with a specific focus on online retail platforms. Surveying the new rules for rankings and recommender systems in consumer contract law, unfair commercial practices law, and platform regulation, it identifies shortcomings and inconsistencies and highlights the need for coherence between the different regulatory regimes. The Digital Services Act could change the regulatory trajectory by introducing (albeit hesitantly and incompletely) a new regulatory model that shifts the focus from algorithmic transparency to algorithmic choice. More importantly, a choice-based approach to recommender governance and a market for third-party recommender systems (“RecommenderTech”) could also be facilitated by the new interoperability requirements introduced by the Digital Markets Act.
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Kwiesielewicz, Miroslaw, and Ewa van Uden. "Ranking Decision Variants by Subjective Paired Comparisons in Cases with Incomplete Data." In Computational Science and Its Applications — ICCSA 2003, 208–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44842-x_22.

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Couso, Inés, and Eyke Hüllermeier. "Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators." In Frontiers in Computational Intelligence, 31–46. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67789-7_3.

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Al-Helali, Baligh, Qi Chen, Bing Xue, and Mengjie Zhang. "Genetic Programming for Imputation Predictor Selection and Ranking in Symbolic Regression with High-Dimensional Incomplete Data." In AI 2019: Advances in Artificial Intelligence, 523–35. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35288-2_42.

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Conference papers on the topic "Incomplete rankings"

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Gorantla, Sruthi, Amit Deshpande, and Anand Louis. "Sampling Ex-Post Group-Fair Rankings." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/46.

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Randomized rankings have been of recent interest to achieve ex-ante fairer exposure and better robustness than deterministic rankings. We propose a set of natural axioms for randomized group-fair rankings and prove that there exists a unique distribution D that satisfies our axioms and is supported only over ex-post group-fair rankings, i.e., rankings that satisfy given lower and upper bounds on group-wise representation in the top-k ranks. Our problem formulation works even when there is implicit bias, incomplete relevance information, or only ordinal ranking is available instead of relevance scores or utility values. We propose two algorithms to sample a random group-fair ranking from the distribution D mentioned above. Our first dynamic programming-based algorithm samples ex-post group-fair rankings uniformly at random in time O(k^2 ell), where "ell" is the number of groups. Our second random walk-based algorithm samples ex-post group-fair rankings from a distribution epsilon-close to D in total variation distance and has expected running time O*(k^2 ell^2), when there is a sufficient gap between the given upper and lower bounds on the group-wise representation. The former does exact sampling, but the latter runs significantly faster on real-world data sets for larger values of k. We give empirical evidence that our algorithms compare favorably against recent baselines for fairness and ranking utility on real-world data sets.
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Sibony, Eric, Stephan Clemencon, and Jeremie Jakubowicz. "Multiresolution analysis of incomplete rankings with applications to prediction." In 2014 IEEE International Conference on Big Data (Big Data). IEEE, 2014. http://dx.doi.org/10.1109/bigdata.2014.7004361.

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Lorena, Luiz H. N., Antonio A. Chaves, Geraldo R. Mauri, and Luiz A. N. Lorena. "An Adaptive Biased Random-key Genetic Algorithm for Rank Aggregation with Ties and Incomplete Rankings." In 2022 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2022. http://dx.doi.org/10.1109/cec55065.2022.9870203.

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Kırnap, Ömer, Fernando Diaz, Asia Biega, Michael Ekstrand, Ben Carterette, and Emine Yilmaz. "Estimation of Fair Ranking Metrics with Incomplete Judgments." In WWW '21: The Web Conference 2021. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3442381.3450080.

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Li, Xiang, Ling Feng, and Lizhu Zhou. "Contextual ranking of query results with incomplete preferences." In 2009 Joint Conferences on Pervasive Computing (JCPC). IEEE, 2009. http://dx.doi.org/10.1109/jcpc.2009.5420161.

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Ben Amor, Nahla, Helene Fargier, Régis Sabbadin, and Meriem Trabelsi. "Possibilistic Games with Incomplete Information." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/214.

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Bayesian games offer a suitable framework for games where the utility degrees are additive in essence. This approach does nevertheless not apply to ordinal games, where the utility degrees do not capture more than a ranking, nor to situations of decision under qualitative uncertainty. This paper proposes a representation framework for ordinal games under possibilistic incomplete information (π-games) and extends the fundamental notion of Nash equilibrium (NE) to this framework. We show that deciding whether a NE exists is a difficult problem (NP-hard) and propose a Mixed Integer Linear Programming (MILP) encoding. Experiments on variants of the GAMUT problems confirm the feasibility of this approach.
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Terzopoulou, Zoi, and Ulle Endriss. "Aggregating Incomplete Pairwise Preferences by Weight." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/84.

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We develop a model for the aggregation of preferences that do not need to be either complete or transitive. Our focus is on the normative characterisation of aggregation rules under which each agent has a weight that depends only on the size of her ballot, i.e., on the number of pairs of alternatives for which she chooses to report a relative ranking. We show that for rules that satisfy a restricted form of majoritarianism these weights in fact must be constant, while for rules that are invariant under agents with compatible preferences forming pre-election pacts it must be the case that an agent's weight is inversely proportional to the size of her ballot.
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Niu, Xiang, Lusong Li, Xiaobing Xiong, Daniel Tkach, He Li, and Ke Xu. "Performances and Characteristics of DIGRank, Ranking in the Incomplete Networks." In 2011 IEEE 11th International Conference on Data Mining (ICDM). IEEE, 2011. http://dx.doi.org/10.1109/icdm.2011.117.

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Jian-hua, Dai, Yu Chun-long, and Ding Yi. "A ranking method of incomplete matrix based on prospect theory." In 2013 International Conference on Management Science and Engineering (ICMSE). IEEE, 2013. http://dx.doi.org/10.1109/icmse.2013.6586309.

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Chen, Yuanyuan, Chen Chen, and Hanyan Huang. "A Weighted PK Graph Based Ranking Aggregation Method for Incomplete Lists." In 2023 International Conference on Algorithms, Computing and Data Processing (ACDP). IEEE, 2023. http://dx.doi.org/10.1109/acdp59959.2023.00012.

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Reports on the topic "Incomplete rankings"

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Pound, B. G. GRI-99-0000 Gap Analysis of the GRI Research Program on Internal Corrosion. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), December 1999. http://dx.doi.org/10.55274/r0010720.

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Extensive information on the corrosion of steel in aqueous CO2 systems is now available from this program and numerous other sources. This information was reviewed to identify what research has been performed and what research remains to be undertaken to develop a expert system/risk management program. Four areas were examined: corrosion mechanisms, mitigation strategies, monitoring techniques, and models/risk assessment. There were five gaps in mechanisms (two for bacteria and one each for flow rate/chloride concentration, hydrocarbons, and organic acids) and four gaps in mitigation (antibiofilm additives, antibacterial corrosion inhibitors, antibiofilm coatings, and UV light). Monitoring techniques have one principal gap, which is the lack of a single sensor that can indicate the type of corrosion and whether bacteria are involved. Various gaps were found in the approaches used for modeling and risk assessment: semiempirical and mechanistic models (deficient in their ability to treat films, H2S, and bacteria); thermodynamic models (incomplete range of key chemical species); statistical models (limited testing); probabilistic risk assessment (lack of usable data); and ranking risk assessment (lack of appropriate algorithms for internal corrosion).
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