1,720,955 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Modeling the winning seed distribution of the NCAA basketball tournament
Full text linkThe National Collegiate Athletic Association's (NCAA) men's division I college basketball tournament is an annual competition that draws widespread attention in the United States. Estimating the outcome of each game is a popular activity undertaken by numerous websites, fans, and more recently, academic researchers. There has been a surge of interest in proposing mathematical methods to model the tournament's results and pick the winners of future games. This thesis analyzes the results of the NCAA basketball tournament since 1985 and proposes several models to capture the winning seed distribution in each round.
The Exponential Model estimates the winning probability of each team by modeling the time between a team's successive winnings in a round as an exponential random variable. The Exponential Model estimates a zero probability for events that have not occurred in the training data set. The Markov Model solves this limitation by defining a Markov chain that incorporates each team's winnings in prior rounds to estimate its winning probability. Results of these two models are validated using a chi-squared goodness of fit test.
The Power Model, which is an intelligent tool for generating brackets of winners, quantifies the relative strength of each match-up in a round as a power function of the teams' seed numbers, with the exponent estimated using the historical results. The main problem of the Power Model is the data complications that are generally caused by the small size of the training data set, especially in later rounds. The Position and Upset Models solve this problem by representing the tournament's games as a binary sequence and estimating the outcome of each game based on the teams' performance in the similar game.
While generating a bracket in a forward direction from the first to the last round propagates the incorrect picks through the tournament, correctly picking the winners in later rounds automatically fills the bracket for several games in earlier rounds. This motivates developing bidirectional models that pick the winners based on a combination of models in forward and backward directions. The Power, Position, Upset, and bidirectional models are assessed based on the aggregate performance of millions of brackets for the five most recent tournaments (2012-2016).
The proposed models allow one to estimate the likelihoods of different seed combinations by applying the estimated winning seed distributions, which accurately summarize the seeds' aggregate performance and provide a deeper understanding of the uncertainty in the games' outcomes.Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-02-28 without embargo termsThe student, Arash Khatibi, accepted the attached license on 2016-11-22 at 10:42.The student, Arash Khatibi, submitted this Thesis for approval on 2016-11-22 at 10:49.This Thesis was approved for publication on 2016-11-23 at 09:58.DSpace SAF Submission Ingestion Package generated from Vireo submission #10295 on 2017-02-28 at 14:51:46Made available in DSpace on 2017-03-01T15:49:02Z (GMT). No. of bitstreams: 2
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Previous issue date: 2016-11-2
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Generalized sequential assignment problem
Full text linkThe Sequential Stochastic Assignment Problem (SSAP) deals with assigning sequentially arriving tasks with stochastic parameters to workers with fixed success rates. The reward of each assignment is the product of the worker's success rate and the task value assigned to the worker. The objective is to maximize the total expected reward. There has been a surge of interest in studying sequential assignment problems due to their applications in online matching markets, asset selling, and organ transplant.
This dissertation studies several variations of SSAP by relaxing the main assumptions. The first part assumes that the workers' success rates are random values coming from a known distribution. This generalization modifies the SSAP from a problem with a single random value (i.e., the task value) at each stage to an online matching problem with several random parameters (i.e., the task value and the workers' success rates). The optimal assignment policy uses backward induction to first solve smaller subproblems, and then use them to optimally assign tasks to workers from the first stage. An approximation algorithm is proposed that achieves a fraction of the optimal reward in a polynomial time.
Assuming that the value of sequentially arriving elements are independently drawn from a known distribution is unrealistic in many applications. The second part of thesis relaxes this assumption and uses the well-known Secretary Problem to derive constant-competitive algorithms for SSAP with tasks having a random arrival order. Several deterministic and randomized algorithms are proposed and their performance are compared with the maximum offline reward. These algorithms use the first stages of the problem as a training phase to compute thresholds for the task values. These thresholds are used to assign tasks to workers after the training phase.
The third part uses the linear programming technique to derive bounds on the performance of optimal policy for several variations of SSAP. Formulating an online matching problem as a linear program is a useful tool. In addition to deriving bounds on performance of optimal policies, the linear programming technique can be used to formulate extensions of the problem as linear programs by simple changes in the objective function and constraints of the basic formulation. The linear programming formulation of the incentive compatible problem and the sequential assignment problem with unknown number of elements are also proposed. The edge-weighted online bipartite matching problem is used to design assignment policies for each of the formulated problems.
The last part relaxes the assumption that at most one task must be assigned to each worker in SSAP. It is assumed that a worker is available for possible future assignments after performing the previously assigned task. The number of stages that the worker is not available due to a prior task assignment is referred to as the task duration. This problem is studied under various models for the task duration. First, it is assumed that the task duration is fixed. Then, assignment policies are proposed for the problem with a memoryless model for the task duration. The proposed algorithms are extensions of the optimal algorithm for the sequential assignment problem. They divide the n-stage assignment process to periods whose lengths are equal to the expected task duration. Then, they assign tasks to workers in each period by applying the optimal algorithm of the sequential assignment problem.Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-08-10 without embargo termsThe student, Arash Khatibi, accepted the attached license on 2017-04-10 at 21:35.The student, Arash Khatibi, submitted this Dissertation for approval on 2017-04-10 at 21:42.This Dissertation was approved for publication on 2017-04-11 at 16:29.DSpace SAF Submission Ingestion Package generated from Vireo submission #10696 on 2017-08-10 at 13:39:11Made available in DSpace on 2017-08-10T19:14:52Z (GMT). No. of bitstreams: 2
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Previous issue date: 2017-04-1
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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