291 research outputs found
Rank Aggregation via Heterogeneous Thurstone Preference Models
We propose the Heterogeneous Thurstone Model (HTM) for aggregating ranked
data, which can take the accuracy levels of different users into account. By
allowing different noise distributions, the proposed HTM model maintains the
generality of Thurstone's original framework, and as such, also extends the
Bradley-Terry-Luce (BTL) model for pairwise comparisons to heterogeneous
populations of users. Under this framework, we also propose a rank aggregation
algorithm based on alternating gradient descent to estimate the underlying item
scores and accuracy levels of different users simultaneously from noisy
pairwise comparisons. We theoretically prove that the proposed algorithm
converges linearly up to a statistical error which matches that of the
state-of-the-art method for the single-user BTL model. We evaluate the proposed
HTM model and algorithm on both synthetic and real data, demonstrating that it
outperforms existing methods.Comment: 36 pages, 2 figures, 8 tables. In AAAI 202
A Margin-based MLE for Crowdsourced Partial Ranking
A preference order or ranking aggregated from pairwise comparison data is
commonly understood as a strict total order. However, in real-world scenarios,
some items are intrinsically ambiguous in comparisons, which may very well be
an inherent uncertainty of the data. In this case, the conventional total order
ranking can not capture such uncertainty with mere global ranking or utility
scores. In this paper, we are specifically interested in the recent surge in
crowdsourcing applications to predict partial but more accurate (i.e., making
less incorrect statements) orders rather than complete ones. To do so, we
propose a novel framework to learn some probabilistic models of partial orders
as a \emph{margin-based Maximum Likelihood Estimate} (MLE) method. We prove
that the induced MLE is a joint convex optimization problem with respect to all
the parameters, including the global ranking scores and margin parameter.
Moreover, three kinds of generalized linear models are studied, including the
basic uniform model, Bradley-Terry model, and Thurstone-Mosteller model,
equipped with some theoretical analysis on FDR and Power control for the
proposed methods. The validity of these models are supported by experiments
with both simulated and real-world datasets, which shows that the proposed
models exhibit improvements compared with traditional state-of-the-art
algorithms.Comment: 9 pages, Accepted by ACM Multimedia 2018 as a full pape
Static and Dynamic BART for Rank-Order Data
Ranking lists are often provided at regular time intervals by one or multiple
rankers in a range of applications, including sports, marketing, and politics.
Most popular methods for rank-order data postulate a linear specification for
the latent scores, which determine the observed ranks, and ignore the temporal
dependence of the ranking lists. To address these issues, novel nonparametric
static (ROBART) and autoregressive (ARROBART) models are introduced, with
latent scores defined as nonlinear Bayesian additive regression tree functions
of covariates. To make inferences in the dynamic ARROBART model, closed-form
filtering, predictive, and smoothing distributions for the latent time-varying
scores are derived. These results are applied in a Gibbs sampler with data
augmentation for posterior inference. The proposed methods are shown to
outperform existing competitors in simulation studies, and the advantages of
the dynamic model are demonstrated by forecasts of weekly pollster rankings of
NCAA football teams.Comment: The Supplementary Material is available upon request to the author
Prioritizing Offshore Vendor Selection Criteria for the North American Geospatial Industry
The U.S. market for geospatial services totaled US $2.2 billion in 2010, representing 50% of the global market. Data-processing firms subcontract labor-intensive portions of data services to offshore providers in South and East Asia and Eastern Europe. In general, half of all offshore contracts fail within the first 5 years because one or more parties consider the relationship unsuccessful. Despite the high failure rates, no study has examined the offshore vendor selection process in the geospatial industry. The purpose of this study was to determine the list of key offshore vendor selection criteria and the efficacy of the analytic hierarchy process (AHP) for ranking the criteria that North American geospatial companies consider in the offshore vendor selection process. After the selection of the initial list of factors from the literature and their validation in a pilot study, a final survey instrument was developed and administered to 15 subject matter experts (SMEs) in North America. The SMEs expressed their preferences for one criterion over another by pairwise comparisons, which served as input to the AHP procedure. The results showed that the quality of deliverables was the top ranked (out of 26) factors, instead of the price, which ranked third. Similarly, SMEs considered social and environmental consciousness on the vendor side as irrelevant. More importantly, the findings indicated that the structured AHP process provides a useful and effective methodology whose application may considerably improve the quality of the overall vendor selection process. Last, improved and stabilized business relationships leading to predictable budgets might catalyze social change, supporting stable employment. Consumers could benefit from derivative improvements in product quality and pricing
Valuing agricultural externalities in Canterbury rivers and streams
Water quality and quantity concerns in Canterbury are intrinsically related to agriculture. Monetary values for impacts on streams and rivers is lacking in policy debate. This paper employs choice modelling to estimate values of three impacts on rivers and streams in Canterbury associated with agriculture: health risks of E coli from animal waste, ecological effects of excess nutrients, and low-flow impacts of irrigation. This study provides a valuation of outcomes for public policy implemented in Canterbury such as The Dairy and Clean Streams Accord, Living Streams, and The Restorative Programme for Lowland Streams.non-market-valuation, choice experiment, agricultural externalities, New Zealand, Agricultural and Food Policy, Environmental Economics and Policy, Food Consumption/Nutrition/Food Safety, Health Economics and Policy,
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