Topic
Pairwise comparison
About: Pairwise comparison is a research topic. Over the lifetime, 6804 publications have been published within this topic receiving 174081 citations.
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23 Aug 2020TL;DR: This work empirically finds that at each decomposition level, the investigated hypergraphs obey five structural properties, which serve as criteria for evaluating how realistic a hypergraph is, and establish a foundation for the hypergraph generation problem.
Abstract: Graphs have been utilized as a powerful tool to model pairwise relationships between people or objects. Such structure is a special type of a broader concept referred to as hypergraph, in which each hyperedge may consist of an arbitrary number of nodes, rather than just two. A large number of real-world datasets are of this form - for example, lists of recipients of emails sent from an organization, users participating in a discussion thread or subject labels tagged in an online question. However, due to complex representations and lack of adequate tools, little attention has been paid to exploring the underlying patterns in these interactions. In this work, we empirically study a number of real-world hypergraph datasets across various domains. In order to enable thorough investigations, we introduce the multi-level decomposition method, which represents each hypergraph by a set of pairwise graphs. Each pairwise graph, which we refer to as a k-level decomposed graph, captures the interactions between pairs of subsets of k nodes. We empirically find that at each decomposition level, the investigated hypergraphs obey five structural properties. These properties serve as criteria for evaluating how realistic a hypergraph is, and establish a foundation for the hypergraph generation problem. We also propose a hypergraph generator that is remarkably simple but capable of fulfilling these evaluation metrics, which are hardly achieved by other baseline generator models.
46 citations
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TL;DR: This paper proposes a method for solving the stochastic multiple criteria decision making (SMCDM) problem, where consequences of alternatives with respect to criteria are represented by random variables with probability distributions.
46 citations
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46 citations
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20 Mar 2009TL;DR: The popular past and recent work on both local and global pairwise sequence alignment algorithms are presented and the advantages and limitations of the algorithms are also presented.
Abstract: Pairwise sequence alignment is a fundamental compute-intensive problem in bioinformatics that has helped researchers analyse biological sequences. The analysis has helped biologists detect pathogens, develop drugs, and identify common genes. The biological sequence database has been growing rapidly due to new sequences being discovered. This has brought many new challenges including sequence database searching and aligning long sequences. To solve these problems, many sequence alignment algorithms have been developed. These algorithms employ various techniques to efficiently find optimal or nearly-optimal alignments. In this paper, we present the popular past and recent work on both local and global pairwise sequence alignment algorithms. In addition to identifying the techniques used, the advantages and limitations of the algorithms are also presented.
46 citations
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TL;DR: In this article, an item response theory-based approach is presented to construct and model multidimensional pairwise preference responses directly, assessing information at the item and scale levels, and a way of computing standard errors for trait scores and estimating scale reliability.
Abstract: In this article, we offer some suggestions as to why tetrads and pentads have become the dominant formats for administering multidimensional forced choice (MFC) items but, in turn, raise questions regarding the underlying psychometric model and means of addressing item quality and scoring accuracy. We then focus our attention on multidimensional pairwise preference (MDPP) items and present an item response theory–based approach to constructing and modeling MDPP responses directly, assessing information at the item and scale levels, and a way of computing standard errors for trait scores and estimating scale reliability. To demonstrate the viability of this method for applied use, we show that the correspondence between MDPP scores derived from direct modeling with those obtained using single statement and unidimensional pairwise preference measures administered in a laboratory setting. Trait score correlations and criterion related validities are compared across testing formats and rating sources (i.e., s...
46 citations