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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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Proceedings ArticleDOI
04 Feb 2010
TL;DR: This paper shows how a combination of pointwise, pairwise, and list-wise approaches can lead to improved ranking performance and, moreover, how it can be implemented in log-linear time.
Abstract: Ranking a set of retrieved documents according to their relevance to a given query has become a popular problem at the intersection of web search, machine learning, and information retrieval. Recent work on ranking focused on a number of different paradigms, namely, pointwise, pairwise, and list-wise approaches. Each of those paradigms focuses on a different aspect of the dataset while largely ignoring others. The current paper shows how a combination of them can lead to improved ranking performance and, moreover, how it can be implemented in log-linear time.The basic idea of the algorithm is to use isotonic regression with adaptive bandwidth selection per relevance grade. This results in an implicitly-defined loss function which can be minimized efficiently by a subgradient descent procedure. Experimental results show that the resulting algorithm is competitive on both commercial search engine data and publicly available LETOR data sets.

45 citations

Journal ArticleDOI
TL;DR: Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling.
Abstract: Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models. MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality. Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy.

45 citations

Book ChapterDOI
29 May 2016
TL;DR: This work focuses on the question whether some links—based on their context/position in the article text—can be deemed more important than others and presents different PageRank-based analyses on the link graph of Wikipedia and according experiments.
Abstract: Link analysis methods are used to estimate importance in graph-structured data. In that realm, the PageRank algorithm has been used to analyze directed graphs, in particular the link structure of the Web. Recent developments in information retrieval focus on entities and their relations (i.e., knowledge graph panels). Many entities are documented in the popular knowledge base Wikipedia. The cross-references within Wikipedia exhibit a directed graph structure that is suitable for computing PageRank scores as importance indicators for entities. In this work, we present different PageRank-based analyses on the link graph of Wikipedia and according experiments. We focus on the question whether some links—based on their context/position in the article text—can be deemed more important than others. In our variants, we change the probabilistic impact of links in accordance to their context/position on the page and measure the effects on the output of the PageRank algorithm. We compare the resulting rankings and those of existing systems with page-view-based rankings and provide statistics on the pairwise computed Spearman and Kendall rank correlations.

45 citations

Proceedings ArticleDOI
18 Jul 2010
TL;DR: This paper considers ag-glomerative hierarchical algorithms with pairwise constraints and introduces the single linkage which is equivalent to the transitive closure algorithm, while the centroid method and the Ward methods need kernelization of the algorithms.
Abstract: Recently semi-supervised clustering has been studied by many researchers, but there are no extensive studies using different types of algorithms. In this paper we consider ag-glomerative hierarchical algorithms with pairwise constraints. The constraints are directly introduced to the single linkage which is equivalent to the transitive closure algorithm, while the centroid method and the Ward methods need kernelization of the algorithms. Simple numerical examples are shown to see how the constraints work.

44 citations

Journal ArticleDOI
TL;DR: A way to significantly reduce the influence of noise is proposed by making use of entanglement purification together with a teleportation-based protocol and analyzing and comparing the effect of noise for the different simulation methods.
Abstract: We consider the simulation of interacting high-dimensional systems using pairwise interacting qubits. The main tool in this context is the generation of effective many-body interactions, and we examine a number of different protocols for obtaining them. These methods include the usage of higher-order processes (commutator method), unitary conjugation or graph state encoding, as well as teleportation-based approaches. We illustrate and compare these methods in detail and analyze the time cost for simulation. In the second part of the paper, we investigate the influence of noise on the simulation process. We concentrate on errors in the interaction Hamiltonians and consider two generic noise models: (i) timing errors in pairwise interactions and (ii) noisy pairwise interactions described by Master equations of Lindblad form. We analyze and compare the effect of noise for the different simulation methods and propose a way to significantly reduce the influence of noise by making use of entanglement purification together with a teleportation-based protocol.

44 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
20231,305
20222,607
2021581
2020554
2019520