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92
Inferring hierarchical descriptions.
- In CIKM ’02: Proceedings of the eleventh international conference on Information and knowledge management,
, 2002
"... ABSTRACT We create a statistical model for inferring hierarchical term relationships about a topic, given only a small set of example web pages on the topic, without prior knowledge of any hierarchical information. The model can utilize either the full text of the pages in the cluster or the contex ..."
Abstract
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Cited by 30 (2 self)
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or the context of links to the pages. To support the model, we use "ground truth" data taken from the category labels in the Open Directory. We show that the model accurately separates terms in the following classes: self terms describing the cluster, parent terms describing more general concepts
Inferring the Demographics of Search Users Social Data Meets Search Queries
"... Knowing users ’ views and demographic traits offers a great potential for personalizing web search results or related services such as query suggestion and query completion. Such signals however are often only available for a small fraction of search users, namely those who log in with their social ..."
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Cited by 5 (0 self)
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scores and data from the US Religious Landscape Survey. We conclude that it is indeed feasible to infer important demographic data of users from their query history based on labelled Likes data and believe that this approach could provide valuable information for personalization and monetization even
SOFTWARE Open Access PAnalyzer: A software tool for protein inference in shotgun proteomics
"... Background: Protein inference from peptide identifications in shotgun proteomics must deal with ambiguities that arise due to the presence of peptides shared between different proteins, which is common in higher eukaryotes. Recently data independent acquisition (DIA) approaches have emerged as an al ..."
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Background: Protein inference from peptide identifications in shotgun proteomics must deal with ambiguities that arise due to the presence of peptides shared between different proteins, which is common in higher eukaryotes. Recently data independent acquisition (DIA) approaches have emerged
Open Access
"... Epilepsy, the condition of recurrent unprovoked seizures, is the world’s most prominent serious brain disorder, affecting some 50 million people worldwide. For an estimated 30 % of these patients, seizures remain poorly controlled despite maximal medical management. Moreover, control of epilepsy thr ..."
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understood. Here we present a general paradigm for the inference of dynamic functional networks from time series data, and apply this paradigm to the analysis of multielectrode invasive voltage recordings made directly from cortex
Phylogenetic comparative analysis: A modeling approach for adaptive evolution. The American Naturalist 164:683–695
, 2004
"... abstract: Biologists employ phylogenetic comparative methods to study adaptive evolution. However, none of the popular methods model selection directly. We explain and develop a method based on the Ornstein-Uhlenbeck (OU) process, first proposed by Hansen. Ornstein-Uhlenbeck models incorporate both ..."
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Cited by 77 (1 self)
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, and to infer details of the evolutionary process. We illustrate the method using two worked examples. Relative to existing approaches, the direct modeling approach we demonstrate allows one to explore more detailed hypotheses and to utilize more of the information content of comparative data sets than existing
METHODOLOGY ARTICLE Open Access
"... M3-S: a genotype calling method incorporating information from samples with known genotypes Gengxin Li1* † and Hongyu Zhao2† Background: A key challenge in analyzing high throughput Single Nucleotide Polymorphism (SNP) arrays is the accurate inference of genotypes for SNPs with low minor allele freq ..."
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can improve genotyping accuracy through clearly defining the boundaries of genotype clusters from samples with known genotypes, and enlarge the call rate by combining the simulated data based on the inferred genotype clusters information with the study population. Conclusions: Applications to real
Data Mining for Discrimination Discovery
"... In the context of civil rights law, discrimination refers to unfair or unequal treatment of people based on membership to a category or a minority, without regard to individual merit. Discrimination in credit, mortgage, insurance, labor market, and education has been investigated by researchers in e ..."
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Cited by 22 (10 self)
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in economics and human sciences. With the advent of automatic decision support systems, such as credit scoring systems, the ease of data collection opens several challenges to data analysts for the fight against discrimination. In this paper, we introduce the problem of discovering discrimination through data
RESEARCH ARTICLE Open Access
"... Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0) Jean-Marie Cornuet 1, Virgine Ravigné 2, Arnaud Estoup 1* Background: Approximate Bayesian computation (ABC) is a recent flexible class of Monte-Carlo algorithms increasingly ..."
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and population size changes. We here describe and illustrate new developments of this software that mainly include (i) inference from DNA sequence data in addition or separately to microsatellite data, (ii) the possibility to analyze five categories of loci considering balanced or non balanced sex ratios
RESEARCH ARTICLE Open Access
"... Phylogenomic analyses reveal a molecular signature linked to subterranean adaptation in rodents Kang Du1,2, Liandong Yang1,2 and Shunping He1* Background: Genome-wide signatures of convergent evolution are widely expected but rarely revealed in animals. Subterranean rodent genome and transcriptome d ..."
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data produced by next-generation sequencing facilitate the use of phylogenetic methods to infer non-synonymous and synonymous substitution rates within coding regions, which can reveal changes at the molecular level that are correlated with the dramatic shift from a terrestrial to subterranean habitat
Open Access Observing and Intervening: Rational and Heuristic Models of Causal Decision Making
"... Abstract: Recently, a number of rational theories have been put forward which provide a coherent formal framework for modeling different types of causal inferences, such as prediction, diagnosis, and action planning. A hallmark of these theories is their capacity to simultaneously express probabilit ..."
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the causal structure is unknown to the agent. A Bayesian approach of rational causal inference, which aims to infer the structure and its parameters from the available data, provides the benchmark model. This account is contrasted with a heuristic approach which knows categories of causes and effects
Results 1 - 10
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92
