Results 221 to 230 of about 129,844 (264)

Crowdsourced Selection on Multi-Attribute Data

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017
Crowdsourced selection asks the crowd to select entities that satisfy a query condition, e.g., selecting the photos of people wearing sunglasses from a given set of photos. Existing studies focus on a single query predicate and in this paper we study the crowdsourced selection problem on multi-attribute data, e.g., selecting the female photos with dark
Xueping Weng, Guoliang Li 0001, Huiqi Hu, Jianhua Feng   +3 more
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On Soft Partition Attribute Selection

2012
Rough set theory provides a methodology for data analysis based on the approximation of information systems. It is revolves around the notion of discernibility i.e. the ability to distinguish between objects based on their attributes value. It allows inferring data dependencies that are useful in the fields of feature selection and decision model ...
Rabiei Mamat, Tutut Herawan, Ahmad Noraziah, Mustafa Mat Deris   +3 more
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Unsupervised feature selection for attributed graphs

Expert Systems with Applications, 2021
Abstract Many real-world applications generate attributed graphs that contain both link structures and content information associated with nodes. Content information in real networks always contains high dimensional feature space. In recent years, unsupervised feature selection has been widely used in handling high dimensional data without label ...
Ruizhi Zhou, Lingfeng Niu, Hong Yang 0003   +2 more
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Feature selections for authorship attribution

Proceedings of the 28th Annual ACM Symposium on Applied Computing, 2013
The authorship attribution (AA) problem can be viewed as a categorization problem. To determine the most effective features to discriminate between different authors, we have evaluated six independent feature-scoring selection functions (information gain, pointwise mutual information, odds ratio, χ2, DIA, and the document frequency (df)).
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Gene-finding as an Attribute Selection Task

6th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007), 2007
For data miners, bioinformatics pose a most demanding challenge than only creating efficient algorithms. They should work with databases that are more "horizontal" than "vertical", as the data consist of a few samples of a large (sometimes huge) number of attributes in the case of micro-arrays.
Helyane Bronoski Borges, Júlio C. Nievola   +1 more
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Zero-Shot Learning With Attribute Selection

Proceedings of the AAAI Conference on Artificial Intelligence, 2018
Zero-shot learning (ZSL) is regarded as an effective way to construct classification models for target classes which have no labeled samples available. The basic framework is to transfer knowledge from (different) auxiliary source classes having sufficient labeled samples with some attributes shared by target and source classes as ...
Yuchen Guo, Guiguang Ding, Jungong Han, Sheng Tang   +3 more
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A tree-based algorithm for attribute selection

Applied Intelligence, 2017
This paper presents an improved version of a decision tree-based filter algorithm for attribute selection. This algorithm can be seen as a pre-processing step of induction algorithms of machine learning and data mining tasks. The filter was evaluated based on thirty medical datasets considering its execution time, data compression ability and AUC (Area
José Augusto Baranauskas, Oscar Picchi Netto, Sérgio Ricardo Nozawa, Alessandra Alaniz Macedo   +3 more
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Selective facilitation of memory attributes by strychnine

Pharmacology Biochemistry and Behavior, 1977
In two experiments, the effects of strychnine on the specific memory attributes of prior discrimination training were assessed in terms of subjects' performance under various discrimination reversal conditions. Mice were trained in a discrimination task with two redundant relevant cues.
M J, Brennan, W C, Gordon
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The Selection of the Attributes

1971
The problem of how to select an effective set of attributes for a PRD is generally considered the single most difficult problem in the design. The problem is frequently discussed in the literature (Levine 1969; Nagy 1969; Nelson and Levy; Fu et al. 1970; Henderson and Lainiotis 1970) and is the topic of September 1971 issue of the IEEE Transactions on ...
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Multi-attribute optimization in service selection

World Wide Web, 2011
As multiple service providers may compete to offer the same functionality with different quality of service (e.g., latency, fee, and reputation), a key issue in service computing is selecting service providers with the best user desired quality. Existing service selection approaches mostly rely on computing a predefined objective function.
Qi Yu 0001, Athman Bouguettaya
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