Add to ORKGThis paper introduces an approach to text classification for semi-structured label systems that have poor performance with standard methods. With the perspective that perfect classification for such a system is unattainable, we demonstrate an automated procedure to isolate the learnable elements of the problem. Through analysis of an example dataset, we identify attributes of the label system that hinder performance and demonstrate through manual methods that minimizing these attributes will lead to improved performance. Further we present that label clustering effectively minimizes these attributes. We then show that with a combination of frequency, co-occurrence, and document simil...
Abstract-With the boom of web and social networking, the amount of generated text data has increased...
A common classification task of today is classifying resources that consist of words. Nondiscriminat...
Document clustering is a very hard task in automatic text processing since it requires extracting re...
Document classification is a large body of search, many approaches were proposed for single label an...
Document classification is a large body of search, many approaches were proposed for single label an...
The purpose of text clustering in information retrieval is to discover groups of semantically relate...
AbstractText classification method that uses efficient similarity measures to achieve better perform...
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training da...
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training dat...
This paper addresses the problem of learning to classify texts by exploiting information derived fro...
Supervised and unsupervised learning have been the focus of critical research in the areas of machin...
Supervised and unsupervised learning have been the focus of critical research in the areas of machin...
Feature selection methods have been successfully applied to text categorization but seldom applied t...
Supervised and unsupervised learning have been the focus of critical research in the areas of machin...
Text categorization involves mapping of documents to a fixed set of labels. A similar but equally im...
Abstract-With the boom of web and social networking, the amount of generated text data has increased...
A common classification task of today is classifying resources that consist of words. Nondiscriminat...
Document clustering is a very hard task in automatic text processing since it requires extracting re...
Document classification is a large body of search, many approaches were proposed for single label an...
Document classification is a large body of search, many approaches were proposed for single label an...
The purpose of text clustering in information retrieval is to discover groups of semantically relate...
AbstractText classification method that uses efficient similarity measures to achieve better perform...
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training da...
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training dat...
This paper addresses the problem of learning to classify texts by exploiting information derived fro...
Supervised and unsupervised learning have been the focus of critical research in the areas of machin...
Supervised and unsupervised learning have been the focus of critical research in the areas of machin...
Feature selection methods have been successfully applied to text categorization but seldom applied t...
Supervised and unsupervised learning have been the focus of critical research in the areas of machin...
Text categorization involves mapping of documents to a fixed set of labels. A similar but equally im...
Abstract-With the boom of web and social networking, the amount of generated text data has increased...
A common classification task of today is classifying resources that consist of words. Nondiscriminat...
Document clustering is a very hard task in automatic text processing since it requires extracting re...