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Concise Comparative Summaries (CCS) of Large Text Corpora with a Human Experiment
text summarization high-dimensional analysis sparse model- ing Lasso L1 regularized logistic regression co-occurrence tf-idf
2016/1/25
In this paper, we propose a general framework for topic-specific summarization of large text corpora, and illustrate how it can be used for the analysis of news databases. Our framework, concise compa...
Varying Naive Bayes Models with Applications toClassi cation of Chinese Text Documents
BIC Chinese Document Classification Screening Consistency Time-dependent Classification Rule
2016/1/20
Document classification is an area of great importance for which many clas-sification methods have been well developed. However, most of these methods cannot generate time-dependent classification rul...
Concise Comparative Summaries (CCS) of Large Text Corpora with a Human Experiment
text summarization high-dimensional analysis sparse model- ing, Lasso L1 regularized logistic regression co-occurrence tf-idf
2016/1/20
In this paper, we propose a general framework for topic-specific summarization of large text corpora, and illustrate how it can be used for the analysis of news databases. Our framework, concise compa...
Feature Selection Based on Term Frequency and T-Test for Text Categorization
feature selection term frequency t-test text classification
2013/6/14
Much work has been done on feature selection. Existing methods are based on document frequency, such as Chi-Square Statistic, Information Gain etc. However, these methods have two shortcomings: one is...
Scalable Text and Link Analysis with Mixed-Topic Link Models
Document classification Community detection Topic mod-eling Link prediction Stochastic block model
2013/5/2
Many data sets contain rich information about objects, as well as pairwise relations between them. For instance, in networks of websites, scientific papers, and other documents, each node has content ...
Text data, including speeches, stories, and other document forms, is often composed with regard to sentiment variables that are of interest for research in marketing, economics, and other social resea...
Text data mining：Theory and methods
text data mining clustering visualization pattern recognition discriminant analysis dimensionality reduction feature extraction manifold learning
2009/2/11
This paper provides the reader with a very brief introduction to some of the theory and methods of text data mining. The intent of this article is to introduce the reader to some of the current method...