Add to ORKGStatistical analysis prior to processing queries in text mining is important and can help text searching methods to perform better. In this paper descriptive analysis and non-parametric ANOVA are presented for Term Document frequency matrix showing the significance of different terms and their paired comparisons. This will filter and reduce the number of the terms and can be significantly contributed to faster and efficient searching results
In text mining most techniques depends on statistical analysis of terms. Statistical analysis trance...
In this paper, we propose a new research trend analysis using important word clusters and its relati...
The need for an efficient method to find the furthermost appropriate document corresponding to a par...
In text documents data mining techniques have been proposed for mining useful patterns. But how to e...
Text mining, also referred to as text data mining, roughly equivalent to text analytics, refers to t...
It is a big challenge to guarantee the quality of discovered relevance features in text documents fo...
Measuring document similarity has shown its fundamental utilization in various text mining applicati...
Most of text mining techniques are based on word and/or phrase analysis of the text. The statistical...
This paper describes a text mining tool that performs two tasks, namely document clustering and text...
Predefined categories can be assigned to the natural language text using for text classification. It...
Text mining research paper is a scientific study that focuses on the development and application of ...
Analysis of large text data sets is gaining popularity providing the users some insights into their ...
Typically, textual information is available as unstructured data, which require processing so that d...
Most existing automatic content analysis and indexing techniques are based on word frequency charac...
In the era of big data, the capacity to produce textual documents is increasing day by day. Our abil...
In text mining most techniques depends on statistical analysis of terms. Statistical analysis trance...
In this paper, we propose a new research trend analysis using important word clusters and its relati...
The need for an efficient method to find the furthermost appropriate document corresponding to a par...
In text documents data mining techniques have been proposed for mining useful patterns. But how to e...
Text mining, also referred to as text data mining, roughly equivalent to text analytics, refers to t...
It is a big challenge to guarantee the quality of discovered relevance features in text documents fo...
Measuring document similarity has shown its fundamental utilization in various text mining applicati...
Most of text mining techniques are based on word and/or phrase analysis of the text. The statistical...
This paper describes a text mining tool that performs two tasks, namely document clustering and text...
Predefined categories can be assigned to the natural language text using for text classification. It...
Text mining research paper is a scientific study that focuses on the development and application of ...
Analysis of large text data sets is gaining popularity providing the users some insights into their ...
Typically, textual information is available as unstructured data, which require processing so that d...
Most existing automatic content analysis and indexing techniques are based on word frequency charac...
In the era of big data, the capacity to produce textual documents is increasing day by day. Our abil...
In text mining most techniques depends on statistical analysis of terms. Statistical analysis trance...
In this paper, we propose a new research trend analysis using important word clusters and its relati...
The need for an efficient method to find the furthermost appropriate document corresponding to a par...