Text Classification Algorithms

Zhou Y (2009) An improved KNN text classification algorithm based on clustering. J Comput... 

While we like to imagine that beautiful well constructed theories underly our algorithms, we frequently find that when it comes to text classification many systems in praetiee simply use a hodge-podge of rules to perform the task. This is particularly common in approaches to semiotic classification in genres where the amount of non-natural language text is very low, and so only a few special cases (say dealing with munbers) are required. 

The first stage in text analysis is therefore to perform semiotic classification which assigns a class to each token. This is performed by one of the above mentioned classification algorithms... 

Another poly(A) site prediction tool, PAG, was designed to extract poly(A) sites from known dataset (with poly(A) specified) and use this information to predict poly(A) sites from unknown sequences. This is powerful when dealing with a new species that is substantially different (or do not know if there is different) from Arabidopsis or rice models. It constitutes three major steps. In the first step, PAG takes a set of nucleotide sequences as input and imports the parameter file for the classification model and the features. In the second step, a classification algorithm is performed to train and test the model. In the final step, the output files are generated. The output of PAG is a few text files with one of them containing the probabilities of each sequence to determine the potential poly(A) sites and the others as intermediate files. 

The section that follows describes basic background concepts and nomenclature. Then a classification of various programming models is outlined. Computational chemistry applications rely on many kinds of linear algebra and on equation-solving techniques that use new computer science algorithms. These implementations are delineated. A partial review of current and planned applications, developed on today s MPP supercomputers for chemistry, is presented. The last section of text gives a summary and our conclusions. Finally, we present a glossary and an appendix that reviews the currently available MPP machines. 

---