On Utilization and Importance of Perl Status Reporter (SRr) in Text Mining

Details On Utilization and Importance of Perl Status Reporter (SRr) in Text Mining On Utilization and Importance of Perl Status Reporter (SRr) in Text Mining

2010-01-19

arxiv.org/abs/1001.3277v2

International Journal of Computer Science and Information Security, IJCSIS, Vol. 6, No. 3, pp. 253-259, December 2009, USA

Computer Science

Information Retrieval

7 pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS December 2009, ISSN 1947 5500,

Scientific paper

In Bioinformatics, text mining and text data mining sometimes interchangeably used is a process to derive high-quality information from text. Perl Status Reporter (SRr) is a data fetching tool from a flat text file and in this research paper we illustrate the use of SRr in text or data mining. SRr needs a flat text input file where the mining process to be performed. SRr reads input file and derives the high quality information from it. Typically text mining tasks are text categorization, text clustering, concept and entity extraction, and document summarization. SRr can be utilized for any of these tasks with little or none customizing efforts. In our implementation we perform text categorization mining operation on input file. The input file has two parameters of interest (firstKey and secondKey). The composition of these two parameters describes the uniqueness of entries in that file in the similar manner as done by composite key in database. SRr reads the input file line by line and extracts the parameters of interest and form a composite key by joining them together. It subsequently generates an output file consisting of the name as firstKey secondKey. SRr reads the input file and tracks the composite key. It further stores all that data lines, having the same composite key, in output file generated by SRr based on that composite key.

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