A Simple Study on Search Engine Text Classification for Retails Store Renien Joseph 1 , Samith Sandanayake 2 and Thanuja Perera 3 1 Zone24x7 (Private) Limited 460, Nawala Road Koswatte, Sri Lanka renien.john@gmail.com 2 Zone24x7 (Private) Limited 460, Nawala Road Koswatte, Sri Lanka samithdisal@gmail.com 3 Zone24x7 (Private) Limited 460, Nawala Road Koswatte, Sri Lanka tm.thanuja.perera@gmail.com Abstract It is obvious, the continuing growth of textual content rapidly increasing within the Word Wide Web (WWW). So certainly with the combination of sophisticated text processing and classification techniques it leads to produce high accurate search results. Even though a large body of research has delved into these problems; each has their theories and different approaches according to their data collection. This has been very challenging task continuously and this paper converges solutions, comprehensive comparisons that leads to different approaches. Therefore it will help to implement a robust search engine. The research proves probability text classification models classify documents robustly. But to improve the search result that involves short texts, we should certainly go through a hybrid approach including rules and statistical neural network models. As a pruning components the pre-processing and post- processing modules should adapted. And also due to the dynamic data the process pipeline should be frequently update. Keywords: Search queries, Text Classification, Rules, Machine Learning, and Information Retrieval 1. Introduction Nowadays the Internet usage is very common. With the rapid growing technologies world is shrinking too small. People do their activities on World Wide Web and they are now getting comfortable with online shopping experience. Hence, it is important the consumers should be provided with concrete online-based search solutions [12][10]. Catering a solution to all kind of consumers is a challenging task. There are consumers use search engine with different behaviorism. In the context of search engine many researchers still have higher involvement to provide a robust solution. Queries can be categorized in to two [9] and they are, 1) Key word/ Short word search queries 2) Long tail search queries Fig. 1 Search query demand [11] Fig. 2 Benchmarking of search traffic [11] The graphs (Figure 1,Figure 2) explain the variation of the search queries and its demand. It clearly shows consumers try mostly with short end queries more than long tail queries. Therefore, this research approach can be catered to short and long tail queries appropriately. ACSIJ Advances in Computer Science: an International Journal, Vol. 5, Issue 1, No.19 , January 2016 ISSN : 2322-5157 www.ACSIJ.org 52 Copyright (c) 2016 Advances in Computer Science: an International Journal. All Rights Reserved.