International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 5 Issue: 6 650 – 654 _______________________________________________________________________________________________ 650 IJRITCC | June 2017, Available @ http://www.ijritcc.org _______________________________________________________________________________________ Research Proposal on Distinct Study and Significant of Search Techniques in Web Mining Tiruveedula Gopikrishna Research Scholar in CSE Dept. Rayalaseema University Kurnool, India gktiruveedula@gmail.com Prof.Dr.K.V.N.Sunitha Supervisor Principal, BVRITWomen’s Engg.College Hyderabad, India k.v.n.sunitha@gmail.com Abstract—The goal of this research is to provide a more current evaluation and update of web mining research and how machine learning techniques can be applied to web mining techniques available. Currenttrends in each of the three different types of web mining are reviewed in the categories of web content mining, web usage mining, and web structure mining.Unlike previous investigators, we divide web mining processes into the following five subtasks such as resource finding and retrieving, information selection and preprocessing, patterns analysis and recognition, validation and interpretation, and visualization.Major limitations of web mining research are lack of suitable test collections that can be reused by researchers and difficulty to collect web usage data across different web sites. Most web mining applications have been reviewed in this research. Although the activities are still in their early stages and should continue to develop as the Web evolves. This research shows that frequent pattern growth algorithm produces more efficient and accurate results to compare with K-Apriori algorithm. The proposed methods were successfully tested and results were observed and compared with existing methods on the web log files using machine learning techniques. Keywords-Web Mining,web content mining, web usage mining, web structure mining, patterns analysis and recognition. __________________________________________________*****_________________________________________________ I. INTRODUCTION The current topic is to find out the significant and latest updates on Search techniques and web mining in the world of Internet. Here we shall discuss the types, application and systematic use of search techniques. Through some distinct chapters we shall also come to know about the latest updates on web world and different tools and techniques of searching or exploring data. Although the term is common to all of us but through this research study we shall come to know about its deep interface and new ways and future possibilities of different mining and search applications Web Mining As per the general definition, Web mining techniques to discover patterns from the Web is known as web mining. Web mining can be divided into three different types, which are Web usage mining, Web content mining and Web structure mining. Web data mining is a process that discovers the built-in relationships among Web data, which are expressed in the forms of textual, linkage or usage information, via analyzing the features of the Web and web-based data using data mining techniques. Predominantly it concentrates on discovering Web usage pattern via Web usage mining. Web usage mining discovers the usage knowledge of web users with more personalized information [1]. Web Data Web data can be collected in server logs, browser logs, proxy logs, or obtained from an organization's database. These data collections differ in terms of the location of the data source, the kinds of data available, the segment of population from which the data was collected, and methods of implementation. There are many kinds of data that can be used in Web Mining are classified into three categories are content mining, structure mining and usage mining [2].  Content Mining: The visible information in the Web pages or the information which was meant to be forwarded to the users. A major part of it includes text and graphics [2].  Structure Mining: Information which describes the organization of the website. It is divided into two types. In a given page intra-page structure information includes the arrangement of various HTML or XML tags. Inter-page arrangement information is the hyper- links used for site navigation [2].  Usage Mining: In usage mining data that depicts the usage patterns of Web pages, such as IP addresses, page references, and the date and time of accesses and other information depending on the web log arrangement.Web Usage Mining is a part of Web Mining, which, in turn, is a part of data mining. As data mining involves the concept of extraction meaningful and valuable information from large volume of data, Web usage mining involves mining the usage characteristics of the users of Web applications [2]. This uncovered information can then be used in a several ways such as, development of the application, checking of fraudulent elements etc. Web usage mining is frequently regarded as a part of the