Notes On Web Usage Mining

There are over 1 billion active websites today and its growth is exponential. Not all of them are optimized and effectively used by the users. Every owner of the website should continuously assess and improve the effectiveness of their website, if they want to address the above question. How they can do that? That is where Web Analytics comes into picture. The process of tracking, collecting, measuring, reporting and analyzing the data collected from the web for understanding and optimizing the web usage is known as Web Analytics. We can track every click of every person on the website. It provides information about number of visitors to a website and number of page views. In other words, Web Analytics is tracking the visitor behavior of

Web analytics is the practice of measuring, collecting, analyzing and reporting on Internet data for the purposes of understanding how a web site is used by its audience and how to optimize its usage. Web analytics helps a business owner break down the measure of information that originates from the web and aides in extraction of information in a simplified manner. In addition, Web analytics helps the organization in externalizing and standardizing information including variables that can be compared with each other.

Web analytics is nothing but collecting of web data, measuring the date, analysing the data and create the report of web usage. Web analytics used to measure the web traffic and also used as tool for business and market research for improve the effectiveness of web site. Web analytics can also be used to measure

information to send out target coupons to improve the sales of their maternity and baby

Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.

Made out of Web locales interconnected by hyperlinks, the World Wide Web can be seen as an enormous yet tumultuous wellspring of data. For choice making numerous business applications need to rely on upon web keeping in mind the end goal to total data from various sites. Programmed information extraction assumes an essential part in preparing results gave via internet searchers in the wake of presenting the question by client. presently days "site" has begun keeping more significance to our life. without which it is hard to oblige even one day .so it has turned into the need that the site ought to be more enlightening and alluring . be that as it may, the sites are created and just grew purposely or unwittingly

web mining is a method of structure information from unstructured or semi-structured web data source. Corporations are using web mining as gears to collect data from the different website. The data is gathered and examined to design a website, which it can offer information from variety of websites. The business can raise the sales because the consumers have an aptitude to trace web users browsing manners to the mouse clicks. It allows a business to personalize facilities for the client.

Web Analytics is a revolutionary way to support decisions in Web business using tools to collect and analyze data. The expression “ Collect and analyze data” it self is imprecise for a strong definition of Web Analytics, because of its paradoxically interpretation. According to Avinash Kaushik (Sybex, 2007) Web analyzes based only on data can’t motivate complete decisions, and even when there is lots of dates it necessary the small number of insights from the infinitesimally quantity of data. Therefore, I think that the best definition of Web Analytics is presented by Avinash Kaushik on his book Web Analytics 2.0 book, the art of online accountability & Science of customer centricity. For Avinash Kaushik Web Analytics is the web site and the competition around it qualitative and quantitative data analysis, in order to create

The definition of web mining from the book is the process to found useful information from web data, which are expressed in the form of textual, linkage, or usage information. These data that web mining collects can be beneficial for enterprise because information or data that web mining

Web analytics is characterized as a sway 's investigation of a site on its clients. E-trade organizations and other site distributers regularly utilize web investigation programming is to quantify such solid subtle elements as what number of individuals went by their website, what number of those guests were novel guests, how they went to the webpage, what decisive words they sought with on the webpage 's internet searcher, to what extent they remained focused given page or on the whole website and what joins they tapped on and when they exited the webpage.

Web analytics is, therefore, one of the approaches to improve the usability and the content for the website. For achieving this, understanding customer behavior plays a major role as key conversion metrics. Businesses use web analytics to measure, compare site performances and to look at Key Performance Indicator (KPI) that drive their business, such as purchase and conversion rates. Web analytics technologies are usually categorized into on-site and off-site web analytics. On-site web analytics refers to data collection on the current site, whereas Off-site analytics refers to data collection on the different sites (not on your current site) (Kaushik, 2009). The paper shall thus provide an overview of web analytics, with a focus on categorizing web analytics history, metrics, uses and need for web analytics with supporting case studies.

As probably the most natural type of storing information is text and text mining is believed to have a commercial potential greater than that of data mining. The recent study indicated that 80% of a company’s information is including in text documents. Text mining, however, is also a more complex task as compare to data mining as it involves dealing with text data that are naturally unstructured and fuzzy. Text mining is a multidisciplinary area, involving information retrieval, text examination, information extraction, clustering, categorization, visualization, database technology, device learning, and data mining [2]. In Text Mining, patterns are extracted from natural language Textual Database. There are many methods of text mining. In general, the major approaches, based on the kinds of data they take as input,

Data mining or Knowledge Discovery in Databases (KDD) is discovering patterns from large data groups through methods of artificial intelligence, machine learning ,statistics, and database systems. The aim of data mining process is to extract information from a data group and switch it to an ideal format for future . The data mining process comprise of database and data management aspects, data preprocessing, inference, complexity of discovered structures, and updating.

In this electronic and online world nowadays everything is online. This all had grown bigger in last few years. Because if we go back before 20 to 25 years, there was not any website. And now you look to any business, there is no business without having online websites. So there came a need of something which would not only help to develop but also maintain the website. And the field which do both of the thing is called as web analytics.

The wide adoption of the Internet has fundamentally altered the ways in which user communicate, gather information, conduct businesses and make purchases. As the use of World Wide Web is increasing, data on internet is increasing. A few sites consist of millions of pages, but millions of sites only contain a handful of pages. Few sites contain millions of links, but many sites have one or two. Millions of users flock to a few select sites, giving little attention to millions of others. The expansion of the World Wide Web (Web for short) has resulted in a large amount of data that is now in general freely available for user access. The different types of data have to be managed and organized in such a way that they can be accessed by different users efficiently by the search engine.