What Is Web Proxy Log Data And Preprocessing

This section discuss about the common traits or ideas observed in the three research topics. Although, each of the three articles discuss a unique idea, all of them are aimed at utilizing the web data to produce better results. Web data mining is a hot research topic in the current realm of big data. These papers discuss about the utilization of the valuable user generated data from the social media or the browser cookies to provide the best user experience in order to maintain the user interest in the company's product or to take effective decisions by an individual. All the three articles propose an idea to solution the problem stated, compared their results to the existing models and showed significant improvement.

Here we discuss about the common traits or ideas observed in the three research topics. Although, these three papers discuss about different ideas, they all fall under the web data mining domain. web data mining is a hot research topic in the current realm of big data. These papers discuss about the utilisation of the valuable user generated data from the social media or the the browser cookies to provide the best user experience in order to maintain the user interest in the company's product or to take effective decisions by the individual.

Keywords— Internet, User studies, worldwide web, Systems analysis, Data mining, visitors behavior, web analysis, web metric, Google Analytics, visitor tracking.

Abstract- Web is a collection of inter-related files on one or more web servers while web mining means extracting valuable information from web databases. Web mining is one of the data mining domains where data mining techniques are used for extracting information from the web servers. The web data includes web pages, web links, objects on the web and web logs. Web mining is used to understand the customer behaviour, evaluate a particular website based on the information which is stored in web log files. Web mining is evaluated by using data mining techniques, namely classification, clustering, and association rules. It has some beneficial areas or applications such as Electronic commerce, E-learning, E-government, E-policies, E-democracy, Electronic business, security and crime investigation and digital library. Retrieving the required web page from the web efficiently and effectively becomes a challenging task because web is made up of unstructured data, which delivers the

User profiling techniques have widely applied in various web search, user-adaptive software systems, web user identification, personalization, recommendation, e-market analysis, intelligent tutoring systems, intelligent agents, as well as personalized information retrieval and filtering.

Web sites have progressed to a new level of sophistication, especially in terms of their capacity to track and store usage patterns and allow for the utilization of this

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, 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.

The logs files are maintained by the web server by the activity of the client who accesses the web server for a web site through the browser. The information can be written by the site owner, gleaned from the other web sites or other sources or contributed by users. The sample web log dataset are:

Although association rule methods have advantages, there are also some limitations that might cause loosing information. Exemplary association rules concentrate on the co-occurrence of items like purchased products, visited web pages, etc. within the transaction set. A single transaction can be a payment for purchased products or services, an order with a set of items with a historical session in a web portal. Alternate independence of items, products and web pages, is one of the most significant hypotheses of the technique, but it is not fulfilled in the web domain. Web pages are linked with each other by using hyperlinks, and they often calibrate all potential navigational paths. A user can enter the required web page address URL to a browser. However, most navigation is completed with the help of hyperlinks created by site administrators. Hence, the web structure sorely incarcerates visited list of pages, user sessions, which are not independent of one another as products in a ideal store. To access a page, the user is usually imposed to

Data mining is a process of extracting the information from the large set of databases. As the web contain huge amount of information finding the exact information of which user required is difficult. Web personalization is a process of analyzing the user?s navigational behavior based on web sequence access performed by the user based on which recommendations are done. Web usage mining plays an important role in recommendation of pages to user based on user interest. Different kinds of technics and algorithms are used for web personalization and recommendation of pages. The technics of data mining such as collaborative filtering, association rule mining, ontology, support vector machine, sequence access patterns and web log mining are compared to know which technic is more efficient for recommendation of web pages based on web personalization. A survey conducted to find which technic easily recommends the web pages to user such that it consumes less time for searching the information. The paper proposes the technic that provides efficient results for recommendation of pages to user based on user interest comparing parameters like precision and recall and matching algorithm. Web log based recommendations are more efficient when compared to other technics as it consumes less time for searching the relevant information. The survey gives the result in the form of the graph for different parameters.

The method employs data mining techniques such as a frequent pattern and reference mining found from (Holland et al., 2003; KieBling & Kostler, 2002) and (Ivancy & Vajk, 2006). Frequent and reference mining is a heavily research area in data mining with wide range applications for discovering a pattern from Web log data to obtain information about navigational behavior of

Web Data Mining is the use of unstructured or semi-structured web data sources to extract structured information. Organization make use of web data mining as a tool in which data is gathered from different web sites. The data is then collated to do analysis, build other web sites that will provide information. It is an advantage to have

The process in which the analysis of the user interaction with the website is carried out is called web analytics.

Ever since the invention of the World Wide Web by British computer scientist Tim Berners-Lee in 1990, the number of people worldwide, in both developed and developing countries, using the internet to communicate and as a source of information has been on an unremitting increase. In 2005, there were approximately 1 billion internet users worldwide and has risen consistently. By 2017 there are roughly 3.5 billion internet users. This dramatic increase is due to the ceaseless technological advancements in telecommunications. At the same point in time from when the internet was introduced, there have been online communities.