This document discusses web usage mining and analyzing user behavior patterns on websites. It covers collecting and processing clickstream data from web server logs to discover frequently accessed pages and user interests. Specific user behaviors like product views, clicks, purchases and time spent on a site can be analyzed. Web usage mining aims to increase sales and profits by better understanding user navigation and providing personalized experiences. The document also outlines hardware, software and development process requirements for a web usage mining application.

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Academic Year 2016-2017

2. Presented by Under Guidance of
Rutuja A Suryawanshi Prof.Rashmi Tundalwar
Supriya H Wakchaure
Sonal S Patil
Ashish S More
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 Web usage mining: automatic discovery of
patterns in clickstreams and associated data
collected or generated as a result of user
interactions with one or more Web sites.
 Goal: analyze the behavioral patterns and
profiles of users interacting with a Web site.
 The discovered patterns are usually
represented as collections of pages, objects,
or resources that are frequently accessed by
groups of users with common interests.

4.  Data in Web Usage Mining:
◦ Web server logs
◦ Site contents //eg jsp pagesclicks
◦ Further application data
 A large part of Web usage mining is about
processing usage/ clickstream data.
◦ After that various data mining algorithm can be
applied eg. k-means,navybayes.
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6.  In Web usage analysis, these data are the
sessions of the site visitors: the activities
performed by a user from the moment she
enters the site until the moment she leaves it.
 Difficult to obtain reliable usage data due to
proxy servers (duplicate server built for
convinience)
 Eg facebook has time limit sessions log login
logout in browsers not in apps.
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7.  Product View
◦ Occurs every time a product is displayed on a page
view
◦ Typical Types: Image, Link, Text
 Product Click-through
◦ Occurs every time a user “clicks” on a product to
get more information
 Maximum purchases of particular product
 And avialable offers.
 Mgs and mail through offers are informed.
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8.  Shopping Cart
◦ Shopping Cart Add –here ID is generated
 Product Buy
◦ Separate buy event occurs for each product in the
shopping cart and value of the quantity is
generated.
◦ Addition to the product
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9.  Simplest form of analysis: examine individual
or groups of activity.
 Advantages:
◦ Increase in sales of products.
◦ Increase in profitability.
 Drawbacks:
◦ LOTS of data.
◦ Difficult to generalize.
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10. Hardware requirement:
 Processor - Windows 7,8
 Speed - 1.1 Ghz
 RAM - 1 GB(min)
Software Requirement
 Front End - HTML, Java, Jsp(java server pages)
 Scripts - JavaScript.
 Server side Script - Java Server Pages.
 Database - Mysql 5.0
 Database Connectivity - JDBC.
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11.  Requirement Specification
 Literal survey
 Technology familiarization
 Start design
 Working on the application
 Preparing documentation
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12.  Web usage mining has emerged as the essential
tool for realizing more personalized, user-friendly
and business-optimal Web services.
 Traditionally, Web usage mining is used by e-
commerce sites and other organisations to
organize their sites and to increase profits.
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13. Thank you
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