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Text and Web Analytics (Text Mining Application Area ( Information…

- - - - depends not only on definition of
        term but also on the context used
    - - eg analysis of free-form text found in
        e-mails and recorded telephone transcripts
    - - eg grammar ambiguity
    - - eg foreign accents
    - - understanding themeaning of words (i.e. book = to reserve vs book = a manual)
    - - e.g.customer, cust, customar, csmr
- - - - data stored in server access logs, referrer logs, agent logs, and client-side cookies
      - User characteristics and usage profiles
      - metadata, such as page attributes, content attributes, and usage
        data
- - - - Improve usability of web site - decrease the average no.of pages visited by a customer before a purchase transaction
      - Personalize web pages for customers
      - Determine products for sale at a web site that tend to be purchased or viewed together
  - - - 1st issue: Differentiate individual user session
        
        Host addresses are not useful because multiple users may access a site from the same host
        
        May be able to differentiate different user sessions
        by combining host addresses with the referring
        page
        
        Best able to differentiate user sessions if cookies
        (data files are allowed to be placed on users’
        computers to contain session information
      - 2nd issue: Identify unwanted log file entries
        
        A single user page request oftentimes
        generates multiple log file entries from several
        types of servers (e.g. image servers)
        
        Must have a technique to identify unwanted log
        file entries so that they do not become part of
        the session file
      - 3rd issue: Data transformation
        
        New attributes can be added to user session records to improve prediction of outcome
        
        Examples: 1. Average purchase amount of repeat customers
        
        Time of most recent transaction
  - - - Usage profiles for clusters
      - Form clusters of similar user session instances to personalise pages viewed by web site users
  - - - Set up online advertising promotions
      -  Send e-mail to promote products of likely interest to a select group of registered customers
      -  Modify content of a Web site by grouping products likely to be purchased together
    - - Adapt the indexing structure of a Web site to better reflect the paths followed by typical users and the changes in needs of users over time
    - - Implement strategy to personalize web pages
      - • Manual : force users to register at web site
      - • Data mining to automate personalisation based on actual user behaviour