3. Classification Analysis
Classification Analysis is a well-organized rule for achieving significant and relevant information regarding the data, and metadata. The classification analysis assists in distinguishing to which of a set of categories different types of data belong [6]. Classification analysis is closely connected to cluster analysis as the classification can be applied to cluster data.
A well-known example of classification analysis is the email provider; they use algorithms that are proficient of classifying your email as authorized or label it as spam. This is performed on the basis of the data which is associated with the email or the information that is within the email, for instance, specific words or attachments that designate
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It is the procedure of initialising the customized experience for the user of a website.The visitors are associated with the tailored need and desires by the website to give them unique experience [11]. Examples of web personalization are as follows:
1. Greet user by name
2. Remember their last shopping
3. Remember preferred shipping address and credit card’
4. Change home page and image
5. Change links
There are many types of web personalization which contains:
6. Behavioral
7. Contextual
8. Technical
9. Collaborative filtered
10. Historic data Figure 1.5: Personalized web resources for user
Preference-based personalization
It is task of monitoring the activity of a web site user through successive visits to the site. It is based on a model of the user's interests created from the information accumulated.
The software analyzes the content of pages viewed by the user, and through the application, e.g. neural net technology, and complex algorithms, develops a user profile. Based on this profile, content that is similar to pages previously visited are suggested to the user during future sessions. This technology constantly monitors the user’s behavior, and thus provides continuously updated user