Explore Movie Site - Personalization

Explore Movie Site

Movie Site demonstrates the LikeMinds Recommendation Engine, guiding us through a Personalization scenario that is based on factual data from a popular site on the internet. The website uses a personalization solution to analyze visitor behavior and to recommend individualized content information and services while the visitor is actively engaged on the site.

The provided Resource Collections are for IBM DB2 Universal Database Enterprise Server Edition and DB2 for z/OS only. To use the sample on other database types, we can regenerate them using RAD. For information about Resource Collections, see the topic Resources, resource instances, and resource collections.

It is assumed that we are the Movie Site user, likeminds. This user has previously rated some movies and registered preferences as configured in the installation.

To set up the Movie Site sample, choose the appropriate option:

AIX SolarisLinux: ./ConfigEngine.sh cfg-likeminds-samples -DWasPassword=foo -DLikemindsDbPassword=foo

Windows: ConfigEngine.bat cfg-likeminds-samples -DWasPassword=foo -DLikemindsDbPassword=foo

IBM i: ConfigEngine.sh cfg-likeminds-samples -DWasPassword=foo -DLikemindsDbPassword=foo

Check the output for any error messages before proceeding with the next task. If any of the configuration tasks fail, verify the values in the wkplc.properties file.
Start the application:

Open the WebSphere Integrated Solutions Console.

Go to http://machine:port_number/ibm/console where port_number is the port number for HCL WebSphere Portal.

Click Applications > Application Types > WebSphere enterprise applications.

Select Movie Site Application, and click Start.

Rate movies using the Movie Site home page.

Step number Description Action to be taken
1 Navigate to the Movie Site Home Page.
For this demo we will concentrate on the recommendation engine which uses mathematical algorithms to provide collaborative filtering.
Open a separate browser window to the Movie Site home page. The URL is http://hostname:port/MovieSite where port is the port number for HCL WebSphere Portal
2 Log in as the LikeMinds user.
Log on as the user, likeminds. This login name is the default user who has registered to the site and has rated some movies.

Type likeminds in the login field.

Type likeminds in the password field

Click Enter.

3 Sample previous ratings.
Look at the movie ratings by selecting Sample Previous Ratings. This section of the site contains a few sample movie ratings the user likeminds previously placed.

Click Sample Previous Ratings.

Select Get more movies from the menu.

Click the To Lobby icon.

We can show all of the movies or just certain rated movies by selecting one of the ratings. We can look at the ratings of other movies by clicking Get More Movies. This demo allows us to rate movies. For more movies, type the name of a movie into the search panel to see if specific movies are stored in the database.
4 Use the SuperRater to rate a movie.
In Super-Rater mode, clicking the drop-down menu associated with each movie of the movie reveals a rating choice.
We can rate any movies on the list and click Submit to log the rating choice.
If you click the movie title it will link us to information about the movie using the imdb.com site.
Notice the prediction of the recommendation engine of how much you, as the LikeMinds login user, would like this movie.

Click To Lobby.

Click Rate more movies.

Click Turn on Superrater.

Click the dropdown menu associated with the rating to see the options.

Click Movie title.
This opens a new window.

5 End demonstration. Click To Lobby.

The LikeMinds collaborative filtering technology considers each user to be the center of their own preference cluster, instead of trying to find the best preordained preference category for every user, which is typical of profile-based approaches. LikeMinds recommendations can adapt to these changes much more quickly than aggregated, profile based techniques.
Choose the appropriate task to remove the application:

Windows: ConfigEngine.bat remove-likeminds-samples -DWasPassword=foo -DLikemindsDbPassword=foo

AIXSolarisLinux: ./ConfigEngine.sh remove-likeminds-samples -DWasPassword=foo -DLikemindsDbPassword=foo

IBM i: ConfigEngine.sh remove-likeminds-samples -DWasPassword=foo -DLikemindsDbPassword=foo

Check the output for any error messages before proceeding with the next task. If any of the configuration tasks fail, verify the values in the wkplc.properties, wkplc_dbdomain.properties, and wkplc_dbtype.properties files.

Parent: MovieSite Sample

Step number	Description	Action to be taken
1	Navigate to the Movie Site Home Page. For this demo we will concentrate on the recommendation engine which uses mathematical algorithms to provide collaborative filtering.	Open a separate browser window to the Movie Site home page. The URL is http://hostname:port/MovieSite where port is the port number for HCL WebSphere Portal
2	Log in as the LikeMinds user. Log on as the user, likeminds. This login name is the default user who has registered to the site and has rated some movies.	Type likeminds in the login field. Type likeminds in the password field Click Enter.
3	Sample previous ratings. Look at the movie ratings by selecting Sample Previous Ratings. This section of the site contains a few sample movie ratings the user likeminds previously placed.	Click Sample Previous Ratings. Select Get more movies from the menu. Click the To Lobby icon. We can show all of the movies or just certain rated movies by selecting one of the ratings. We can look at the ratings of other movies by clicking Get More Movies. This demo allows us to rate movies. For more movies, type the name of a movie into the search panel to see if specific movies are stored in the database.
4	Use the SuperRater to rate a movie. In Super-Rater mode, clicking the drop-down menu associated with each movie of the movie reveals a rating choice. We can rate any movies on the list and click Submit to log the rating choice. If you click the movie title it will link us to information about the movie using the imdb.com site. Notice the prediction of the recommendation engine of how much you, as the LikeMinds login user, would like this movie.	Click To Lobby. Click Rate more movies. Click Turn on Superrater. Click the dropdown menu associated with the rating to see the options. Click Movie title. This opens a new window.
5	End demonstration.	Click To Lobby.