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HCL Digital Experience Product Documentation
Welcome to the product documentation for HCL Digital Experience. Find information about how to install, configure, maintain, and use HCL Web Content Manager and HCL Portal Server, Enable, and Extend solutions.
HCL Digital Experience 8.5
Learn how to install, configure, troubleshoot, maintain, and use Version 8.5 of HCL Web Content Manager and HCL Portal Server, Enable, and Extend.
Setting up a website
Setting up a website includes, creating pages, adding navigation, setting up search, and adding content to the site. Themes are used to customize the portal's look-and-feel. Out-of-the-box templates and the site wizard can help you set up your portal site faster. You can add wikis and blogs to your site and let users tag and rate content on your site.
Setting up marketing campaigns
Use these tools and features to setup marketing campaigns for your website.
Personalization
Portal Personalization provides automatic customization of website content for individual users and user groups.
LikeMinds Recommendations
Personalization contains a dynamic recommendation system based on LikeMinds. LikeMinds is software that is used with your e-commerce applications. LikeMinds analyzes user interactions that occur on your Web site and generates real time predictions and recommendations to your Web site users.
Configuring LikeMinds
Use a suitable database modification tool or edit the likemindsdb.properties file to configure your LikeMinds server installation.
Configuring the LikeMinds engines
You can configure your LikeMinds recommendation engines to control aspects such as predictability, number of mentors used, which rating, transaction, or mentor set to use, and so on, for the recommendations returned.
Configuring the Preference Engine
The Preference Engine generates recommendations based on users' ratings of items. You can configure the following settings for the Preference Engine.
User predictability
This section contains the following information regarding user predictability.
Minimum number of ratings for user recommendations
Set <eng_instance_name>.engine.titan.predictable.min_ratings_cutoff to the minimum number of ratings a user must make before the Preference Engine will make recommendations for that user. The default is 2.

HCL Digital Experience Product Documentation
Welcome to the product documentation for HCL Digital Experience. Find information about how to install, configure, maintain, and use HCL Web Content Manager and HCL Portal Server, Enable, and Extend solutions.
- HCL Digital Experience 9.5
- HCL Digital Experience 9.5 [Legacy Content]
- HCL Digital Experience 9.0
  Learn how to install, configure, troubleshoot, maintain, and use Version 9.0 of HCL Web Content Manager and HCL Portal Server, Enable, and Extend.
- HCL Digital Experience 8.5
  Learn how to install, configure, troubleshoot, maintain, and use Version 8.5 of HCL Web Content Manager and HCL Portal Server, Enable, and Extend.
  - Overview
    HCL Digital Experience (formerly IBM WebSphere Portal and IBM Web Content Manager) empowers you to create, manage, and deliver engaging omnichannel digital experiences to virtually all audiences with responsive content, targeted offers, seamlessly integrated applications, and consistent branding across channels (web, mobile. and hybrid mobile/web applications and more).
  - Roadmaps to deploy your system
    Review the roadmaps to understand the common deployment, configuration, migration, and integration patterns.
  - Roadmaps to create your website
    Review the roadmaps to understand how to create your website.
  - Online Help
    This Online Help is made available in the HCL Digital Experience Help Center for quick references on how to install, configure, maintain, and use HCL Digital Experience.
  - Installing
    HCL Digital Experience provides flexible deployment options that range from proof-of-concept where you can examine and test functionality to a highly available and scalable production environment. Review the planning information to learn more about hardware and software requirements, high availability, scalability, supported topologies, and much more. Select your operating system and then select the installation pattern that most reflects your business needs.
  - Configuring
    Run the following tasks after you install and deploy HCL Digital Experience. They address tasks that are typically run one time and have a global effect. Some configuration changes are made more frequently or do not have a global effect. These tasks are addressed in the Administering section.
  - Backup and restore
    Backup and recovery of data files and databases is an essential operation for any business system, particularly for data and applications that run in production environments. Create and follow a plan for backing up and recovering data on all tiers of your HCL Digital Experience deployment. IBM Installation Manager must also be included in backup and recovery planning. If you back up the HCL Portal file structure and then install a fix pack, your HCL Digital Experience and IBM Installation Manager become out of sync after you restore the HCL Portal file system. This condition is not recoverable.
  - Migrating
    Successful migration requires significant planning and preparation, understanding the tools that are involved, and careful execution of the appropriate steps in the order provided.
  - Integrating
    Integrate HCL Digital Experience with software such as HCL Sametime to enable your users to collaborate more easily. You can also use the unified task list portlet to integrate HCL with your backend business process software, such as IBM Process Server.
  - Administering
    Use the administration tools that are provided with the portal to do various day-to-day administration tasks. There are two methods for editing portal setup: using the administration portlets or the XML configuration interface. The administration portlets are a convenient way to make real-time updates to the portal's configuration. While the XML configuration interface is suited to more advanced administration, including batch processing of updates.
  - Securing
    Security tasks include setting up property extension databases and custom user repositories, configuring and activating SSL, and configuring authentication. In addition, tasks such as activating Federal Information Processing Standards (FIPS) and NIST SP800-131a security modules and configuring external security managers such as Security Access Manager might be required to secure your portal environment.
  - Monitoring
    HCL Portal includes tools and features to help you monitor the portal site.
  - Setting up a website
    Setting up a website includes, creating pages, adding navigation, setting up search, and adding content to the site. Themes are used to customize the portal's look-and-feel. Out-of-the-box templates and the site wizard can help you set up your portal site faster. You can add wikis and blogs to your site and let users tag and rate content on your site.
    - Website building blocks
      Unless you are familiar with the HCL Digital Experience and HCL Web Content Manager website model, review the building blocks. Building blocks are the different parts that make up the website framework, such as pages, navigation, themes, content, content libraries, and more.
    - Creating reusable assets
      Use reusable assets to store or generate content that is used in more than one place in your website.
    - Building the website
      Building a website includes creating libraries, pages, and web content. You also create links and navigation to your content, and assign access to different types of users, such as editors and viewers.
    - Authoring tools
      There are multiple ways to create and manage content including using the site toolbar, inline editing, and the authoring portlet.
    - Preparing for content authors
      Before content authors can create content you must prepare your site to be ready for content creation, including preparing the site toolbar, enabling inline editing, and creating templates.
    - Developing and managing content
      Use these tools and processes to develop and manage your website.
    - Delivering web content
      The type of delivery method you use to deliver web content to your viewers depend on the type of content that is being delivered, and the type of viewers your website is intended for.
    - Vanity URLs
      You can associate vanity URLs with portal pages and labels. Vanity URLs are short URLs that people can easily remember. They are shorter than full HCL Portal URLs. They are sometimes also called marketing URLs. You can publish vanity URLs for marketing campaigns through different channels, such as email or print. This way, you can use vanity URLs to direct customers to a specific portal page or content item. Interested site visitors who want to view your campaign can then remember or copy the short vanity URL and type it into the browser address field.
    - Social rendering
      HCL Digital Experience page editors can use social rendering to feature social data that is hosted on a remote HCL Connections server in the context of portal pages.
    - Setting up marketing campaigns
      Use these tools and features to setup marketing campaigns for your website.
      - Personalization
        Portal Personalization provides automatic customization of website content for individual users and user groups.
        How a site is personalized
        Use this topic to understand how to define a personalized list of new articles for a website, such as a section of an intranet site for targeted employee bulletins or where the content of the site is tailored to the particular user.
        Personalization terms
        The concepts and principles for working with Portal Personalization require an understanding of terminology.
        The Personalization interface
        The Portal Personalization user interface consists of three portlets: the Personalization Navigator, Personalization Editor, and the Personalized List.
        Publishing personalization rules overview
        HCL Portal Personalization sends published rules across HTTP to a servlet which resides on each personalization server. This servlet can receive publishing data or initiate new publishing jobs. When a user begins a publishing job from the personalization authoring environment, the local servlet is provided with the set of information necessary to complete the job. The local servlet contacts the destination endpoint servlet (which could be the same servlet) and sends its data to it. The destination servlet reports success or failure.
        The Web Content resource collection
        The Web Content resource collection is installed and configured out of the box. This predefined collection allows you to write rules that select lists of content from HCL Web Content Manager. Rules specify which Web content to show in a Portal Personalization component in Web Content Manager.
        The Portal User resource collection
        Portal Personalization comes with a Portal User resource collection. This collection uses public APIs provided by HCL Digital Experience to access user information.
        LikeMinds Recommendations
        Personalization contains a dynamic recommendation system based on LikeMinds. LikeMinds is software that is used with your e-commerce applications. LikeMinds analyzes user interactions that occur on your Web site and generates real time predictions and recommendations to your Web site users.
        LikeMinds Recommendation Engine architecture
        Get an overview of the functioning and architecture of the LikeMinds Recommendation Engine. In order to build your own recommendation application you need to customize the LikeMinds Recommendation Engine settings to work with your database and Web applications.
        How LikeMinds generates recommendations
        Learn how LikeMinds generates recommendations when a user logs on and navigates through your web site.
        The LikeMinds Recommendation Engines
        LikeMinds Recommendation Engines communicate with a relational database and generate recommendations. Learn about the three types of recommendation engines, Preference engine, Clickstream engine, and Item Affinity engine.
        The LikeMinds utilities
        Get an overview of sifter, buildstats, buildvisit, and accumulator, the utilities that support running of background processes along with the LikeMinds server.
        Configuring LikeMinds
        Use a suitable database modification tool or edit the likemindsdb.properties file to configure your LikeMinds server installation.
        Estimating database size
        The size of your database depends on your application, as well as the number of users and items. View some general guidelines for estimating the size of your database, but your results may vary.
        Database performance
        View some guidelines for performance optimization in your LikeMinds database.
        Scheduling LikeMinds Events
        Use the lps.schedule setting to schedule events to be fired at specific dates and times.
        Configuring the LikeMinds engines
        You can configure your LikeMinds recommendation engines to control aspects such as predictability, number of mentors used, which rating, transaction, or mentor set to use, and so on, for the recommendations returned.
        Configuring the Preference Engine
        The Preference Engine generates recommendations based on users' ratings of items. You can configure the following settings for the Preference Engine.
        Number of mentors to use
        Set <eng_instance_name>.db.engine.tune.num_mentors to the maximum number of mentors to assign to a given user. The default is 50.
        Mentors to look for in cache
        If a user requests recommendations before the sifter has found mentors for that user, the Preference Engine checks the cache for mentors for the user. Set <eng_instance_name>.db.engine.tune.max_cached_mentors to the number of potential mentors which it should consider for a given user. The default is 500.
        Use of "average user" to improve recommendation confidence
        The Preference Engine can use an "average user," whose ratings are the average of all users' ratings. The buildstats utility computes the average ratings.
        Use and number of archetypes
        To generate recommendations for items that no mentors have rated, the Preference Engine uses synthetic users called "archetypes." These users possess a particular characteristic very strongly.
        Guidelines for configurable recommendation dynamics
        You can use the following configuration parameters to control, or at least balance, effects of external factors.
        Setting the number of archetypes in cache
        The list of archetypes is kept in the cache for a specified number of uses before it is reloaded. To change the number of users, set <eng_instance_name>.db.engine.tune.max_archetype_list_use. The default is 100000.
        Enabling or disabling the use of archetypes
        To turn on or off the use of archetypes, set <eng_instance_name>.db.engine.tune.consult.archetype_for_list to true or false. The default is false.
        User predictability
        This section contains the following information regarding user predictability.
        Maximum number of mentors assigned to each user
        Use the following setting to specify the number of mentors to be assigned to each user. The number of actual mentors can be less than the maximum setting but never greater than the value specified.
        Maximum ratings a user needs before becoming a mentor
        The following setting specifies the maximum number of ratings a user can have to become a mentor. The sifter uses this setting if the Preference Engine is using that mentor set.
        Maximum transactions a user needs before becoming a mentor
        The following setting specifies the maximum number of transactions a user can have before becoming a mentor. The sifter uses this setting if the Purchase or Clickstream Engine is using that mentor set.
        Minimum number of ratings for user recommendations
        Set <eng_instance_name>.engine.titan.predictable.min_ratings_cutoff to the minimum number of ratings a user must make before the Preference Engine will make recommendations for that user. The default is 2.
        Recomputing Preference Engine predictions
        The <eng_instance_name>.engine.titan.recomputation_bound configuration parameter specifies the percentage change allowed in a user's ratings before the LikeMinds server recomputes the user's predictions.
        Default Preference Engine recommendations
        The Preference Engine reads the value from the score field in the Lps_Item_Data table to determine which items are popular. Hence, a higher score means that the item is more popular.
        Configuring LikeMinds utilities
        You can configure the following settings for the buildstats and buildvisit background utilities.
        Configuring the Clickstream Engine
        The Clickstream Engine generates recommendations based on a record of user shopping behavior as the user navigates through a Web site; that is, a history of user "clicks" during the user's website visit. It uses data such as the items the users view, click, and add to their shopping carts.
        Configuring the Item Affinity Engine
        For every cross-selling transaction in the user's shopping history, the Item Affinity Engine derives its calculations from the following statistics
        Specifying recommendation behavior
        You can configure several parameters that affect the way the LikeMinds server generates recommendations.
        MovieSite Sample
        The MovieSite documentation focuses on six aspects of LikeMinds capabilities.
        Using the LikeMinds utilities
        Learn about the four utilities LikeMinds uses to update the database, buildvisit (for the Preference Engine), sifter, buildstats, and lpsIAA (for the Item Affinity Engine's accumulator utility).
        Filtering LikeMinds recommendations
        When LikeMinds makes recommendations, it can make the recommendations based on all items in your resource collection, or it can limit the predictions to only items that have certain characteristics.
        Feedback and analytics
        Personalization provides a complete logging framework for collecting data on how visitors are using your Web site. If Feedback is enabled, data is automatically collected about each Personalization rule that is fired. In addition, development tools enable websites to collect a variety of data related to visitors' actions and behavior. By default this data is logged to a standard database schema for later analysis and reporting. The framework is also extensible, allowing websites to customize and supplement the way data is collected and stored to more fully meet their needs.
        Developing a personalized portlet
        This exercise demonstrates how to use Personalization features of HCL Portal and Rational Application Developer to build your first personalized portlet. Your final result is a working portlet that uses Personalization rules and content spots to display personal news based on user attributes (or profiles).
        Personalization programming reference
        HCL Digital Experience provides the programming model, processes, and APIs for the Personalization rules and resource engines.
        Personalization APIs
      - Social Media Publisher
        The Social Media Publisher for HCL Web Content Manager is an extension to HCL Web Content Manager that allows businesses to promote their web content on social networks, and provide some basic statistics about the promoted content.
    - HCL Web Content Manager Multilingual Solution
      The HCL Web Content Manager Multilingual Solution is a set of tools that are used to manage translated versions of localized and regionalized websites.
    - Syndicated Feed Portlet
      The Syndicated Feed Portlet for HCL Digital Experience offers enhanced feed subscription and presentation capabilities.
  - Staging to production
    During portal solution development, the solution is initially developed, tested, and refined on one server or a limited number of servers. The solution is deployed later on live systems, referred to as the production environment. The process of moving the solution from the development environment to the production environment is called staging.
  - Developing
    This section includes developer documentation on extending applications and development assets for HCL Portal and HCL Web Content Manager.
  - Troubleshooting
    This section helps you resolve problems, use diagnostic tools and tracing to capture HCL Digital Experience system errors.
  - Reference
    View information that can help you use the Digital Experience Help Center including directory conventions, terms of use, trademarks, a glossary, and more.
  - Glossary
    This glossary includes terms and definitions for HCL Digital Experience.
  - Content Template Catalog 4.4
    The Content Template (CTC) is a set of templates that accelerate the process of building a website.

Minimum number of ratings for user recommendations | HCL Digital Experience

Set <eng_instance_name>.engine.titan.predictable.min_ratings_cutoff to the minimum number of ratings a user must make before the Preference Engine will make recommendations for that user. The default is 2.

For example:

movie_pref.engine.titan.predictable.min_ratings_cutoff = 3