If your knowledge base is an external knowledge base with LivePerson AI or an internal knowledge base (which also uses LivePerson AI), it makes use of Natural Language Understanding or NLU to evaluate the articles against the consumer's utterance (the intent) in order to return the highest scoring article.

To set this up, you create a domain with the necessary intents in Intent Manager, where the domain specifies the NLU engine to use. Then, within the Knowledge Base application, you 1) associate the domain with the knowledge base, 2) associate the domain's intents with the articles, and 3) train the knowledge base to use the intents to return the articles.

Intent Manager offers a set of prebuilt domains. These are designed to get you up and running quickly with intents.

Associate a domain with a knowledge base

You associate a domain with an external knowledge base when you add the knowledge base:

And you likewise associate a domain with an internal knowledge base when you add the knowledge base:

Associating the domain gives you access to the domain's intents, so you can associate them with the articles. This is the next step in connecting your content to intents.

When you are adding the knowledge base, take care when selecting the domain. You can't change the domain after adding the knowledge base.

Associate intents with articles

After you've added a knowledge base that is associated to a domain, configure the articles so that each is linked to the appropriate intent.

You don’t need to link your articles to intents right away, as the Intent field is optional. This is deliberate because it allows you to get started with a knowledge base by adding just the articles first. Then, you can create intents for the content you care about the most, and link those to the relevant articles. This means you can focus on specific content areas in your knowledge base, and manage the content overall with varying levels of effort on your part. The approach gives you flexibility as you maintain the knowledge base over time.

Tune a knowledge base

After you've added your content and linked it to intents, tune the knowledge base. Tuning involves:

  1. Performing a search using a consumer utterance.
  2. Reviewing the results.
  3. Adding or removing training phrases in the intents as needed.

To tune a knowledge base

  1. Open the knowledge base.
  2. In the Question Tester on the right, specify the following:

    • Question: Enter the consumer utterance for which you want to find matching articles.
    • Search Mode: Select the type of search to perform. For explanations of each search mode, see Search modes farther below in this topic.
    • Confidence: Select the NLU confidence threshold that an article must meet for it to be returned as a result. For more on thresholds, see Scoring and thresholds farther below in this topic.
    • # of Results: Select how many results to return.
    • Article Status: Select the status of the artice, either Active, Inactive, or All. This option is only available for internal knowledge bases.
  3. Click Find Answer.
  4. Review the results under Matched Answers.

  5. You can click on an article title to see the article, and toggle between this and its JSON.

  6. Based on the results, adjust the training phrases for the intents in the associated domain if needed.

Search modes

A knowledge base search is performed using a specified "search mode." The search mode determines the type of search. Possible modes include:

  • Intents
  • Intents Only
  • Text

Intents mode

When the Intents mode is used, an exact match, text-to-text search is performed first. If a match isn't found by the first search, Knowledge Base next uses Natural Language Understanding (NLU) algorithms to match the consumer input to articles. And if a match isn't found by the NLU search, a final, text-to-text search is performed as a fallback.

Intents Only mode

The Intents Only mode is like the Intents mode (above) except that the final, text-to-text search isn't performed as a fallback.

Text mode

When the Text mode is used, a text-to-text search is performed:

You can improve the quality of your knowledge base answers by linking your articles to intents and performing intent-based searches. However, often this change is introduced gradually, as time and opportunity allow. Typically, Text searches are used when you haven’t yet linked your articles to intents.

Be aware that, when a Text search is performed, if a match for the search phrase is found, the associated confidence score is reduced to FAIR_PLUS if either of the following is true:

  • The search phrase has less than three (3) words.
  • The search phrase and the stored content don’t have matched words in sequence (with two deviations).

Therefore, if you’re using a Text search, LivePerson recommends that you test and tune the knowledge base using a threshold of FAIR_PLUS. If you aren’t satisfied with the results, increase the threshold to GOOD.

Scoring and thresholds

When the Knowledge Base uses Natural Language Understanding (NLU) algorithms to evaluate a consumer's input against a knowledge base, it scores the articles based on the confidence level of the match: VERY GOOD, GOOD, FAIR PLUS, FAIR or POOR.

If the knowledge base is… Then…
an external knowledge base with LivePerson AI the scoring breakdown for the NLU engine used by the associated domain is used
an internal knowledge base with Domain intents the scoring breakdown for the NLU engine used by the associated domain is used
an internal knowledge base with Knowledge Base intents (intent qualifiers) the scoring breakdown for LivePerson (Legacy) is used

For these confidence score breakdowns, see here.

When you implement a knowledge base search within a bot via a Knowledge AI interaction, you specify the minimum score that a result must have in order to be returned. You can select from VERY GOOD, GOOD or FAIR PLUS. The default value is GOOD. If you downgrade the threshold to FAIR PLUS, be sure to test whether the quality of the results meets your expectations. It's generally recommended to keep the quality above FAIR PLUS.