Find the Likelihood of Existing Answers

When you add new questions to your Answer Bank Agentstore, you can find out whether there are any likely answers in your existing question equivalence classes.

The answer likelihood score field for a particular question stores the likelihood that there is an existing answer. Answer Server uses the question text to query your question equivalence classes, and uses the relevance score of each question equivalence class that returns in the query to calculate the likelihood score.

You can use this score to sort questions by likelihood in the GetResources action. See GetResources.

Periodically, Answer Server runs a background process to calculate the likelihood scores for all the questions in the Answer Bank Agentstore that do not have an answer, and updates the field for those questions.

By default, this process runs every 600 seconds (ten minutes). You can use the UpdateLikelihoodInterval configuration parameter in your Answer Bank system configuration to change how frequently to update the likelihood score field.

You can update the field more frequently if you need up-to-date information to sort by likelihood. However, for performance reasons HPE recommends that you do not update the likelihood score field too frequently, because it might result in a large number of indexing operations in the Answer Bank Agentstore component.

You can set UpdateLikelihoodInterval to a higher value if your question equivalence classes do not change very often, or if do not intend to use the likelihood scores very often.

For more information about UpdateLikelihoodInterval and the GetResources sort options, refer to the Answer Server Reference.

Find the Likely Answers to a Question

You can use the GetResources action to filter the list of question equivalence classes to those that are likely to provide an answer for a particular question or set of questions, by using the likely_answer_for filter. This filter matches question equivalence classes where the answer is most relevant to the specified questions.

For example:

action=GetResources&type=question_equivalance_class&filter={ "likely_answer_for": [ {"ids":[ "2373534828452857425" ], "resource_type":"question"} ] }

For more information, refer to the Answer Server Reference.


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