Fusion AI 4.1.1 Release Notes
Release date: 7 November 2018
See also the Fusion Server 4.1.1 release notes.
Improvements
-
Phrase Extraction job improvements
-
The job now trims low-confidence phrases based on likelihood.
-
The job adds a
review
tag on the result to facilitate the review process based on beginning and ending POS and likelihood. -
The output now connects phrase tokens with an underscore (
_
) to make a single token per phrase so that complete phrases can be used as facets. -
New metadata fields:
-
phrases_count
shows how many times the phrases appear in the documents. -
word_num
shows how many words are in the phrase.
-
-
This release includes optimizations to the default Lucene analyzer configuration.
-
Output names are updated for clarity, such as
llr
tolikelihood
andngram
tophrases
.
-
-
The Head/Tail Analysis job now processes large data sets twice as fast.
-
The Ranking Metrics job now correctly accepts values for the
queryPipelines
property in the Fusion UI.
-
The Solr Query pipeline stage has two new properties to configure signals:
-
responseSignalsEnabled
Disable this option to prevent the stage from generating a response signal containing metadata about the response from Solr.
Response signals are used by App Insights and experiments.
In auto-complete pipelines, disable this option to avoid generating a response signal for each keystroke. -
excludeResponseSignalMatchRules
If
responseSignalsEnabled
is "true", then you can prevent generating a response signal based on specific parameters in the query, such as to enable response signals in general but to disable them for auto-complete queries.
-
Other changes
-
The Spark driver now cleans up
$FUSION_HOME/var/spark/Spark-workDir-*
directories and shaded jars correctly on Windows to prevent excessive disk consumption.
-
For installations that were upgraded from 3.1.x to 4.1.0, upgrading to 4.1.1 resolves an issue that prevented successful signal aggregations with the Parameterized SQL Aggregation job.