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Update documentation

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This commit is contained in:
Eike Kettner
2021-01-20 21:35:54 +01:00
parent 85ddc61d9d
commit a6c31be22f
6 changed files with 206 additions and 93 deletions
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modules/joex/src/main/resources/reference.conf
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@ -286,16 +286,13 @@ docspell.joex {
# 4. disabled - doesn't use any stanford-nlp feature
#
# The full and basic variants rely on pre-build language models
# that are available for only 3 lanugages at the moment: German,
# English and French.
#
# Memory usage varies greatly among the languages. German has
# quite large models, that require about 1G heap. So joex should
# run with -Xmx1500M at least when using mode=full.
# that are available for only a few languages. Memory usage
# varies among the languages. So joex should run with -Xmx1400M
# at least when using mode=full.
#
# The basic variant does a quite good job for German and
# English. It might be worse for French, always depending on the
# type of text that is analysed. Joex should run with about 600M
# type of text that is analysed. Joex should run with about 500M
# heap, here again lanugage German uses the most.
#
# The regexonly variant doesn't depend on a language. It roughly
@ -349,25 +346,23 @@ docspell.joex {
# Settings for doing document classification.
#
# This works by learning from existing documents. A collective can
# specify a tag category and the system will try to predict a tag
# from this category for new incoming documents.
#
# This requires a satstical model that is computed from all
# existing documents. This process is run periodically as
# configured by the collective. It may require a lot of memory,
# depending on the amount of data.
# This works by learning from existing documents. This requires a
# satstical model that is computed from all existing documents.
# This process is run periodically as configured by the
# collective. It may require more memory, depending on the amount
# of data.
#
# It utilises this NLP library: https://nlp.stanford.edu/.
classification {
# Whether to enable classification globally. Each collective can
# decide to disable it. If it is disabled here, no collective
# can use classification.
# enable/disable auto-tagging. The classifier is also used for
# finding correspondents and concerned entities, if enabled
# here.
enabled = true
# If concerned with memory consumption, this restricts the
# number of items to consider. More are better for training. A
# negative value or zero means no train on all items.
# negative value or zero means to train on all items.
item-count = 0
# These settings are used to configure the classifier. If