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new b38e440 Update docs.html
b38e440 is described below
commit b38e4409e4c885fbd95e5bc094395042f3de5d47
Author: Aaron Radzinski <[email protected]>
AuthorDate: Sun Mar 21 20:00:20 2021 -0700
Update docs.html
---
docs.html | 22 ++++++++++++----------
1 file changed, 12 insertions(+), 10 deletions(-)
diff --git a/docs.html b/docs.html
index 000203f..06408d6 100644
--- a/docs.html
+++ b/docs.html
@@ -27,21 +27,23 @@ id: overview
<p>
Apache NLPCraft is a Java-based <a target=_blank
href="https://www.apache.org/licenses/";>open source</a> library
for adding a natural language interaction interface to any
applications. It can connect with
- any private or public data source, and has no hardware or software
lock-in. It is based on advanced intent-based matching
+ any private or public data source, and has no hardware or software
lock-in. Its design based on advanced
+ <a href="/intent-matching.html">Intent Definition Language</a>
(IDL) for defining non-trivial intents and unique fully deterministic intent
matching
of the input utterances. You can build intents for NLPCraft using
any JVM-based languages like Java, Scala, Kotlin, Groovy, etc. NLPCraft
exposes REST APIs for integration with end-user applications that
can be written in any language or system.
</p>
<p>
- One of the key features of NLPCraft is its use of deterministic
intent matching that is tailor made for
- domain-specific natural language interface. It doesn't force
developers to use direct deep learning
- approach that involves time consuming model training or corpora
development - resulting in much <em>simpler <span class="amp">&</span>
faster</em>
- implementation.
+ One of the key features of NLPCraft is its use of IDL coupled with
deterministic intent matching that are tailor made for
+ domain-specific natural language interface. This design doesn't
force developers to use direct deep learning
+ approach with time consuming corpora development and model
training - resulting in much a
+ <em>simpler <span class="amp">&</span> faster</em> implementation.
</p>
<p>
Another key aspect of NLPCraft is its initial focus on processing
English language. Although it may sound
counterintuitive, this narrower initial focus enables NLPCraft to
deliver unprecedented ease of use combined with
unparalleled comprehension capabilities for English input
out-of-the-box. It avoids watered down functionality and overly
- complicated configuration, training and usage. English language is
spoken by more
+ complicated configuration and usage - following on project's
"built for engineers by engineers" ethos.
+ English language is spoken by more
than a billion people on this planet and is de facto standard
global language of the business and commerce.
</p>
<p>
@@ -63,16 +65,16 @@ id: overview
<section id="data-model">
<h3 class="section-title">Data Model</h3>
<p>
- NLPCraft employs model-as-a-code approach where entire data model
is an implementation of
+ NLPCraft employs model-as-a-code approach where everything you do
in NLPCraft is part of your source code. Data model is an implementation of
<a target="javadoc"
href="/apis/latest/org/apache/nlpcraft/model/NCModel.html">NCModel</a> Java
interface that
can be developed using any JVM programming language like Java,
Scala, Kotlin or Groovy.
- Data model defines named entities, various configuration
properties as well as intents that use defined named entities. Model-as-a-code
natively supports
+ Data model defines named entities, various configuration
properties as well as intents to interpret user input. Model-as-a-code natively
supports
any software lifecycle tools and frameworks in Java ecosystem.
</p>
<p>
Typically, declarative portion of the model will be stored in a
separate JSON or YAML file
for simpler maintenance. There are no practical limitation on how
complex or simple a model
- can be, or what other tools it can use. Data models use
comprehensive <a href="/intent-matching.html">intent-based matching</a>.
+ can be, or what other tools it can use. Data models use <a
href="/intent-matching.html">intents</a> to match the user input.
</p>
<p>
To use data model it has to be deployed into a data probe.
@@ -81,7 +83,7 @@ id: overview
<section id="data-probe">
<h3 class="section-title">Data Probe</h3>
<p>
- Data probe is a light-weight container designed to securely deploy
and manage data models.
+ Data probe is a light-weight container designed to securely deploy
and manage user data models.
Each probe can deploy and manage multiple models and many probes
can be connected to the REST server (or a cluster of REST servers).
The main purpose of the data probe is to separate data model
hosting from managing REST calls from the clients.
While you would typically have just one REST server, you may have
multiple data probes deployed
