Angoss and Lexalytics Text Analytics - Angoss Software Corporation

Angoss and Lexalytics
Lexalytics builds a text analysis engine that’s
entirely purposed for OEM integration into your
application or service. For 9 years, we’ve been
refining and improving our engine: “Salience”.
Organizations have historically used predictive
Salience analytics is a multi-lingual to analyze and text model analysis based engine on their that
is currently proprietary, integrated structured into systems data (like for transactional business
intelligence, data, CRM (social) data media etc.). Text monitoring, analytics reputation allows
management, organizations automated expand trading, the types survey and analysis, volume
customer of data satisfaction, used for advanced and more. analytics to include
unstructured, text-based data—whether
Salience integrates painlessly with your BI/
proprietary (like email communications,
dashboard/ analytics or data warehouse system,
CRM notes, claims) or from the Web (like
social media from Tweets, blogs, forums).
Lexalytics and Angoss have partnered
to advance big data analytics and the
accuracy of predictive modeling by
increasing the types and volume of
data that can be analyzed to include
text-based, unstructured data.
These enhanced capabilities are
available in Angoss’ Text Analytics
for KnowledgeSTUDIO®—powered
and works “right out of the box”, quickly adding
value by Lexalytics’ to your business text and – letting sentiment you focus on
building analysis your engine. service and not on the technical
details of text analytics.
The addition of more data types (and volume)
We allows don’t for believe more accurate in black modeling boxes, so resulting every parameter
is from available additional for you predictive to tune variables. and optimize. Put
simply, The ability Salience to mine has and the analyze strength unstructured, to analyze the
entire text-based blogosphere, data and apply the subtlety predictive to look for slight
trends techniques in confidential allows organizations records, and to discover the flexibility
for insights completely and customer novel problems. intelligence Unlike previously other text
analytics unavailable companies to them—in – Lexalytics doing so they focuses uncover on your
application, new opportunities not ours. to increase sales and
profitability via faster, better decision making.
Expand Your Analytical Insights
In order to gain greater insight from text mining
and unstructured data analysis, the output of text
analysis should be combined with your structured,
proprietary data.
The results of text analytics can be
used to build strategies around:
• Customer retention
• Cross-sell and upsell
• Demand generation
• Next-best-offer
• Claims fraud reduction
• Customer service routing
• Warranty analysis
KnowledgeSTUDIO allows you to merge the
output of text analytics with your structured data
to perform data mining and predictive analytics
with additional predictive variables for improved
accuracy—expanding your predictive and
exploratory power.
Angoss’ Text Analytics for KnowledgeSTUDIO
provides outstanding productivity and efficacy by
generating a data mining view that combines text
mining results with unstructured data in a single
environment. This is powered by data preparation
wizards used to join, aggregate, and append
datasets, as well as remove duplicates.
From this single environment users can extract
entities and themes, analyze and score associated
sentiment, visualize relationships and prepare
unstructured text output for use in advanced
predictive models.

Lexalytics Salience Engine provides the text
analytics functionality behind Angoss’ Text
Analytics for KnowledgeSTUDIO. Text analytics
is the ability to parse unstructured language and
extract meaning. Salience provides 4 key areas of
functionality in the Text Analytics add-on: Named
Entity Extraction, Sentiment Analysis, Theme
Extraction and Summarization.
Named Entity Extraction p
Named Entity Extraction is the ability to recognize
“who” is being talked about in a piece of text.
Lexalytics supports 5 different methods for
extracting Named Entities from your text. Named
Entities are important in that our software will
then go on to calculate other metrics to go along
with the Entity - things like the Entity’s Sentiment
score, or the associated Themes. Salience has been
trained to automatically start extracting People,
Places, Companies, Products, URLs, Phone
Numbers, and more. You don’t have to configure
anything. However, there is a ton that you can
configure if you want to improve upon what the
system does automatically.
Sentiment Analysis
Sentiment scoring allows a computer to consistently
rate the positive or negative assertions that are
associated with a document or entity. Lexalytics has
been dealing with mechanical analysis of sentiment
for over ten years now, across a wide variety of
different kinds of text. Sentiment is completely
tunable by the user to produce optimal accuracy for
their particular application.
Theme Extraction p
Themes are noun phrases with contextual relevance
scores. Differently put, they are the “what” people
are saying about the “who” that was produced
with Named Entity Extraction. As an example, the
sentence “Joe’s Craft Beer just launched a new
beer” would yield the theme “new beer”. So, you
could see the entity (Joe’s Craft Beer) and it’s
associated theme (new beer). Great for finding
patterns in language in content like warranty or
insurance claims, or to see the language that people
are using to describe a product.
Summarization p
Summarization provides the most important
sentences in a piece of text – useful for scanning
through the content of a number of documents that
have been processed to get a “human” feel for them.
Technical Requirements
Available for use on Windows and Red Hat Linux
platforms. 64-bit; 4GB RAM.
Angoss Software Corporation
111 George Street, Suite 200
Toronto, Ontario M5A 2N4 Canada
1-866-687-8838
www.angoss.com
info@angoss.com
Lexalytics Inc.
101 University Drive, Suite A3
Amherst, MA 01002
800-377-8036
lexalytics.com
sales@lexalytics.com
© Copyright 2012