Learn five creative ways that text analytics can be used to deliver compelling search solutions.

1. Five Creative Search Solutions
using Text Analytics
Joe Hilger, Principal at Enterprise Knowledge

2. EK Search Best Practices
• Three primary types of search: find, discovery and
legal. Determine which type best fits your needs.
• Facets are the most important feature of search.
Properly designed facets solve most search relevancy
problems.
• Search is a means to an end. Each result type should
be designed to support the action the person is
trying to accomplish.
• Search is most powerful when it is used to
summarize and query information.
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3. Methods of Text Analytics
Method Description
Natural Language
Processing
Tools using sentence structure to understand
context and identify people, places and things
within text.
Entity Recognition Identification of people, places and things through a
combination of pattern matching, dictionaries and
graph databases.
Statistical Algorithms Statistical models to identify the unique topic of a
piece of content within a larger corpus of
documents.
Pattern Recognition Extraction of information based on the structure of
the document or information within the document.
Auto-categorization The use of any of the above methods to
automatically associate content with a pre-defined
taxonomy.
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4. #1. Contract Analysis
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The Problem:
A large government agency needs to
understand how much money they spend on
different software applications. Unfortunately,
software is bought by decentralized business
units and purchased through larger contract
vehicles.
The Solution:
Use Text Analytics to read contracts and
extract vendor names, software product
names, contract amounts, and the begin and
end date for the contract. This information can
be used to create an analytics based search
solution that shows charts and graphs of
spending on software products.

5. #1. Contract Analysis - Results
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6. #2. Company Information Search
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The Problem:
A financial news provider needs to create a
more compelling search for their paid
subscribers. Subscribers need consolidated
information about companies that is easy to
find.
The Solution:
Use text analytics to build a database of every
company mentioned in the article, newsletters,
financial reports and analyst reports. This
database is indexed by the search engine and
the companies are exposed in the type ahead
list and as a quick answer in search.

7. #2. Company Information Search - Results
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8. #3. Medical Research Search
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The Problem:
A medical researcher needs to understand the
most commonly recommended treatments for
diseases. They have access to hundreds of
thousands of medical journal articles, but no
way to summarize the information without
reading every article.
The Solution:
A text analytics tool identifies diseases,
treatments, diagnostic methods and symptoms
from within every article stored in the medical
database. The frequency in which each
disease and the recommended treatment are
found in the articles is displayed in search
results.

9. #3. Medical Research Search - Results
8http://pairs.demo.marklogic.com/

10. #4. Publishing Knowledge Base
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The Problem:
People want to understand where research is
being done on medical topics that are
important to them. A scientific and technical
publisher had a large corpus of information
that would make this possible if the content
could be summarized.
The Solution:
The publisher uses a text analytics tool to
identify the location, author, date and
institution responsible for publishing the
article, or publication. They developed a
search that showed all of this information
based on the location where the content was
published.

11. #4. Publishing Knowledge Base - Results
10http://authormapper.com/

12. #5. Improved Knowledge Sharing
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The Problem:
Science.gov was created in order to better
disseminate scientific information to the
American public. Science.gov had access to
hundreds of thousands of articles, but needed
to find a way to make the information easier to
find and understand.
The Solution:
Use statistical text analytics to identify the
relevant topic(s) for each article. Create a
search that allows people to filter their results
in an appealing graphical format.

13. #5. Improved Knowledge Sharing - Results
12http://www.science.gov/

14. Building Blocks for Search Success
• Action oriented result types
• Entity Extraction
• Taxonomies
• Auto-generation of meaningful content
• Augment your information with content from
external data sources
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15. jhilger@enterprise-knowledge.com
@jhilgerbc
www.enterprise-knowledge.com