How to Get Enterprise Search Right Webinar

How to Get Enterprise Search Right
Juan J. Celaya
President & CEO
COMPU-DATA International, LLC
jcelaya@cdlac.com
Twitter @conceptsearch
Ken Lemons
VP Federal Programs
Concept Searching
kenl@conceptsearching.com

Expert Speakers
Ken Lemons – VP Federal Programs at Concept Searching
has over 25 years’ experience in the IT industry, with a track record in
consulting, solutions delivery, sales and project management in the federal
sector. He has managed Microsoft consulting practices for several US
government integrators, latterly as VP of Business Development for Air Force
and DoD programs. Ken has provided US DoD agencies with solutions to
address a range of challenges, leveraging a combination of Microsoft and third
party technology solutions.
Juan Celaya – President and CEO at COMPU-DATA International
founded COMPU-DATA International, LLC in 1988 and has been successfully
delivering content and data integration solutions for ECM implementations
through the use of capture, administration, collaboration, retrieval technologies
and solutions. Juan has a broad Information Technology background covering
30 years of experience, with successful system implementations in Energy,
Healthcare, Pharmaceutical and Transportation companies, the US Department
of Defense and the National Nuclear Security Administration.

Agenda
• Introductions
• Concept Searching
• Our Approach and Technologies
• The Challenge of Search
• Products
• COMPU-DATA International
• Why Searching Raw Corporate Content is not Enough
• The Managed Metadata Environment – Your Organization’s “Controlled Vocabulary”
• CDI’s “IGT” Model – A simple approach to the Managed Medata Environment
• Initial Setup Sample
• Rules
• Taxonomy
• Leveraging Automatically Applied Metadata to Deliver
• Improved Search Results
• Utilizing the Combined Power of
• Classification and Taxonomy Management Technology

• Company founded in 2002
• Product launched in 2003
• Focus on management of structured and unstructured information
• Technology Platform
• Delivered as a web service
• Automatic concept identification, content tagging, auto-classification,
taxonomy management
• Only statistical vendor that can extract conceptual metadata
• 2009, 2010, 2011, 2012, 2013 ‘100 Companies that Matter in KM’
(KMWorld Magazine) and Trend Setting product of 2009, 2010, 2011, 2012,
2013
• Authority to Operate enterprise wide US Air Force and enterprise wide
NETCON US Army
• Locations: US, UK, and South Africa
• Client base: Fortune 500/1000 organizations
• Managed Partner under Microsoft global ISV Program - ‘go to partner’
for Microsoft for auto-classification and taxonomy management
• Smart Content Framework™ for Information Governance
• Product Suite: conceptSearch, conceptTaxonomyManager, conceptClassifier,
conceptClassifier for SharePoint, conceptTaxonomyWorkflow, conceptContentTypeUpdater for SharePoint
Concept Searching – The Industry Leader in
Managed Metadata Solutions

• Metadata driven application and enforcement of policies - conceptClassifier has been
deployed since 2003 to automatically generate metadata and use that metadata to apply and enforce
policies. Most clients are using the platform to support their information governance strategy.
• Proven, mature functionality out of the box - The platform has been deployed in numerous sites
and applications across the enterprise, including MOSS and SharePoint 2010, 2013, Office 365, Stellent,
Documentum, SQL, Oracle, File Shares, Exchange via SharePoint and across the enterprise.
Smart Content Framework™
Getting It Right

• Concept Searching’s statistical concept identification underpins all technologies
• Multi-word suggestion is explicitly more valuable than single term suggestion algorithms
• conceptClassifier will generate conceptual metadata by
extracting multi-word terms that identify ‘triple heart bypass’
as a concept as opposed to single keywords
• conceptTaxonomyManager uses statistical concept
identification to provide real-time feedback during the process
of building, testing, refining, and deploying taxonomies
• Metadata can be used by any search engine index or any
application/process that uses metadata.
Concept Searching
provides Automatic
Concept Term Extraction
Triple
Baseball
Three
Heart
Organ
Center
Bypass
Highway
Avoid
Industry Unique Technology

A Manual Metadata Approach Will Fail 95%+ Of The Time
Issue Organizational Impact
Inconsistent Less than 50% of content is correctly indexed, meta-tagged or
efficiently searchable rendering it unusable to the organization. (IDC)
Risky 59% of middle managers miss valuable information every day
because they can’t find it or never see it (Accenture)
Cumbersome - expensive Average cost of manually tagging one item runs from $4 - $7 per
document and does not factor in the accuracy of the meta tags nor the
repercussions from mis-tagged content. (Hoovers)
Malicious compliance End users select first value in list.
(Perspectives on Metadata, Sarah Courier)
No perceived value for end user What’s in it for me? End user does not see value for organization nor
risks associated with litigation and non- conformance to policies. Less
than 14% of end users receive training. (AIIM)
What have you seen Metadata will continue to be a problem due to inconsistent human
behavior.
The answer to consistent metadata is an automated approach that can extract the meaning
from content eliminating manual metadata generation yet still providing the ability to manage
knowledge assets in alignment with the unique corporate knowledge infrastructure.
Manual Approach Leads to Failure

Learning to Search
• Searchers do not know “how to search”
• 56% constructed poor queries
• Proficiency with the machine does not translate
into proficiency with the software
• Searchers get lost in the data
• 33% had difficulty navigating/orienting search
results
• 28% had difficulty maintaining orientation on a
website
• Loss of capacity for discernment
• 36% did not go beyond the first 3 search results
• (not pages…results on page 1)
• 91% did not go beyond the first page of search
results
• 55% selected irrelevant results 1 or more times

• Enterprise versus Internet search is a different animal
• In the enterprise end users know the information is there
if they could only find it
• As a result, they will spend more time and aggravation
looking for that one asset and don’t want to give up
(IDC)
• Enterprise end users expect information to be found
within 4 minutes but will actually spend 2.5 hours per
day looking for information
• How do enterprise users overcome poor search results?
• Recreate information
• Use outdated or older versions of information
• Interrupt a co-worker
• Forget about finding the information
• Just don’t start the task
The Typical Search Approach

The Hidden Costs of Search
“There is a debilitating disconnect between the proliferation of electronic information and the
constant need to quickly and accurately find all of the information and expertise that is
essential for work every day. From top to bottom, enterprises have failed to take seriously the
high cost of being grossly inadequate at finding information, data, documents, experts. Instead
they have settled for low performance, low-return techniques to… sort of handle Search.”
Julie Hunt - Search Consultant
The cost to a 500 employee company is
$2.4 million per year in inefficiencies
and lost productivity.
Gartner Group

The Intelligent Search Approach

• People explore concepts – computers find keywords
• Recall versus Precision
• Location Search
• User knows what they are seeking
• Search engine must retrieve exactly and only the information required
• Discovery Search
• User does not know precisely what they are seeking
• Search engine must retrieve content that “appears” to answer the query
• Search engine must be able to accommodate both types of searching
• The hierarchy provided by a taxonomy addresses the two different search
approaches. Location based searches appear simple, but in fact are not.
• If the end user does not immediately find what they are looking for, they can use the
hierarchical structure to drill down by searching the concepts or taxonomy nodes.
• Outcome: Identify associations and relationships that are typically not obvious in
searching
• More relevant information being found more quickly
• Accessing inter-related ideas and concepts supports a fundamental change in
user focus and activity and transforms it from searching to insight and discovery
Taxonomy Navigation

It’s Not Just About Search!!
• Data Privacy
• Records Management
• Migration
• Enterprise Content Management
• Information Governance
• Legal, eDiscovery, FOIA
• Collaboration/Social
• Text Analytics

conceptClassifier for SharePoint
• conceptClassifier for SharePoint
• Combination of automatic classification, taxonomy management and Concept Searching’s
APIs packaged for delivery into the SharePoint environment
• Single code able to be deployed with SharePoint 2007, 2010, 2013, and Office 365
• Provides clients with the choice of on-premise, cloud based, or hybrid solutions to best meet
their needs
• Integrates with any search engine (SharePoint, former FAST products, Google Search
Appliance, etc.)
• Classifies content as it is created or ingested from diverse repositories within and outside of
SharePoint
• conceptTaxonomyWorkflow
• Optional component that can perform an action on a document following a classification
decision when the criteria are met
• Built with a plug-in architecture enabling the simple development of content sources
• Uses records retention codes, semantic, and security metadata associated to data assets to
identify and process the automatic application of content types
• Once documents have the appropriate content type, based on natural language and
automatically applied metadata, workflows can be initiated.
• Workflow source type works in the SharePoint 2007, 2010, and 2013 as well as for all
document types, FILE document types, and HTTP document types

conceptClassifier for Office 365
• Runs natively and bi-directionally with the SharePoint Term Store in any
environment
• Portability – ubiquitous access to information regardless of where it resides or
how it is stored
• Provides “intelligent” migration capabilities
• Enables management of one term store for on premise and Office 365 use
• Maintains GUIDs
• Delivers enterprise class automatic document classification for all SharePoint,
FILE, and HTTP document types
• Protects records and confidential information from inadvertently being place in
the cloud to avoid data breaches and unauthorized access to information
• Enables concept based search and retrieval integrated with Microsoft search
solutions
• Provides a method to enable text analytics from multiple data sources without
impacting on-premise server utilization

Preserving
the
World's Knowledge
  
Available Anytime Anywhere
SM
Getting
Enterprise
Search Right
by Using
Your Own
Vocabulary
For Indexing
and
Searching

Preserving the Worlds Knowledge - Available Anytime AnywhereSM
©2013 COMPU-DATA International, LLC, All Rights Reserved
Many Thanks To

• Why Searching Raw Corporate Content is not enough
• The Managed Metadata Environment –
Your Organization’s “Controlled Vocabulary”
• CDI’s “IGT” Model –
A simple approach to the Managed Medata Environment
• Initial Setup Sample:
 Rules
 Taxonomy
• Leveraging Automatically Applied Metadata to Deliver:
 Improved Search Results
• Utilizing the combined power of:
 Classification & Taxonomy Management Technology
Presentation Overview

Searching Raw Corporate Content is not enough
• Limited Resources
• Corporate Content Control
 Not written for SEO
 Not HTML
• Not HTML
 No Title Tags
 Header Tags
 Content missing keywords
 No Meta Tags
• How do you make content relevant?
 Add corporate vocabulary (Tags, Tags and more Tags)
Keywords too!
 Adapt to the changing business environment
 Leverage automatic metadata tagging
You are not Google,
Bing or Yahoo!

“The managed meta data environment represents the architectural
components, people and processes that are required to properly and
systematically gather, retain and disseminate meta data throughout the
enterprise.”
Components:
1. Meta data sourcing layer
2. Meta data integration layer
3. Meta data repository
4. Meta data management layer
5. Meta data marts
6. Meta data delivery layer
Managed Metadata
Environment*
*From the book Universal Meta Data Models by David Marco
and Michael Jennings (John Wiley & Sons)

The “IGT” Model:
1. Metadata Identification
2. Automatic Metadata Generation
3. Automatic Metadata Tagging
Delivering a Dependable
Automatic Data Enhancement Solution
Applicable Across the Enterprise
Implementing a Simple
Managed Metadata Environment

Metadata
Identification
1. The process to create the rules by
which Metadata can be identified for
electronic content and data files.
2. Requires technologies to process
text content such as that from
Concept Searching and others that
can be used on images, audio, and
video.
3. Requires Expertise: Data Science,
Classification, Statistical Theory,
Content SMEs, Library Sciences,
Records Management. Other areas
for which content must be identified.
4. Recursive process receiving input
from actual results and new input
from business needs and
requirements.

Automatic
Metadata
Generation
1. Is the process to automatically
provide Metadata to a requestor
based on a predefined set of rules
and processes.
2. Functionality either included in the
tool and technology used or it is built
to support this function.
3. Requires Expertise: Programming
and integration, knowledge of tool
and technology APIs and
functionality.

3. Automatic Metadata Tagging
Automatic
Metadata
Tagging
1. Is the process and methods by
which content is enhanced when
one or more Metadata Tags are
attached, assigned, joined or
associated with the content’s
electronic file through an automated
process.
2. Functionality either included in the
tool and technology used, it is
provided from a 3rd party or it is built
internally.
3. Requires Expertise: Programming
and integration, knowledge of tool
and technology APIs and process
functionality.
4. Provides feedback to improve
Metadata Identification.

Overview of CDI’s
“IGT“ Model steps
to a Successful
Automatic
Metadata Tagging
Solution
Metadata
Identification
The process to create the rules by
which Metadata can be identified.
Tools &
Technologies: Text
based technology
such as Concept
Searching, and
others that can be
used on images,
audio, and video.
Required Expertise:
Data Science,
Classification,
Statistical Theory ,
Content SMEs,
Library Sciences,
Records
Management.
STEP #1
Automatic
Metadata
Generation
The process to Automatically
Generate Metadata for content by
using the technologies used and
rules defined in the Metadata
Identification process.
Functionality either
included in the tool
and technology
used or it is built to
support the tool
and technology.
Required Expertise:
Programming and
integration,
knowledge of tool
and technology
APIs and
functionality.
STEP #2
STEP #3
Automatic
Metadata
Tagging
The process and methods by which
one or more Metadata Tags are
attached, assigned, joined or
associated to an electronic file.
Functionality either
included in the tool
and technology
used, it is provided
from a 3rd party or
it is built internally.
Required Expertise:
Programming and
integration,
knowledge of tool
and technology
APIs and process
functionality.
Feed
back
from
actual
results

Metadata Identification
Advantages provided by
each step in the “IGT” Model
Automatic
Metadata Generation
Automatic
Metadata Tagging
1. Standardize identification rules and
establish a common metadata
vocabulary.
2. Able to manage (distributed at and
centrally for) different levels of the
organization as needed.
3. Provides for ad hock support based
on needs arising from eDiscovery
and litigation.
4. Improve reliability in the result lists
delivered by enterprise search
technologies used.
5. Multiple approaches and
technologies can be used that are
applicable to varying content.
6. Easy to distribute improvements as
feedback is applied.
1. SOP across the organization for
getting corporate, departmental,
project and any other applicable
metadata.
2. Single interface for access to
varying metadata identification
technologies.
1. Enforce rules established in the
organization and reduce costs due
to changes in regulations/business.
2. Eliminates human factors and
behaviors that contribute to negative
outcomes associated with metadata
assignment.
3. Makes it easier to achieve
“findability”, enforce access controls,
apply corporate governance and
implement a record retention
schedule.
4. Centralized and distributed tagging
integration and control of data
sources.
5. Bridges the implementation of any
metadata identification technology to
any data source.
Note: Advantages of each step are not “all inclusive”

Supports
Storage &
Preservation
Business
Function
Application of
record retention
codes with
metadata deriving
storage &
preservation
Supports
Information
Rights
Management
Business
Functions
Content types
drive automatic
application of
RMS templates
Supports
Search
Business
Function
Application of
metadata
drives search
precision
TAXONOMY MANAGEMENT ENVIRONMENT
(Developed using Taxonomy Management Technology)
Data Privacy and Security Compliance Taxonomies
(Data Privacy & Security Enforcement, see (A, B))
Data Transparency by Metadata Tagging
Compliance
(Access Policies & Rights Management), see (A, C))
Records Management Compliance Taxonomies
(Records Retention Schedules, see (A))
Improved Enterprise Search
(Search Precision, see (B, C))
• The Taxonomy Management
Environment (TME) is made up of the
technologies, processes and utilities
used to create and administer
Taxonomies.
• Within the TME subject matter experts,
librarians and operations personnel
work together to create taxonomies
which define the business rules by
which content files are analyzed.
• These taxonomies are then used to
classify electronic content and associate
each applicable rule to the content file
processed.
• Content is “Automatically Tagged” with
the appropriate rule identifier and
corresponding vocabularies used within
the organization.
Taxonomy Management Environment
A B C

Document
Creation/
Modification
by User
SharePoint
Update
Content
Types
28
Enterprise
Search
Search on user’s compliance
domain (based on document
content & metadata)
Document
Search by
User
Supports
Storage &
Preservation
Business
Function
Application of
record retention
codes with
metadata deriving
storage &
preservation
Supports
Information
Rights
Management
Business
Functions
Content types
drive automatic
application of
RMS templates
Supports
Search
Business
Function
Application of
metadata
drives search
precision
A
Compliance
B C
SharePoint Implementation
conceptClassifier Classification Engine
Tagging Processes

Document
Creation/
Modification
by User
Shared
Drives
SharePoint
Other Data
Sources
Update
Content
Types
29
Enterprise
Search
Search on user’s compliance
domain (based on document
content & metadata)
Document
Search by
User
Supports
Storage &
Preservation
Business
Function
Application of
record retention
codes with
metadata deriving
storage &
preservation
Supports
Information
Rights
Management
Business
Functions
Content types
drive automatic
application of
RMS templates
Supports
Search
Business
Function
Application of
metadata
drives search
precision
A
Compliance
B C
Enterprise Implementation
Real Time
Tagging
Metadata Tagging & Workflow
of Data Source Content
Managed by DES*
Move file to
another
location
Sensitive
Info?
Auto
Tagging of
Content
Files
DES* automatically tags & classifies
content based on semantics contained
within actual content files.
N
Y
Move to
SharePoint
Manage
Relations
of Rules &
Content
conceptClassifier Classification Engine
*Data Enhancement System™ (DES) is a patent pending
product from COMPU-DATA International, LLC.

conceptClassifier
Tool
CDI’s DES* (Data Enhancement System™) Management Layer
Automated Metadata Tagging of Content To/From Data Sources
Other File
Format Tools
Data store for
testing new
taxonomies
Data store for
testing new
taxonomies
Librarian/Client-Generated
Taxonomies & Fields
Taxonomy A TA - Fields
Taxonomy B TB - Fields
● ● ● ● ● ●
Taxonomy N TN - Fields
Taxonomies & Fields
● ● ● ● ● ●
Metadata Generation Technologies
SharePoint®
in the Cloud
SharePoint®
On-Premise
Shared
Drives
Other
ECMs/APPs
DATA SOURCES
● ● ●
Automated Tagging of
Content
Content
Content
DIRECT DATA SOURCE MONITORING
Taxonomy
Managers &
Subject
Matter
Experts
● ● ●
©2012 - 2013 COMPU-
DATA International, LLC, All
Rights Reserved
TAXONOMY
MANAGEMENT
ENVIRONMENT
MANAGE
AUTOMATIC
METADATA
TAGGING OF
CONTENT
*Data Enhancement System™ (DES) is a patent pending
product from COMPU-DATA International, LLC.

conceptClassifier
Tool
CDI’s DES * (Data Enhancement System™) Management Layer
Automated Metadata Tagging of Content To/From Data Generation Sources
Other File
Format Tools
Data store for
testing new
taxonomies
Data store for
testing new
taxonomies
Taxonomies & Fields
● ● ● ● ● ●
Taxonomies & Fields
● ● ● ● ● ●
Metadata Generation Technologies
Automated Tagging
&
Delivery of Content
INTEGRATION WITH CAPTURE, PROCESSES & APPLICATIONS
SharePoint®
In the Cloud
SharePoint®
On-Premise
Shared Drives
Others
ECMs/APPs
DATA SOURCES
● ● ●
Business & Application Processes
Taxonomy
Managers &
Subject
Matter
Experts
Kodak Capture Pro
● ● ●
©2012 - 2013 COMPU-
DATA International, LLC, All
Rights Reserved
Info Activate
MANAGE
AUTOMATIC
METADATA
TAGGING OF
CONTENT
*Data Enhancement System™ (DES) is a patent pending product from COMPU-DATA International, LLC.

Supports
Storage &
Preservation
Business
Function
Application of
record retention
codes with
metadata deriving
storage &
preservation
Supports
Information
Rights
Management
Business
Functions
Content types
drive automatic
application of
RMS templates
Supports
Search
Business
Function
Application of
metadata drives
search precision
Data Privacy and Security Compliance
Data Privacy & Security Enforcement
Data Transparency by Metadata Tagging Compliance
Access Policies & Rights Management
Records Management Compliance
Records Retention Schedules
Search Precision
Data Enhancement Through
Automatic Metadata Tagging
B
A
C
CB
A B C
A
A

Supports
Search
Business
Function
Application of
metadata drives
search precision
Search Precision
Automatic Metadata Tagging to all Data Sources
using your own Vocabulary
Identify, Retrieve, Secure & Control Access to Data Assets
across Distinct Business & Service Delivery Units
Supports
Information
Rights
Management
Business
Functions
Content types
drive automatic
application of
RMS templates
Data Enhancement Through
Automatic Metadata Tagging

Taxonomy Management
Enabling the Automatic Meta-tagging and Auto-Classification of Documents and Records
Each node is a piece of metadata that gets tagged to a document or record based upon the
prevalence of a clue within the document
Manually Created Metadata associated
with the concept of “Weather”
Distribution Statement A: Approved for public release; distribution is unlimited
311 ABG/PA No. 09-488, 16 Oct 2009

Automatic Metadata Generation
Unique IP of Compound Term Processing enables the identification of compound terms
(not keywords) from highly relevant content that can be used to trigger the automatic
meta-tagging and auto-classification processes
Automatically Generated
Metadata associated with
the concept of “Weather”
311 ABG/PA No. 09-488, 16 Oct 2009

Automatic Metadata Generation
Automatically generated metadata is added to original metadata for the category/folder
Outcome: more semantics that can be linked to a document or record result in information that
becomes more actionable (the document/record is now retrievable and classifiable)
Highly relevant metadata generated by
Taxonomy Manager added to original clue
set for the concept of “Weather”
311 ABG/PA No. 09-488, 16 Oct 2009

Automatic Meta-tagging
Metatags are automatically added to the properties field of each document
enhancing the document’s valuable to the organization by increasing
the ability of the document to be retrieved using enterprise search
solutions that use keywords and metadata to retrieve information

Automatic Meta-tagging in Action
One of the Metatags for the document was “Turbulence Encounter” however when
we search for this term within the document we do not find it
Why did this happen?

Turbulence Encounter is only one of 4 “clues” that must exist within a document in order for
that document to be automatically meta-tagged with the concept of Turbulence Encounter
311 ABG/PA No. 09-488, 16 Oct 2009

When we search the document using another clue for Turbulence Encounter, “Windshear”,
we see that its existence within the document triggered the automated meta-tagging event
that resulted in the document being tagged with “Turbulence Encounter”

Automatic Meta-tagging
Metatags are automatically added to the properties field of each document
making the document more valuable to the organization by increasing
the ability of the document to be retrieved using enterprise search
solutions that use keywords and metadata to retrieve information

Automatically Apply Semantic Metadata
Records Retention Codes
Data Privacy & Security Metadata
To Every Document in SharePoint, File Shares
and other Data Sources
“Corporate
Vocabulary”
as the Metadata
Environment
(Taxonomy)
“Non-Preferred
Vocabulary Terms”

• US Army - Records Management and Declassification Agency (RMDA)
• Solution
• An integrated search solution to consolidate over 20 data sources and
databases into just a few repositories, with access to high data volumes
• Benefits
• Centralized data standardization
• Increased findability
• Terabyte size data store support
• Increased productivity
• Scalable
Use Case - RMDA

• A global company which designs, manufactures, and distributes
appliances to more than 70 countries
• Solution
• An intranet and content management solution to improve search,
sensitive/confidential information protection, and records identification
and tagging
• Benefits
• Accurate search
• Data privacy
• Effective records management
Use Case – Global Appliance Company

Time for a Demo
Let’s Tie all of this Together
With a Live Demo

Thank You
Juan J. Celaya
President & CEO
jcelaya@cdlac.com
Twitter @conceptsearch
Ken Lemons
VP Federal Programs
Concept Searching
kenl@conceptsearching.com

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