2. Introduction
• Taxonomy is all about organizing and classifying.
• The word “Taxonomy” is derived from two Greek terms : taxis and
nomos.
• Taxis – the arrangement or ordering of things
• Nomos – anything assigned, usage or custom, law or ordinance.
• Taxonomy is a subject-based classification that arranges the terms in
a controlled vocabulary , and allows related terms to be grouped
together and categorized in ways that make it easier to find the
correct term to use.
• Taxonomy is useful when searching for, or describing, an object.
3. Terminology: data, information, knowledge
• Data: any fact
• Metadata/Information: the
act or fact of informing
Data about data
Provides context
Relationship with other data
objects
• Knowledge: the fact or
state of knowing
the perception of fact or truth
Interpreted data,
“understands” data and
information to refine or fulfil a
query Experiential data
4. SECI MODEL
Sympathized Knowledge: Shared
mental models and technical
skills
Conceptual Knowledge:
Analogies & metaphors of
products & processes
Systematic Knowledge:
Prototypes or new technologies
Operational Knowledge: Project
management, production
process, new product usage and
policy implementation
6. Concept Synonym Characteristics Definition
Model
PURPOSE: knowledge
representation
simplified representation of
knowledge about phenomena
Ontology
concept model; concept
system
DESCRIPTION: concepts
model for the description of
knowledge about concepts
Data model DESCRIPTION: data
formal model for the description of
data in an IT system
Classification System classification PURPOSE: classification
system for the division of
phenomena into classes
Taxonomy CONTENTS: categories
classification system for the
division of categories of a domain
Subject classification
system
subject classification
CONTENTS: subject
fields
classification system for the division
of phenomena into subject fields
8. Flat Taxonomies
• Group content into a
controlled set of categories
• Alphabetical listing of people
is a flat taxonomy
• Lists of countries or states
• Lists of currencies
• Controlled vocabularies
• List of security classification
values
9. Hierarchical Taxonomies
• Hierarchical taxonomies structure content into
at least two levels
• Hierarchies are bi-directional
• Each direction has meaning
• Moving up the hierarchy means expanding the
category or concept
• Moving down the hierarchy means refining
the category or the concept
10. Facet Taxonomies
• Facets can describe a property or value
• Facets can represent different views or aspects
of a single topic
• The contents of each attribute may have other
kinds of taxonomies associated with them
• Facets are attributes - their values are called
facet values
• Meaning in the structure derives from the
association of the categories to the object or
primary topic
• Put a person in the center of a facet taxonomy
11. Network Taxonomy
• Taxonomy which organizes content
into both hierarchical & associative
categories
• Combination of a hierarchy & star
architectures
• Any two nodes in a network taxonomy
may be linked
• Categories or concepts are linked to
one another based on the nature of
their associations
• Links may have more complex
meaningful than we find in hierarchical
taxonomies
12. We start with a generalized
term, and keep getting more
and more specific.
Almost anything may be
classified according to some
taxonomic scheme, as long
as there’s a logical hierarchy.
13. Two Types of Taxonomies:
Browse and Formal
Browse Taxonomy – Yahoo
https://in.yahoo.com/?p=us
15. Browse Taxonomies: Strengths and Weaknesses
Strengths
• Browse is better than search
• Context and discovery
• Browse by task, type, etc.
Weaknesses
• Catalogs, alphabetical listings,
Subject matter, functional,
publisher, document type
• Vocabulary and nomenclature
Issues
• Problems with maintenance, new
material
• Little relationship between parts.
• No foundation for standards
16. Formal Taxonomies: Strengths and Weaknesses
Strengths
• Fixed Resource – little or no
maintenance
• Communication Platform – share
ideas, standards
• Infrastructure Resource
• Controlled vocabulary and
keywords
Weaknesses
• Difficult to develop and
customize
• Don’t reflect users’ perspectives
• Users have to adapt to language
17. Varieties of Taxonomy/ Text Analytics Software
• Taxonomy Management
• Text Analytics
• Auto-Categorization, Entity Extraction
• Sentiment Analysis
• Software Platforms
• Content Management, Search
• Application Specific
• Business Intelligence
18. Vendors of Taxonomy/ Text Analytics Software
Attensity Multi-Tes
Business Objects – Inxight Nstein
Clarabridge SchemaLogic
ClearForest Teragram
Data Harmony / Access
Innovations
Wikionomy
Lexalytics Wordmap
The SECI model is a well known conceptual model that was first proposed by Nonaka
In one sentence, Bloom's Taxonomy is a hierarchical ordering of cognitive skills that can, among countless other uses, help teachers teach and students learn.