henry stewart dam2010_taxonomicsearch_markohurst
TRANSCRIPT
MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD GroupDisclosure range: Functional or organizational groups of MISI clients for business purposes
Leveraging Taxonomy & Metadata For Superior Search Relevancy
Achieve greater search relevancy with content structure
Speaker: Marko Hurst
2MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Me
Consultant, Author, & Speaker User Experience / Experience Design Web Analytics Search
Background: 14 years experience Search Systems, Data Analysis, Enterprise Applications,
Websites, Mobile, Web. 2.0 Independent, agency, & consulting firms National & regional lead for UX, Strategy, & Web Analytics
practices Industries: Government, Media, eCommerce, Financial Services,
Automotive, Technology, Mobile, CPG
Contact: MISI, Engagement Manager: [email protected] Read my Blog: MarkoHurst.com “Insightful Analytics”
Follow me on Twitter: MarkoHurst
3MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Me
Book: Search Analytics - Conversations With Your Customers Anticipated release: late 2010 Book website: RosenfeldMedia.com/books/SearchAnalytics Co-Author: Lou Rosenfeld
Speaker: Keynote North America & Europe eMetrics Marketing Optimization Summit Search Marketing Exchange, SMX Usability Professional Association, UPA Various
Digital Asset Management Technology Marketing Corporate Government Agencies
MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD GroupDisclosure range: Functional or organizational groups of MISI clients for business purposes
Before We Begin
Audience Survey
5MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Audience Survey
Question 1
Who uses only an algorithm (does not leverage a formal taxonomy or metadata structure) for search results?
It’s OK, I’m here to help
6MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Audience Survey
Question 2
Who uses a taxonomy to aid search relevancy? Sweet! – You’re ahead of most
7MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Audience Survey
Question 3
Who uses a ontology to aid search relevancy?I salute you! You will find Nirvana here.
8MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
What We’re Going To Cover
Definition of Common Terms
Taxonomy and Search
Metadata and Search
Ontology and Search
Q&A
MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD GroupDisclosure range: Functional or organizational groups of MISI clients for business purposes
Definitions
Let’s be sure we’re talking the same language
10MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Definition: Taxonomy
Snippet A parent / child hierarchal relationship between two or more items
English Knowledge map that allows users to access relevant objects, ideas and/or experts quickly
and efficiently Taxonomies classify domains of knowledge and show the hierarchical relationships
between categories, sub-categories and values within categories
Geek Speak Taxonomy is the practice and science of classification and comes from the Greek “taxis”
– “order" (or arrangement or division) and "nomos", meaning law or science Taxonomies, which are composed of taxonomic units known as taxa (singular taxon), are
frequently hierarchical in structure, commonly displaying parent-child relationships
11MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Taxonomy: Sample Screenshot - DAM System
http://www.day.com/content/day/en/products/digital_asset_management/features/_jcr_content/par/image.img.gif
12MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Taxonomy: Conceptual
13MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Definition: Metadata
Snippet “Data about data” of any sort in any media (paper-based or electronic media).
English Metadata describes how and when and by whom a particular asset was collected, and how
the asset is formatted asset in order to provide access to the asset Metadata is text, voice, or image that describes what the audience wants or needs to see
or experience
Geek Speak In its broadest sense, “metadata” can be used to describe information structures Metadata is a summary of the form and content of a resource, i.e. books: titles, authors,
publishers, ISBN, etc. Usually includes information about the intellectual content of the image, digital
representation data, and security or rights management information
14MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Metadata: DAM System Assigning Metadata
http://dev.day.com/content/docs/en/cq/current/dam/how_to_edit_metadata/_jcr_content/par/image_6.img.png/1258559070876.png
15MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Definition: Ontology
Snippet Form associative relationships between two or more items
English Metadata describes how and when and by whom a particular asset was collected, and how
the asset is formatted asset in order to provide access to the asset an explicit formal specification of how to represent the objects, concepts and other entities
that are assumed to exist in some area of interest and the relationships that hold among them and describes rather than the hierarchy, the relationship between entities
Geek Speak Ontologies resemble faceted taxonomies but use richer semantic relationships among
terms and attributes, as well as strict rules about how to specify terms and relationships Because ontologies do more than just control a vocabulary, they are thought of as
knowledge representation Ontologies can represent complex relationships between objects, and include the rules and
axioms missing from semantic networks
16MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Ontology: Protégé
Pizza
http://www.cmswire.com/images/protege.jpg
17MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Ontology: Conceptual
18MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Ontology: Visual Word Cloud
Associative relationships for “Legacy Loan Program”
http://subsidyscope.com/media/images/llp_word_cloud.png
MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD GroupDisclosure range: Functional or organizational groups of MISI clients for business purposes
Taxonomic Search
Putting content structure to work
20MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Surfacing Content With Search
Two dimensions for surfacing content within search: Semantic and Taxonomic
Semantic / Text paradigm Pertains to search only Search (pull) relies upon textual matching and semantic algorithms to surface relevant
content Search engine derives semantics from phrases and words in unstructured content and from
field-definition in structured content
Taxonomic paradigm Pertains to search (pull), personalization, and customization (push) Utilizes a taxonomy to surface relevant content. Search interrogates taxonomy and ontology (associative relationships)
Be aware Both approaches have advantages and disadvantages Both approaches have significant challenges – there are NO easy options! Possible to incorporate both approaches in a single search solution in effect creating two
concurrent searches
21MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Semantic vs. Taxonomy Based Search
Semantic/Free Text Search
Searches against the content of a database repository (i.e. involves only two steps: search contents) Uses only the keyword(s) entered into the search engine Where these is an exact match, a result is returned
This gives results that are less expansive, less controlled and often, less relevant...
22MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Semantic vs. Taxonomy Based Search
Taxonomy Based Search
Searches against the metadata associated with the content stored in a database repository (i.e. involves three steps: search metadata contents) The metadata (NOT the search itself) is mapped against the contents of a database
repository
Can match the user’s search word entered into the search engine with synonyms mapped in the taxonomy (e.g. “"P.D. 533" maps to "Presidential Decree No. 533” and “The anti-Cattle Rustling Law
of 1974”).
Matches can be made between a user's query and related terms mapped in the taxonomy, e.g. “P.D. 533” might be mapped to "Cattle Theft"; "Felony" to "Legislation”)
23MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Semantic vs. Taxonomy Based Search
Taxonomy Based Search (con’t)
Search results can be prioritized and categorized by filtering for pages and/or documents associated with specific search terms e.g. "best bets”
When there is ambiguity, can ask users to refine their searches by providing “Did you mean...?” feedback
This gives results that are more expansive and relevant…
24MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
How Taxonomy Aids Searching
A taxonomy aids searching by…
Restricting searches within a finite category or set of categories e.g. a search for “Farm Bill" will be restricted to the category "Legislation”
Expanding searches to higher (parent), lower (e.g. child) or equivalent (e.g. sibling) categories e.g. a search for “"Cattle Poaching" would search across "Legislation", "PB 553", “SB 1163”
"Felony" “Products”, etc.
25MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Restricting / Expanding Search With Taxonomy
Search for “Farm Bill”
Par
ent
no
de
Sib
lin
g n
od
e
Child node
Child node
26MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
How Taxonomy Aids Searching (con’t)
Provide “Did you mean?” feedback to users to refine searches e.g. a search for “Livestock” might return: “Did you mean Livestock Health, Livestock
Management, Livestock Legislation or Supplies & Equipment?”
Search against synonyms (i.e. alternate terms) e.g. a query against the acronym “DDT" would map to “dichlorodiphenyltrichloroethane”,
and search in the "Pesticides" category
Search against related terms e.g. “Pesticide" is a term that exists in both "Crop Plants" and "Products”
Because this relationship is known (and mapped) in the taxonomy, searches on one usage will also return "hits" on the other
Search on obscure or obtuse relationships e.g. Paul Hermann Müller, Rachel Carson, environmental movement, and the book Silent
Spring can all be mapped
27MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
How Taxonomy Aids Searching (con’t)
Allows for easier auto-complete / type ahead functionality Serves as a short‐cut Helps users to avoid unnecessary typing Assists with spelling May suggest related or more specific queries (that begin with or include that word or
phrase
28MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Taxonomic Search
29MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Summary
Two dimensions for surfacing content within search: Semantic and Taxonomic Semantic is pull only Taxonomic is push & pull Both have pros & cons The best search results can typically be achieved by using both
Taxonomy is a parent / child relationship between two or more items
Taxonomic search Allows for use of synonyms & mapping to related & obscure relationships Allows for expanding and restricting of content by moving up (parent), moving across (sibling), or moving
down (child) nodes within the taxonomy Many benefits / features can be used within the interface using taxonomy
Did You Mean?, Auto-Suggest, Best Bets, etc.
Metadata Metadata is “data about data” of any sort in any media Taxonomies provide an inherent level of metadata that is not possible otherwise Leveraging metadata frameworks (Dublin Core, PRISM, etc) allow for standard methods of
Ontology Associative relationship between two or more items Synonyms, controlled vocabularies, metadata, etc can be mapped taxonomy items for greater expansion &
contraction of related content
30MISI Company, Ltd. | Info Classification: Confidential | Information owner: MISI XD Group
Disclosure range: Functional or organizational groups of MISI clients for business purposes
Thank You!Contact: [email protected]
Book: RosenfeldMedia.com/books/SearchAnalytics
Blog: MarkoHurst.com
Twitter: MarkoHurst