Taxonomy in MOSS: Lessons Learned

Taxonomy in MOSS Lessons Learned Sharon Richardson Joining Dots

Taxonomy in MOSS

Still haven’t found what you’re looking for?

MOSS Search Beyond MOSS Search scopes Property extraction

Social Search Social network Organisation hierarchy Diary and contact info

Federated Search One Search Three results sets

Columns

Per list/library, site or site collection

Indexed as crawled properties

Used in search and navigation

Views to filter content

New Zealand Ministry of Transport

Taxonomy Management

Classification of content against defined schema(s)

Manual = user tagging

Automatic = provide training set (Bayesian inference algorithm)

Rev. Thomas Bayes (1702–1761)

Schema Challenges 80% Percentage of terms used by a test audience that were not listed in the Metropolitan Museum of Art’s documentation

Avoid using people 35 The average number of people wrongly declared dead every day in the US as a result of data input errors by social security staff Source: MSNBC, March 2008

MOSS Taxonomy Tips

Manage columns at site collection level

¨Business Unit¨ used 5x

Defined at Site collection = 1 crawled property

Defined per library = 5 crawled properties

MOSS Taxonomy Tips

Avoid empty sites and sub-sites

URL Depth and File Plans

http://intranet/projects/tahoe

http://intranet/uk/london/finance/projects/tahoe

(one is more relevant than the other...)

MOSS Taxonomy Tips

Know your source

Indexing different content

= Different metadata

= Different relevance

= Skewed results

Consider split indexes and federated search

MOSS Taxonomy Tips

What’s on the label?

Automatic metadata

Titles and descriptions

Built-in tags

Click Here versus 2008 Annual Report

Taxonomy Beyond MOSS

Concept-driven Search

Bring results back fast Then pivot based on related terms

Requires partners or bespoke code

Sheppard Mullin Richter & Hampton, LLP

500 lawyers, US-based

Approach:

Targeted web parts

Quick access to financial data

Unified search across all content

Since going live:

Averaging 1,000 document searches per day

1 million docs returned in less than 1 second

Used XMLAW toolkit to index DMS, over 3m docs

¨Stuff that we had in our old portal are looked at as 'new' features because they're now easy to find¨

References (1/2)

Microsoft Enterprise Search resources

http://www.microsoft.com/enterprisesearch/

http://blogs.msdn.com/enterprisesearch/

Microsoft SharePoint resources

http://www.microsoft.com/sharepoint/

http://blogs.msdn.com/sharepoint/

Taxonomy partners include:

SmartLogic - http://www.smartlogic.com/

conceptSearching - http://www.conceptsearching.com/

iBox SharePoint - http://www.interse.co.uk/Home.aspx

XMLAW - http://www.xmlaw.com/default.aspx

References (2/2)

MOSS Faceted Search (CodePlex):

http://www.codeplex.com/FacetedSearch

Sheppard Mullin Richter & Hampton, LLP

http://kmpipeline.blogspot.com/2007/01/live-on-sharepoint-2007-recap-and.html

http://kmpipeline.blogspot.com/2006/11/sharepoint-2007-update-enterprise.html

New Zealand Ministry of Transport case study

http://blogs.msdn.com/sharepoint/archive/2008/04/29/how-we-did-it-tag-driven-information-architecture-using-moss-2007-for-the-new-zealand-ministry-of-transport.aspx