Title: Implementing a Faceted Search Framework
1Implementing a Faceted Search Framework
- Emily Lynema Andrew K. Pace
- NC State University Libraries
- ASIST Seminar
- April 9, 2007
2Agenda
- The Context
- Problem motivation
- Local Implementation
- What and How?
- Challenges Encountered
- Outcomes
- Usage Statistics
- Future Opportunities
3The Context
4Online Catalogs
"Most integrated library systems, as they are
currently configured and used, should be removed
from public view." - Roy Tennant, CDL
5What was the problem?
- Existing catalogs are hard to use
- known item searching works pretty well, but
- users often do keyword searching on topics and
get large result sets returned in system sort
order - catalogs are unforgiving on spelling errors,
stemming
6Catalog value is buried
- Subject headings are not leveraged in searching
- they should be browsed or linked from, not
searched - Data from the item record is not leveraged
- should be able to filter by item type, location,
circulation status, popularity
7What was the motivation?
- Unresponsive vendors (2001-2006)
- Some reading and writing
- SUNY Buffalo XML OPAC (2004)
- My Kingdom for an OPAC (Feb 2005)
- Some casual conversation (Jan 2005)
- Some formal conversation (Feb-June 2005)
- Organizational culture (all along)
- Fast implementation (July 2005-Jan 2006)
8Whats the big picture?
- Improve the quality of the library catalog user
experience - Exploit our existing authority infrastructure
(aka make MARC data work harder) - Build a more flexible catalog tool that can be
integrated with discovery tools of the future.
9What is Endeca?
- Software company based in Cambridge, MA
- Search and information access technology provider
for a number of major e-commerce websites - Developers of the Endeca Information Access
Platform
10Why Endeca?
- Customized relevance ranking of results
- Better subject access by leveraging available
metadata (including item level data!) through
facets - Improved response time
- Enhanced natural language searching through spell
correction, etc. - Browse
11Local Implementation
12Demo
13Relevance ranking
- Based on locally customizable algorithm
- Most relevant query as entered
- For multi-term searches phrase match
- Field match
- title match more relevant than notes match
- Other factors
- number of fields matched
- weighted frequency (tf/idf)
- static ordering (publication date, circulation
stats)
14Faceted navigation
- Combine search and browse in single interface
(Guided Navigation) - Filter results across multiple facets
- Remove facets in any order
15Facet refinements
- Availability
- Author
- Library
- Format
- Language
- New
- LC Classification
- Subject Topic
- Subject Genre
- Subject Region
- Subject Era
16Added search tools
- Automatic spell correction
- Did you mean suggestions
- Automatic stemming
17Implementation team
- Information Technology
- Team chair and project manager
- Technical lead
- ILS Librarian
- Technical manager
- Research and Information Services
- Reference librarian
- Metadata and Cataloging
- Cataloging librarian
- Digital Library Initiatives
- Interface development
18Implementation timeline
- License / negotiation Spring 2005
- Acquire Summer 2005
- Implementation
- August 2005 vendor training
- September 2005 finalize requirements
- October 2005 January 2006 design and
development - January 12, 2006 go-live date
- It doesnt have to be perfect!
19The nitty gritty
- Endeca co-exists with SirsiDynix Unicorn ILS and
Web2 online catalog - Endeca handles keyword search
- Web2 handles authority search and detail page
display - Endeca indexes MARC records exported nightly from
Unicorn - Index is refreshed nightly with records
added/updated during previous day
20Technical overview
Information Access Platform
NCSU exports and reformats
Data Foundry
MDEX Engine
Parse text files
Raw MARC data
Indices
Flat text files
HTTP
HTTP
NCSU Web Application
21Technical overview
Offline - Nightly
NCSU exports and reformats
Data Foundry
MDEX Engine
Parse text files
Raw MARC data
Indices
Flat text files
HTTP
HTTP
NCSU Web Application
22Technical overview
Always Online
NCSU exports and reformats
Data Foundry
MDEX Engine
Parse text files
Raw MARC data
Indices
Flat text files
HTTP
HTTP
NCSU Web Application
23Challenges System design
- Identifying appropriate facets
- Integrating 2 independent data systems
- Unique identifiers are important!
- Designing the user interface
- Search page
- Results page
24- Too many boxes, lines, and shaded areas.
- Elements for a single record not visually grouped.
25First version of results page wireframe (8 total
iterations). Ideas drawn from OPAC,
RedLightGreen, Amazon, etc.
26Brief view vs. Full view gives user choice about
displaying holdings.
Reduces complexity of continuing and online
resources.
8th (and Final) Revision Aggregate holdings
information by library.
27Challenges - Data
- MARC data with MARC-8 encoding gt Text data with
UTF-8 encoding
28Fun with MARC
- MARC ? flat text file(s) for ingest by Endeca.
- Transformation accomplished with MARC4J.
- Opportunity to manipulate data on the back-end.
29Transformed data
30Challenges - Data
- MARC data with MARC-8 encoding gt Text data with
UTF-8 encoding - Data issues revealed by exposing metadata in
facets - Relevance ranking for bibliographic data
31Maintenance
- Little ongoing work required after deployment
- Quarterly data refresh from ILS
- Version upgrades
- 6 member product team meets monthly
- Lots of development ideas (as time / library
priorities afford)! - Loosely coupled making changes twice
32Outcomes
33Relevance
- Are search results in Endeca more likely to be
relevant to a users query than search results in
old OPAC? - 100 topical user searches from 1 month in Fall
2005 - How many of top 5 results relevant?
- 40 relevant in Web2 OPAC 31 no hits
- 68 relevant in Endeca catalog 12 no hits
34Usage statistics
35July 06 Jan 07
36July 06 Jan 07
37July 06 Jan 07
19.4 Subj./Class
38July 06 Jan 07
39July 06 Jan 07
40The Future
41Future opportunities
- Integrate catalog w/other tools through web
services - Enrich catalog through external web services
- book jackets, reviews, etc. Amazon/OCLC
- Build cross-application shopping cart
functionality
42The catalog web services
- Initial impetus 2 requests
- Can we have RSS feeds for the catalog?
- Can we integrate catalog results into library
website QuickSearch? - Initial plan
- Build RSS feeds and extend with OpenSearch for
integration. - Where did we end up?
43Introducing CatalogWS
- A Web API for dynamically querying information
from the NCSU Libraries Catalog - http//www.lib.ncsu.edu/catalog/ws/
- Generic XML layer provides same functionality as
HTML interface - REST web API define HTTP GET requests via URL
parameters - Enables server-side user-defined XSL
transformations
44Why go there?
- More open access to the data available in our
library catalog - Core XML schema can be re-used and modified via
stylesheets - Enable other developers in the library to build
applications using catalog data - Reduce bottleneck (I dont have to do everything)
45RSS
46QuickSearch
47Mobile device searching
48Thanks
- NCSU project site
- http//www.lib.ncsu.edu/endeca
- Andrew K. Pace
- Head, Information Technology
- andrew_pace_at_ncsu.edu
- Emily Lynema
- Systems Librarian for Digital Projects
- emily_lynema_at_ncsu.edu