Collaborative Query Previews in
Digital Libraries
Lin Fu, Dion Goh, Schubert Foo
Division of Information Studies
School of Communication and Information
Nanyang Technological University
Presentation Overview
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Background
Query Previews and Collaborative
Filtering
Collaborative Query Previews (CQPs)
System Design and Implementation
Advantages of the System
Future work
Background
 Information
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World Wide Web
Digital libraries
 Information
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Overload:
Seeking:
Information seeking is a broad term encompassing the
ways individuals articulate their information needs,
seek, evaluate, select and use information (Lokman &
Stephanie, 2001)
Collaboration and communication are important
Pre-Query Information (PQI)
 Information needs
 Information system
 Knowledge of the collection
Use of PQI in Information Retrieval
Information
Needs
Information
Systems
Physical
Collections
Information
Systems
Pre-Query
Information
Query
Collection
Knowledge
Structure of the
Collection
Domain
knowledge
Digital
Library
Target
Information
Example of Collection Knowledge
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Suppose a user wants to search a paper on
overview-detail style interface but does not know
the title, and also a novice in this field.
The user enters “interface” or “overview, detail”
as the query. However, nothing in the top 50
results rings a bell
Someone else searching for the same paper
might remember its name clearly (“Reading of
Electronic Documents: The Usability of Linear,
Fisheye, and Overview+Detail Interfaces”). He
knows that using “fisheye, overview, detail” as
the query keyword will yield a good result
Concept 1: Query Previews
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Definition:
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Query previews provide an overview about the
data distribution in a data collection (Greene
et al., 1999).
Overviews are represented as aggregate
information on attributes of the collection--known as summary data.
The summary data is displayed using various
visualization techniques: histograms,
timelines.
Query Preview Example
Advantages of Query Previews:
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Reduce queries with zero or large number of
hits.
Prevent the retrieval of undesired records.
Represent statistical information of the
database visually
Concept 2: Collaborative Filtering
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Definition:
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Collaborative filtering is a technique for recommending
items to a user based on similarities between the past
behavior of the user and that of likeminded people
(Chun & Hong, 2001)
Examples:
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Tapestry: a system that can filter information according
to other users’ annotations (Goldberg, Nichols, Oki &
Terry, 1992)
GroupLens: a recommender system using user ratings
of documents (Resnick , Courtiat & Villemur, 2001)
Advantages of Collaborative Filtering
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Use the community for knowledge
sharing.
Select high quality items from a large
information stream.
Limitations of Existing Techniques
 Query
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Previews:
Lack of support for communication and
collaboration.
 Collaborative

Filtering:
Lack of support for gathering PQI.
Collaborative Query Previews (CQPs)
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CQP is an integrated approach to
augment
information
seeking
by
supporting
collaboration
and
communication during the process of
gathering PQI.
CQPs generate an overview about a data
collection through a set of aggregate
information.
CQPs introduce a collaborative aspect by
providing recommendations of queries.
Collaborative Query Previews
(CQPs)
 Direct
Previews of the Data
Collection:
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Through the aggregate information on selected
attributes, users can get familiar with the structure of
the database.
 Recommendation
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of Queries:
Through collaborative filtering techniques, CQPs
recommend related queries previously executed by
other users to help the current user make better sense
of how the document collection met past information
needs that coincide with the present information need.
Design and Implementation
 Introduction:
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ZWE provides an integrated platform for
supporting a variety of scholarly tasks including
browsing, querying, organizing and annotating of
information resources (Goh, Fu & Foo, 2002)
using a spatial metaphor.
ZWE supports the entire process of information
seeking by incorporating CQPs.
Design and Implementation
Artifacts (photos, metadata,
annotations)
Browsing
tree
Popup
menu
Tabs
Query
area
Recommended queries
Query
previews
Result
lists
Work
area
Design and Implementation
Zoomable Work Environment
User
Management
Browsing
Authoring
Display
Searching
Query
Previews
Recommendation
Feature
Extraction
Multimedia
Repository
Metadata
Repository
Past Queries
Repository
User Profiles
Repository
Design and Implementation
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JAZZ: a Zoomable User Interface (ZUI) API
that allows developers to quickly and easily
build zoomable information spaces.
Design and Implementation
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Tamino XML Server: a platform to build an XML based
information retrieval system.
Tamino
Manager
Schema
Editor
Interactive
Tools
Database
Schema
Schema
XML
Schema
XML
X-Query
Tools
Design and Implementation
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For query recommendation module, we
proposed a hybrid approach (Fu, Goh & Foo,
2003a, 2003b) to cluster past queries and apply
the algorithms to find similar past queries for a
given query.
Experiments show that our hybrid algorithm
outperforms the existing query clustering
approach.
Advantages of Proposed System
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Integerated work environment: more
interactive,
zoomable.
Multifaceted
information artifacts. Generic framework.
CQPs support the information seeking
process from two perspectives:
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From direct previews of the data collection.
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From queries issued previously by others.
Future Work
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With the initial prototype developed, the
next phase of this work will focus on the
evaluation of CQPs by users of the digital
library.
Continuing research is also being carried
out to improve the aspects of query
clustering by further investigating the use
of hybrid approaches, including contentbased, feedback-based and result-based
approaches.
Thank You
For more information
Schubert Foo [email protected]