1. Collaborative Query Previews in Digital Libraries Lin Fu, Dion Goh, Schubert Foo Division of Information Studies School of Communication and Information Nanyang Technological University

2. Presentation Overview Background Background Query Previews and Collaborative Filtering Query Previews and Collaborative Filtering Collaborative Query Previews (CQPs) Collaborative Query Previews (CQPs) System Design and Implementation System Design and Implementation Advantages of the System Advantages of the System Future work Future work

3. Background Information Overload: Information Overload: World Wide Web World Wide Web Digital libraries Digital libraries Information Seeking: Information Seeking: Information seeking is a broad term encompassing the ways individuals articulate their information needs, seek, evaluate, select and use information (Lokman & Stephanie, 2001) 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 Collaboration and communication are important Pre-Query Information (PQI) Pre-Query Information (PQI) Information needs Information needs Information system Information system Knowledge of the collection Knowledge of the collection

4. Use of PQI in Information Retrieval Information Systems Physical Collections Digital Library Target Information Pre-Query Information Information Needs Collection Knowledge Information Systems Query Structure of the Collection Domain knowledge

5. Example of Collection Knowledge 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. 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 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 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

6. Concept 1: Query Previews Definition: Definition: Query previews provide an overview about the data distribution in a data collection (Greene et al., 1999). 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. 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. The summary data is displayed using various visualization techniques: histograms, timelines.

7. Query Preview Example

8. Reduce queries with zero or large number of hits. Reduce queries with zero or large number of hits. Prevent the retrieval of undesired records. Prevent the retrieval of undesired records. Represent statistical information of the database visually Represent statistical information of the database visually Advantages of Query Previews:

9. Concept 2: Collaborative Filtering Definition: Definition: 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) 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: Examples: Tapestry: a system that can filter information according to other users’ annotations (Goldberg, Nichols, Oki & Terry, 1992) 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) GroupLens: a recommender system using user ratings of documents (Resnick, Courtiat & Villemur, 2001)

10. Advantages of Collaborative Filtering Use the community for knowledge sharing. Use the community for knowledge sharing. Select high quality items from a large information stream. Select high quality items from a large information stream.

11. Limitations of Existing Techniques Query Previews: Query Previews: Lack of support for communication and collaboration. Lack of support for communication and collaboration. Collaborative Filtering: Collaborative Filtering: Lack of support for gathering PQI. Lack of support for gathering PQI.

12. Collaborative Query Previews (CQPs) CQP is an integrated approach to augment information seeking by supporting collaboration and communication during the process of gathering PQI. 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 generate an overview about a data collection through a set of aggregate information. CQPs introduce a collaborative aspect by providing recommendations of queries. CQPs introduce a collaborative aspect by providing recommendations of queries.

13. Collaborative Query Previews (CQPs) Direct Previews of the Data Collection: Direct Previews of the Data Collection: Through the aggregate information on selected attributes, users can get familiar with the structure of the database. Through the aggregate information on selected attributes, users can get familiar with the structure of the database. Recommendation of Queries: Recommendation 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. 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.

14. Design and Implementation Introduction: Introduction: 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 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. ZWE supports the entire process of information seeking by incorporating CQPs.

15. Design and Implementation Tabs Query previews Artifacts (photos, metadata, annotations) Browsing tree Query area Work area Popup menu Recommended queries Result lists

16. Design and Implementation Multimedia Repository Past Queries Repository User Profiles Repository Searching Browsing Query Previews Recommendation Zoomable Work Environment Authoring Metadata Repository Feature Extraction Display User Management

17. Design and Implementation JAZZ: a Zoomable User Interface (ZUI) API that allows developers to quickly and easily build zoomable information spaces. JAZZ: a Zoomable User Interface (ZUI) API that allows developers to quickly and easily build zoomable information spaces.

18. Design and Implementation Tamino XML Server: a platform to build an XML based information retrieval system. Tamino XML Server: a platform to build an XML based information retrieval system. Database Schema XML Tamino Manager Schema Editor Interactive Tools X-Query Tools

19. Design and Implementation 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. 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. Experiments show that our hybrid algorithm outperforms the existing query clustering approach.

20. Advantages of Proposed System Integerated work environment: more interactive, zoomable. Multifaceted information artifacts. Generic framework. Integerated work environment: more interactive, zoomable. Multifaceted information artifacts. Generic framework. CQPs support the information seeking process from two perspectives: CQPs support the information seeking process from two perspectives: From direct previews of the data collection. From direct previews of the data collection. From queries issued previously by others. From queries issued previously by others.

21. Future Work With the initial prototype developed, the next phase of this work will focus on the evaluation of CQPs by users of the digital library. 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 content- based, feedback-based and result-based approaches. Continuing research is also being carried out to improve the aspects of query clustering by further investigating the use of hybrid approaches, including content- based, feedback-based and result-based approaches.

22. Thank You For more information Schubert Foo vd-sci@ntu.edu.sg