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Automated Creation of a Forms-based Database Query Interface

This paper discusses the automated generation of forms-based database query interfaces, focusing on analyzing schema elements in XML datasets. It highlights the challenges of determining the most relevant schema fragments for users and introduces a model representing the database schema as directed graphs. The authors analyze entities and attributes' queriability, leading to efficient form composition for querying. The study compares traditional forms to new, customized forms and evaluates usability through casual and expert user studies to enhance query satisfaction and performance.

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Automated Creation of a Forms-based Database Query Interface

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  1. Automated Creation of a Forms-based Database Query Interface M Jayapandian, HV Jagadish Proceedings of the VLDB 2008

  2. Input & Output • Input: • Dataset stored in XML format • The corresponding schema • Output: • Query forms

  3. Old forms v.s. new forms V.S

  4. Challenges • Determining the schema fragments most likely to be of interest to a querying user • To partition the filtered collection of schema elements into groups • Converting each of these groups of schema elements into a form

  5. Model • The paper model the schema of a database as a directed graph <E, A, L> • E is a finite set of entities • A is a finite set of attributes • L is a finite set of links between nodes (entities or attributes) in the graph

  6. Filtering Schema(1) • Definition of Cardinality: • Number of times each node in the schema graph is instantiated in the data, denoted as C(n) • Definition of link cardinality • Number of link instances between ni and n in the data, denoted as C(ni->n) • Definition of Relative Cardinality: • .

  7. Filtering Schema(2) • Queriability of Entities: • How frequently the entity is going to be queried • Queriability of Related Entities

  8. Filtering Schema(3) • Queriability of Attributes • The number of times it is instantiated in the data for each occurrence of its parent entity

  9. Analyze Schema Algorithm • Create graph G corresponding to schema • For each instantiated element n • If n represents an entity e in G, increase the cardinality of that entity • If n represents an attribute a in G, compute the attribute size of a • For each node n in G • If n represents an entity, compute its queriability • If n represents an attribute, compute its operator specific queriablity

  10. Result of schema analysis

  11. Form Composition Algorithm • Select an entity and create a form for it • Choose entities related to it and create additional forms • Select attributes for each entity and place them in each form

  12. Experiment • Dataset: • MiMI: Michigan Molecular Interaction Database • Geoquery • Jobsquery Database • Criteria: • Percentage of satisfied queries over total number of queries

  13. Expressive Query Specification through Form Customization M Jayapandian, HV Jagadish Proceedings of the 11th international conference on Extending database technology: Advances in database technology 2008

  14. Motivations • Old fashioned form v.s New forms

  15. Input & Output • Input: • Customized form • Output: • Corresponding XQuery expression

  16. Form Elements • Constraint specification element • Result display element • Result ordering element • Aggregate computation element • Disjunction element • Join specification element

  17. Three Steps to Generate a Form • Criteria Pane • Result Pane • Advanced Pane (to define join operation)

  18. Query Generation • Address join element • Lowest Common Ancestor of the attributes selected forms for-clause • All constraints specification form where-clause • Return display & aggregate elements form return-clause

  19. Evaluation • Casual User Study • To measure how long and how correctly casual users were able to perform the required modifications

  20. Evaluation • Expert User Study • To perform a direct comparison between form modification and query re-writing to satisfy a set of information needs

  21. Related works • Usher: Improving Data Quality with Dynamic Forms Chen, K. and Chen H. Proceedings of the International Conference on Data Engineering 2010 • Input: user’s previous answers • Output: customized questions and “false” answers detection • Combining Keyword Search and Forms for Ad Hoc Querying of Databases E Chu, A Baid, X Chai SIGMOD 2009 • Two phrases search: • 1. search among query forms that system produces as many as possible automatically • 2. retrieve records via query forms

  22. Related works • A Hierarchical Approach to Model Web Query Interfaces for Web Source Integration Eduard C. Dragut, Thomas Kabisch, Clement Yu, Ulf Leser VLDB 2009 • To help users find out the appropriate web database that satisfy their queries. • Technical challenge: how to understand web databases via their interfaces, which are query forms.

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