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Automated Creation of a Forms-based Database Query Interface. M Jayapandian , HV Jagadish Proceedings of the VLDB 2008. Input & Output. Input: Dataset stored in XML format The corresponding schema Output: Query forms. Old forms v.s . new forms. V.S. Challenges.
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Automated Creation of a Forms-based Database Query Interface M Jayapandian, HV Jagadish Proceedings of the VLDB 2008
Input & Output • Input: • Dataset stored in XML format • The corresponding schema • Output: • Query forms
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
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
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: • .
Filtering Schema(2) • Queriability of Entities: • How frequently the entity is going to be queried • Queriability of Related Entities
Filtering Schema(3) • Queriability of Attributes • The number of times it is instantiated in the data for each occurrence of its parent entity
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
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
Experiment • Dataset: • MiMI: Michigan Molecular Interaction Database • Geoquery • Jobsquery Database • Criteria: • Percentage of satisfied queries over total number of queries
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
Motivations • Old fashioned form v.s New forms
Input & Output • Input: • Customized form • Output: • Corresponding XQuery expression
Form Elements • Constraint specification element • Result display element • Result ordering element • Aggregate computation element • Disjunction element • Join specification element
Three Steps to Generate a Form • Criteria Pane • Result Pane • Advanced Pane (to define join operation)
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
Evaluation • Casual User Study • To measure how long and how correctly casual users were able to perform the required modifications
Evaluation • Expert User Study • To perform a direct comparison between form modification and query re-writing to satisfy a set of information needs
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
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.