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Conference proceeding
Automatically Mapping and Integrating Multiple Data Entry Forms into a Database
CONCEPTUAL MODELING - ER 2011, v 6998
01 Jan 2011
Abstract
Forms are a standard way of gathering data into a database. Many applications need to support multiple users with evolving data gathering requirements. It is desirable to automatically link dynamic forms to the back-end database. We have developed the Form Mapper system, a fully automatic solution that accepts user-created data entry forms, and maps and integrates them into an existing database in the same domain. The solution comprises of two components: tree extraction and form integration. The tree extraction component leverages a probabilistic process, Hidden Markov Model (HMM), for automatically extracting a semantic tree structure of a form. In the form integration component, we develop a merging procedure that maps and integrates a tree into an existing database and extends the database with desired properties. We conducted experiments evaluating the performance of the system on several large databases designed from a number of complex forms. Our experimental results show that the FormMapper system is promising: It generated databases that are highly similar (87% over-lapped) to those generated by the human experts, given the same set of forms.
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Details
- Title
- Automatically Mapping and Integrating Multiple Data Entry Forms into a Database
- Creators
- Yuan An - Drexel UniversityRitu Khare - Drexel Univ, Coll Informat Sci & Technol, Philadelphia, PA 19104 USAIl-Yeol Song - Drexel UniversityXiaohua Hu - Drexel University
- Contributors
- M A Jeusfeld (Editor)L Delcambre (Editor)T W Ling (Editor)
- Publication Details
- CONCEPTUAL MODELING - ER 2011, v 6998
- Series
- Lecture Notes in Computer Science
- Publisher
- Springer Nature
- Number of pages
- 14
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000303359500020
- Scopus ID
- 2-s2.0-80455123855
- Other Identifier
- 991019170444604721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Software Engineering
- Computer Science, Theory & Methods