Integrating Flexibility and Fuzziness into a Question Driven Query Model
Date
2016-01-18
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Abstract
Data plays an important role in our daily life. Thus, data collection, storage, maintenance
and processing continue to attract considerable attention. Data may exist in various formats,
ranging from unstructured to structured as the two extremes. Traditionally, researchers and
practitioners cooperated and developed various data models which form the main foundation
for existing database management systems. The relational data model is still dominating
despite the rapid development in the techniques used for data collection, storage and processing.
Further, a relational database management system supports a structured query
language (SQL) for data processing, and it is not possible to access and retrieve data from a
relational database without knowing how to use SQL. However, the wide usage of relational
databases motivated researchers to develop more user friendly interfaces which would allow
a larger population of users to access relational databases. Such interfaces range from visual
to natural language based.
This thesis contributes a question driven query model which falls under the natural language
based category. The target is to make databases reachable by a larger population,
especially after the Internet increased database availability. The proposed model supports
fuzziness where every user is given the freedom to de ne his/her own understanding of fuzzy
terms. The developed system absorbs the fuzzy understanding of each user to utilize it while
deciding on the result to be communicated back as answer to the raised question. Data
mining techniques are employed to guide users in de ning their fuzzy understanding. The
developed model is intended to help users to retrieve the data they want from a relational
database without expecting them to know SQL. In the current version only questions written
in English are allowed. The system handles di erent types of questions, such as (1) simple
questions, (2) complex questions with inner joins and where conditions, (3) questions that
involves the usage of aggregate functions (e.g., min, max, etc.), and (4) questions with fuzzy terms. The reported test results demonstrate the e ectiveness of the developed system in
handling various types of questions raised by a heterogeneous set of users ranging from professionals
to naive.
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Computer Science
Citation
Sarhan, A. (2016). Integrating Flexibility and Fuzziness into a Question Driven Query Model (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/26577