Database management system has been widely used for storing and retrieving data. However, database is often hard to access the data since their interface is rigid in cooperating with user, due to that analysis of natural language query interface to relational databases has gained much interest in research community. This can be termed as structured free query interface as it allows the users to retrieve the data from the database without knowing the underlying schema. Structured free query interface should address majorly two problems. Querying the system with natural language interfaces is comfortable for the naive users but it is difficult for the machine to understand. The other problem is that the users can query the system with different expressions to retrieve the same information. The different words used in the query can have same meaning and the same word can have multiple meanings. Hence; it is the responsibilities of the NLI to understand the exact meaning of the word in the particular context to handle such problem the researcher develops an algorithm that is from manually crafted rule that extracted from user queries for proper query translation and SQL query generation. The proposed, pattern matching approach to natural language interface to database system has been passes through various phases. The idea behind the approach is to overcome the problem bottleneck luck of tools in the language, while pattern-matching method can fill the gap of those resources. This makes our approach suitable for AONIDB since Afaan Oromoo is under resourced language. The exact meaning of the word used in the query in particular context obtained using domain-mapping dictionary and database-mapping table constructed form student database that contains grade, department and course table for mapping database information with the help of an algorithm developed by researcher based on the rule that extracted from collected user query. The system has been developed in which user can input query in Afaan Oromoo language and can see result in the same language. The proposed system can handle list query, single and multiple conditional queries, aggregate function queries and join queries. The proposed system evaluated on 100 Afaan Oromoo queries using student database with precision, recall and F-measure. The result of testing is very encouraging and an average performance of 94.2% that implies that the systems validity and reliability is very high, an indicator of its strong and successfully features use and operation. Yet; further experiments using different approaches that extend this work are needed for a better performance.
Keywords
AONLIDB, Afaan Oromoo Language Interface to Database, Natural Language Processing
