Volume 9, Issue 4, December 2014, Pages 1746–1754
Junaid Haseeb1, Irfan Majeed2, Fiaz Majeed3, and Umair Shafique4
1 Department of Information Technology, University of Gujrat, Gujrat, Pakistan
2 Department of Information Technology, University of Gujrat, Gujrat, Pakistan
3 Department of Information Technology, University of Gujrat, Gujrat, Pakistan
4 Department of Information Technology, University of Gujrat, Gujrat, Pakistan
Original language: English
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The Data Warehouse is the advanced form of the database which is used for decision-making by the executives. There are several front-end tools for data warehouse available to support decision making. These tools come under the categories such as OLAP, Data Mining and Enterprise Information System etc. The common thing in using these tools is to have knowledge about the schema. The users of decision-making systems are top management or executives who are normally non-technical having less knowledge of the data warehouse schema and about writing database technical queries. Therefore, Natural Language (NL) interface can facilitate the executives in their decision-making process. The users prefer to have an easy querying tool that free them from technicalities of back-end processes and let them focus on desired results.
This motivated us to develop a natural language retrieval system (Natural Language Interface to Data Warehouse) that supports users especially in the ad-hoc query development. Using this system, non-technical users can easily write any ad-hoc information need in their native language. Users without having the knowledge about back-end query processing and schema can retrieve any information they want that is available in Data Warehouse. As a result, the complexity and time is reduced as well as dependency is removed.
Author Keywords: Business Intelligence, Decision Making, Retrieval, Query, Schema.
Junaid Haseeb1, Irfan Majeed2, Fiaz Majeed3, and Umair Shafique4
1 Department of Information Technology, University of Gujrat, Gujrat, Pakistan
2 Department of Information Technology, University of Gujrat, Gujrat, Pakistan
3 Department of Information Technology, University of Gujrat, Gujrat, Pakistan
4 Department of Information Technology, University of Gujrat, Gujrat, Pakistan
Original language: English
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
The Data Warehouse is the advanced form of the database which is used for decision-making by the executives. There are several front-end tools for data warehouse available to support decision making. These tools come under the categories such as OLAP, Data Mining and Enterprise Information System etc. The common thing in using these tools is to have knowledge about the schema. The users of decision-making systems are top management or executives who are normally non-technical having less knowledge of the data warehouse schema and about writing database technical queries. Therefore, Natural Language (NL) interface can facilitate the executives in their decision-making process. The users prefer to have an easy querying tool that free them from technicalities of back-end processes and let them focus on desired results.
This motivated us to develop a natural language retrieval system (Natural Language Interface to Data Warehouse) that supports users especially in the ad-hoc query development. Using this system, non-technical users can easily write any ad-hoc information need in their native language. Users without having the knowledge about back-end query processing and schema can retrieve any information they want that is available in Data Warehouse. As a result, the complexity and time is reduced as well as dependency is removed.
Author Keywords: Business Intelligence, Decision Making, Retrieval, Query, Schema.
How to Cite this Article
Junaid Haseeb, Irfan Majeed, Fiaz Majeed, and Umair Shafique, “A Natural Language Retrieval System, Natural Language Interface to Data Warehouse (NLI to DWH),” International Journal of Innovation and Applied Studies, vol. 9, no. 4, pp. 1746–1754, December 2014.
