Intelligent Query Interface for Temporal Database with Natural Language Processing using Efficient Context Free Grammar

Nowadays interaction with computer is essential, efficient process and also the storing and retrieving of data from database will play very important role in the database application. To access the Database the user should have a strong knowledge in SQL commands and procedures. The conventional Database will give only current data not past or future data. In this paper we propose a Intelligent Query Interface for temporal databases. This will facilitate the novice user to interact Temporal Database in their Native language (English), without using any SQL command or procedures The main purpose of Intelligent Query Interface is for an English sentence to be interpreted by the computer and appropriate action taken. Asking questions to databases in natural language is a very convenient and easy method of data access. The Temporal data will support for past, present and future data. In temporal data we used third axis as time interval, which support both Transaction time as well valid time. The valid time is the actual or real world time at which the data is valid. This paper proposes the architecture for translating English Query into SQL using Efficient Context Free Grammar. This system has been implemented using Java that can be used in any operating system and has been tested with data from the industry domain. Introduction The Intelligent Query Interface will participate vital role in computer interaction. It is a part of Artificial Intelligence which has information retrieval, Machine translation and Analysis [1]. The main aim of the Intelligent Query Interface(IQI) is to facilitate the novice user to interact Database by avoiding the complex command and function. 154 K.Murugan and T. Ravichandran This Intelligent Query Interface will make the people easy to learn and use the computer as well. [2]. This will make the user to enter the text message as they would pass to the person. The interactive with computer is very essential and also more effective. Nowadays computerization is implemented in almost all the fields. Particularly in Medical Field if the Doctor wants to interact with Database, he should know the complex command as well as procedure. But this Intelligent Query processing made everyone to access the Database easily. The Conventional Database systems are responsible for the storage and processing of huge amounts of information. The data stored in these database systems refers to information valid at present time. The conventional Database does not provide models to support and process the past and future data. The Temporal database stores data relating to time instances. It offers Temporal Data types and stores information related to past, present and future time. In Temporal Database the time period is added to express when it should be valid and when it is stored. A Database that can store and retrieve temporal data, that is, data that depends on time in some way, is termed as a Temporal Database [3]. The Conventional Database is generally two dimensional, and contains only current data. The two dimensions are rows and columns that interact with each other at cells containing particular value whereas temporal databases are three-dimensional with time interval as the third dimension. Temporal Databases can also be referred to as time-oriented Databases, time varying databases, or historical databases [4]. A true temporal database is a bitemporal database that supports both valid time and transaction time [5]. Transaction time is the actual time recorded in the database at which the data is entered and the time is known as the Time-stamp. Time-stamps can include either only the date or both the date and clock time. Time-stamps cannot be changed. The other major type in Temporal Database is the valid time. Valid time is the actual or real world time at which point the data is valid [6][7]. Conventional Databases represent the state of an enterprise at a single moment of time. The conventional database holds the snapshot data. There is a growing interest in applying Database methods for version control and design management in e-commerce applications, requiring capabilities to store and process time dependent data [8][9]. Moreover, many applications such as Medical Diagnosis System, Forest Information Systems, Weather Monitoring Systems and Population Statistics Systems have been forced to manage temporal information in an adhoc manner and support the storage and querying of information that varies over time temporal database holds time varying information, required by the above-mentioned applications. In the present scenario, writing better database queries for databases pertaining to an organization involves a significant amount of time and expertise. It has become a research issue now to increase the service capability of the database systems to help novice users to formulate a query for database access. High-level query languages such as SQL are available in commercial Databases. These are easy for those users with thorough understanding of programming concepts, database schema and relational algebra [10]. To help non-expert users to perform query, a natural language front end is required. For those users who feel SQL difficult to use and for novice users who would like to retrieve data without having to learn Intelligent Query Interface forTemporal Database 155 querying mechanism such as SQL, a temporal natural language querying mechanism has been provided to access data from temporal databases[11]. The Natural Language Interface helps the distribution of the thought process from the human query users to the system [12]. Doing so helps reducing the effort spent by the query users in forming the queries. Related Work Natural Language Processing (NLP) for the Database is the best research work in NLP since it began. Interacting with the Database in Human Language is very convenient and simplest way of accessing data, particularly for the Novice user (who does not know about SQL commands and procedures). As NLP works well in single Database it will be applicable for any of the following applications. Medical Diagnosis System, Forest Information Systems, Weather Monitoring Systems and Population Statistics Systems. NLDBI this system used Efficient Context Free Grammar to parse the given queries. This system support to handle simple queries with standard joins condition [1]. LUNAR involved system which answered question about rock samples brought from moon. In this Augmented Transition Network.(ATN) Parser and Wood’s Procedural Semantics is described. The system was demonstrated at the second annual Lunar Science Conference [2]. LIFER/LADDER was one of the best NLP database systems. In this system Natural Language Interface was implemented for Database of information about US Navy Ships [3]. TEML Design System acts as a standalone Language for querying the Temporal Data. It can also be integrated with SQL for querying the Temporal Database [4]. Design and Retrieving of data from Temporal Database was presented by Jaymin Patel [5]. Object evolution in a Temporal Database can be querying using an Even Matching Language presented by Tsz S.Cheng and Shashi K. Gadia [6]. Efficient System Descriptions Brief information about the system is as follows Let us consider any Databases, for example Microsoft SQL in this we created nearly five Tables. All Tables are Normalized. Any user who may want to access data from these five Tables are supposed to be familiar with SQL commands, procedures to generate query for getting the resultset from the Database. But my system support Novice user to interact with Database for accessing the data in their Human Language. Consider the example to list the Medicine from the table Information for a particular disease, then we should create query i.e. select Medicine from information where disease = ‘Cold’. But the user (he/she) who doesn’t know MY SQL may not be able to access the Database. Thus user should know the SQL commands and procedure. But it is not possible for all types of users. To avoid this difficulty we can 156 K.Murugan and T. Ravichandran use this IQI. All types of users can access data in the Database. In the above said Query is given in normal text in English Language. For example “List the medicine for cold”. Here both Intelligent Query Interface Statement and SQL Statement produce the same result. In this system Novice user can easily access the Databases. Proposed System Here the Intelligent Query Interface is developed, for which the input should be given in English. The input may be question or be a simple sentence (like list, show, what, when etc.,) This system is designed for Temporal Database in which we can get Past, Present as well as Future Data. This system also support for validity time as the Temporal Database holds the time variant information. While typing question are simple sentence for IQI Spell Check will be evaluated by which the wrong spell will be corrected automatically. The input used for this IQI can use both British as well as US English. This system is designed to support both. This system produces the same resultset as the SQL Interface. Data dictionary is developed in which all possible words which are related to the system are maintained. It should be updated whenever new information added in the system