Pattern Evaluation with Location Based Query Search

Authors

  • J. V. D Prasad  Assistant Professor, Computer Science Department, VR Siddhartha College, Vijayawada, Andhra Pradesh, India
  • M. Sri Mounica  Student, Computer Science Department, VR Siddhartha College, Vijayawada, Andhra Pradesh, India

Keywords:

Pattern evaluation, Relational database, Query suggestion, Location based search

Abstract

Customers are increasingly seeking complex task-oriented goals on the Web, such as making routes, managing finances or planning purchases. To this end, they usually break down the duties into a few co-dependent actions and problem multiple concerns around these actions repeatedly over quite a very lengthy time. To better support users in their long-term details missions on the Web, google keep track of their concerns and clicks while searching on the internet. In this document, we study the problem of organizing a user’s historical concerns into categories in an energetic and automated fashion. Instantly determining question categories is helpful for a number of different online look for engine components and applications, such as query suggestions, result position, question alterations, sessionization, and collaborative look for. So in this document we propose to develop Customized Location based Query Search method for pattern evaluation in accessing customer preference location leads to relevant details look for in relational database. This procedure automatically retrieve customer prefer locations centred on their longitude and permission of each customer in relational database.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2017-10-31

Issue

Volume 2, Issue 5, September-October-2017

Section

Research Articles

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How to Cite

[1]
J. V. D Prasad, M. Sri Mounica, " Pattern Evaluation with Location Based Query Search, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.746-750, September-October-2017.