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Autocomplete Text using Graph Database

by Rahul Patel, Sanket Sheth, Kavita Kelkar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 144 - Number 12
Year of Publication: 2016
Authors: Rahul Patel, Sanket Sheth, Kavita Kelkar
10.5120/ijca2016910509

Rahul Patel, Sanket Sheth, Kavita Kelkar . Autocomplete Text using Graph Database. International Journal of Computer Applications. 144, 12 ( Jun 2016), 42-45. DOI=10.5120/ijca2016910509

@article{ 10.5120/ijca2016910509,
author = { Rahul Patel, Sanket Sheth, Kavita Kelkar },
title = { Autocomplete Text using Graph Database },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2016 },
volume = { 144 },
number = { 12 },
month = { Jun },
year = { 2016 },
issn = { 0975-8887 },
pages = { 42-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume144/number12/25235-2016910509/ },
doi = { 10.5120/ijca2016910509 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:47:30.982325+05:30
%A Rahul Patel
%A Sanket Sheth
%A Kavita Kelkar
%T Autocomplete Text using Graph Database
%J International Journal of Computer Applications
%@ 0975-8887
%V 144
%N 12
%P 42-45
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper gives the idea about autocomplete predictive text search coupled with using graph database for storing various nodes. Firstly, the paper focuses on the search bar developed using web technologies that is platform independent and can be deployed on any system. It deals with the Jquery and AJAX mechanisms to give the user immediate autocomplete results before he or she has finished typing. Secondly, the paper discusses the role of a graph database technology used named Neo4j that stores nodes and orders relationships between them. The use of Cypher queries has been explained to retrieve the data from the graph database and JSON encode it on the screen where the user’s current focus remains.

References
  1. Hongcheng Huang, Chongqing Univ. of Posts & Telecommun., Chongqing, China, Ziyu Dong. Research on architecture and query performance based on distribute graph database Neo4j. Consumer Electronics, Communications and Networks (CECNet), 3rd International Conference. 2013.
  2. H. Komatsu, Tokyo Inst. of Technol., Japan, S. Takabayashi, T. Masui. Corpus-based predictive text input. Proceedings of the 2005 International Conference on Active Media Technology. 2005
  3. Neelu Nihalani, Comput. Applic., UIT, Bhopal, India, Sanjay Silakari, Mahesh Motwani. Integration of Artificial Intelligence and Database Management System: An Inventive Approach for Intelligent Databases. Computational Intelligence, Communication Systems and Networks, CICSYN '09. 2009
  4. Tutorialspoint. JQueryUI – Autocomplete. http://www.tutorialspoint.com/jqueryui/jqueryui_autocomplete.htm
  5. Josh Adell. Neo4jphp. Github. https://github.com/jadell/neo4jphp
  6. C. Irniger, Dept. of Comput. Sci., Bern Univ., Switzerland H. Bunke. Graph database filtering using decision trees. Pattern Recognition, ICPR, 2004.
  7. Sadhana Priyadarshini, Debahuti Mishra. An approach to graph mining using gSpan algorithm, Computer and Communication Technology (ICCCT), 2010.
  8. Volker Pacher, Stack Overflow. Running a case insensitive cypher query. http://stackoverflow.com/questions/13439278/running-a-case-insensitive-cypher-query
Index Terms

Computer Science
Information Sciences

Keywords

AJAX HTML PHP JQuery

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