Open Access   Article Go Back

Implementation of Dynamic Keyword Query Suggestions on Geo Location using Document Proximity

P Sujini1 , D.N. Vasundhara2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-7 , Page no. 1338-1342, Jul-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i7.13381342

Online published on Jul 31, 2018

Copyright © P Sujini, D.N. Vasundhara . 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.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: P Sujini, D.N. Vasundhara, “Implementation of Dynamic Keyword Query Suggestions on Geo Location using Document Proximity,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.1338-1342, 2018.

MLA Style Citation: P Sujini, D.N. Vasundhara "Implementation of Dynamic Keyword Query Suggestions on Geo Location using Document Proximity." International Journal of Computer Sciences and Engineering 6.7 (2018): 1338-1342.

APA Style Citation: P Sujini, D.N. Vasundhara, (2018). Implementation of Dynamic Keyword Query Suggestions on Geo Location using Document Proximity. International Journal of Computer Sciences and Engineering, 6(7), 1338-1342.

BibTex Style Citation:
@article{Sujini_2018,
author = {P Sujini, D.N. Vasundhara},
title = {Implementation of Dynamic Keyword Query Suggestions on Geo Location using Document Proximity},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2018},
volume = {6},
Issue = {7},
month = {7},
year = {2018},
issn = {2347-2693},
pages = {1338-1342},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2609},
doi = {https://doi.org/10.26438/ijcse/v6i7.13381342}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i7.13381342}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2609
TI - Implementation of Dynamic Keyword Query Suggestions on Geo Location using Document Proximity
T2 - International Journal of Computer Sciences and Engineering
AU - P Sujini, D.N. Vasundhara
PY - 2018
DA - 2018/07/31
PB - IJCSE, Indore, INDIA
SP - 1338-1342
IS - 7
VL - 6
SN - 2347-2693
ER -

VIEWS PDF XML
508 407 downloads 218 downloads
  
  
           

Abstract

A search engine is an online tool for searching any information on the World Wide Web like documents, business services, images, videos and so on. Many tools were there for helping the search engine helping the search engine like page ranking algorithms, voice search, image mining and keywords suggestions. From all this tools keyword suggestions will help online users to retrieve needed information and Express the queries without any background knowledge. Many tools were proposed to enhance the keyword suggestions like click-through, random walk method etc. But those are not satisfied user requirements in the modern world. In this paper proposing a novel structure of Keyword recommendation using location proximity which gives useful suggestion on geo based location. From the baseline algorithms, we are enhancing the partition based algorithm to achieve keyword suggestions. In addition, we enhance instant search keywords by using location proximity. Our proposed algorithm achieves better performance compared with existing algorithms in time ratio.

Key-Words / Index Term

Baseline algorithm, partition based algorithm, location proximity, keyword suggestions

References

[1] Shuyao Qi “Location aware keyword query suggestion based on document proximity” IEEE 10.1109/ICDE.2016.7498428
[2] H. Tong, C. Faloutsos, and J.-Y. Pan, “Fast random walk with restart and its applications,” in Proc. 6th Int. Conf. Data Mining,2006, pp. 613–622.
[3] P. Berkhin, “Bookmark-coloring algorithm for personalized page rank computing,” Internet Math., vol. 3, pp. 41–62, 2006.
[4] M. Gupta, A. Pathak, and S. Chakrabarti, “Fast algorithms for top k personalized page rank queries,” in Proc. 17th Int. Conf. World Wide Web, 2008, pp. 1225–1226.
[5] Song and L.-W. He, “Optimal rare query suggestion with implicit user feedback,” in Proc. 19th Int. Conf. World Wide Web 2010, pp. 901–910.-9.
[6] Y. Fujiwara, M. Nakatsuji, H. Shiokawa, T. Mishima, and M.Onizuka, “Efficient ad-hoc search for personalized PageRank,” inProc. ACM SIGMOD Int. Conf. Manage. Data, 2013, pp. 445–456.
[7] Y. Fujiwara, M. Nakatsuji, M. Onizuka, and M. Kitsuregawa, “Fastand exact top-k search for random walk with restart,” Proc. VLDBEndowment, vol. 5, no. 5, pp. 442–453, Jan. 2012.
[8] S. Cucerzan and R. W. White, “Query suggestion based on userlanding pages,” in Proc. 30th Annu. Int. ACM SIGIR Conf. Res.Develop. Inf. Retrieval, 2007, pp. 875–876.
[9] R. Li, B. Kao, B. Bi, R. Cheng, and E. Lo, “DQR: A probabilistic approach to diversified query recommendation,” in Proc. 21stACM Conf. Inf. Knowl. Manage., 2012, pp. 16–25.
[10] P. Berkhin, “Bookmark-coloring algorithm for personalized PageRank computing,” Internet Math., vol. 3, pp. 41–62, 2006.
[11] T. Gaasterland, “Cooperative answering through controlled query relaxation,” IEEE Expert, vol. 12, no. 5, pp. 48–59, Sep. 1997
[12] H. Tong, C. Faloutsos, and J.-Y.Pan, “Fast random walk with restart and its applications,” in Proc. 6th Int. Conf. Data Mining,2006, pp. 613–622.
[13] N. Lao and W. W. Cohen, “Relational retrieval using a combination of path-constrained random walks,” Mach. Learn., vol. 81,no. 1, pp. 53–67, 2010.
[14] R. Li, B. Kao, B. Bi, R. Cheng, and E. Lo, “DQR: A probabilistic approach to diversified query recommendation,” in Proc. 21stACM Conf. Inf. Knowl. Manage., 2012, pp. 16–25.
[15] Y. Song and L.-W.He, “Optimal rare query suggestion with implicit user feedback,” in Proc. 19th Int. Conf. World Wide Web,2010, pp. 901–910.
[16] Q. Mei, D. Zhou, K. Church,“Query suggestion using hittingtime,” In CIKM, 2008, pp. 469–478.