Call for Paper

CAE solicits original research papers for the July 2021 Edition. Last date of manuscript submission is June 30, 2021.

Read More

An Agent-based Meta-Search Engine Architecture for Open Government Datasets Search

S.M. Hasan Mahmud, Md. Fazle Rabbi, Kazihise Ntikurako Guy-Fernand. Published in Databases.

Communications on Applied Electronics
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: S.M. Hasan Mahmud, Md. Fazle Rabbi, Kazihise Ntikurako Guy-Fernand
10.5120/cae2016652131

Hasan S M Mahmud, Md. Fazle Rabbi and Kazihise Ntikurako Guy-Fernand. Article: An Agent-based Meta-Search Engine Architecture for Open Government Datasets Search. Communications on Applied Electronics 4(7):21-25, March 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {S.M. Hasan Mahmud and Md. Fazle Rabbi and Kazihise Ntikurako Guy-Fernand},
	title = {Article: An Agent-based Meta-Search Engine Architecture for Open Government Datasets Search},
	journal = {Communications on Applied Electronics},
	year = {2016},
	volume = {4},
	number = {7},
	pages = {21-25},
	month = {March},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Recently, Most of the countries are publishing their government data in the Web as datasets. A large number of datasets (HTML, CSV, RDF, XML, JSON, Excel, and PDF etc), catalogs and portals (data.gov, data.gov.uk, data.gov.au etc) are emerging in the Science and Government sector. Open Government Data drives in the US, UK and elsewhere have created hung amounts of government data available to the public on the web. A large number of datasets are published on government data portals, the question arises how to get datasets satisfying from government data portals with the least effort. However in many cases, a single search result is not sufficient to meet the user’s query and it is necessary to create a new service platform by combining existing government catalogs search. In this paper we proposed a meta- search architecture that will integrate different dataset catalogs search interface and collected datasets from different open government data catalogs and display higher results. In this proposed architecture have search interface provides a scalable and recognizable solution for finding Open Government datasets from open government data catalogs. Thus, the propose meta-search architecture improves the usability and effectively of open government datasets search.

References

  1. Lamberti, F., Sanna, A., Demartini, C.,”A Relation-Based Page Rank Algorithm for Semantic Web Search Engines”, IEEE Transactions on Knowledge & Data Engineering, January 2009, vol.21, no. 1, pp. 123-136.
  2. Srinivas, K., Srinivas, P. V. S.,Govardhan, A., “A Survey on the Performance Evaluation of Various Meta Search Engines”, International Journal of Computer Science Issues (IJCSI), May2011, Vol. 8 Issue 3, p359.
  3. Mukhopadhy, D., Sharma, M., Joshi, G., Pagare, T., and Palwe, A., “Experience of Developing a Meta-Semantic Search Engine”, International Conference on Cloud & Ubiquitous Computing & Emerging Technologies (2013), p. 167-171.
  4. Kumar, P., " SEReleC (Search Engine Result Refinement and Classification) - a Meta search engine based on combinatorial search and search keyword based link classification", International Conference on Advances in Engineering Science and Management (2012), pp. 627-631.
  5. Akhlaghian, F., Moradi, P., "A Multi-Agent Based Personalized Meta-Search Engine Using Automatic Fuzzy Concept Networks", Third International Conference on Knowledge Discovery and Data Mining (2010), pp 208-211.
  6. Bravo-Marquez, F., L Huillier, G., A. Rios, S., Velasquez Juan D. and Guerrero, Luis A., "DOCODE-Lite: A Meta-Search Engine for Document Similarity Retrieval", In Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems (2010), pp: 93-102.
  7. Rasolofo, Y., Abbaci, F., Savoy, J., "Approaches to collection selection and results merging for distributed information retrieval", In Proceedings of the Tenth International Conference on Information and Knowledge Management (2001), pp.191–198.
  8. Zaka, B., "Empowering plagiarism detection with a web services enabled collaborative network", Journal of Information Science and Engineering (2009), vol. 25, 1391–1403.
  9. Chaurasia, B kumar., Gupta, S Kant., Soni, R., “Meta search engine based on prioritizor”, International conference on computational intelligence and communication systems, 2011.
  10. Raval, V., Kumar, P., “EGG (Enhanced Guided Google) - A Meta Search Engine for Combinatorial Keyword Search”, Institute of Technology, Nirma University, Ahmedabad –382 481, 08-10 December, 2011.
  11. Aslam, J.A., Montague, M., "Models for metasearch", In Proceedingsof the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (2001), pp. 276–284.
  12. Chen, J., Liu, W.,” A Framework for Intelligent Meta-search Engine Based on Agent”, Information Technology and Applications (2005), p 276-279.
  13. Zheng, W., “An intelligent agent-based meta search”, International Conference on Future Information Technology and Management Engineering (FITME) (2010), p 263-266.
  14. Klusch, M., ”Information agent technology for the Internet: a survey”, Data & Knowledge Engineering , Volume 36 Issue 3, March 2001, Pages 337 – 372.
  15. Guoyuan L., Jiutao, T., Chun, W., "Studies and Evaluation on Meta Search Engines", Computer Research and Development (ICCRD), 3rd International Conference on  (Volume:3 ), 2011, P 191-193.
  16. Li, Z., Wang, Y., Oria, V., "A New Architecture for Web Meta-Search Engines”, AMCIS 2001Proceedings. Paper 84.s
  17. Sudeepthi1.G., Prof. Surendra Prasad Babu ,M.,” Survey On Meta Search Engine in Semantic Web”, International Journal of Computer Technology and Applications. 2011;02(06)3051-3055.
  18. MARIAPPAN, A.K., SURESH, R.M., BHARATHI, V.SUBBIAH., “SEMANTIC META SEARCH ENGINE USING SEMANTIC SIMILARITY MEASURE”, Journal of Theoretical and Applied Information Technology, 30th April 2013, Vol. 50, No.3.

Keywords

Open Government Data, Government Data Search, Intelligent Agent, Meta-Search Engine, Datasets search.