dc.contributor.author | Alfred, R. | en |
dc.contributor.author | Gan, K. S. | en |
dc.contributor.author | Chin, K. O. | en |
dc.contributor.author | Anthony, Patricia | en |
dc.date.accessioned | 2016-08-16T03:24:16Z | |
dc.date.issued | 2014-04 | en |
dc.identifier.citation | Alfred, R., Gan, K. S., Chin, K. O. & Anthony, P. (2014). A robust framework for web information extraction and retrieval. International Journal of Machine Learning and Computing, 4(2), 146-150. doi:https://doi.org/10.7763/IJMLC.2014.V4.403 | en |
dc.identifier.uri | https://hdl.handle.net/10182/7235 | |
dc.description.abstract | The large volume of online and offline information that is available today has overwhelmed users’ efficiency and effectiveness in processing this information in order to extract relevant information. The exponential growth of the volume of Internet information complicates information access. Thus, it is a very time consuming and complex task for user in accessing relevant information. Information retrieval (IR) is a branch of artificial intelligence that tackles the problem of accessing and retrieving relevant information. The aim of IR is to enable the available data source to be queried for relevant information efficiently and effectively. This paper describes a robust information retrieval framework that can be used to retrieve relevant information. The proposed information retrieval framework is designed to assist users in accessing relevant information effectively and efficiently as it handles queries based on user preferences. Each component and module involved in the proposed framework will be explained in terms of functionality and the processes involved. | en |
dc.format.extent | 146-150 | en |
dc.language | English | en |
dc.language.iso | en | en |
dc.publisher | IACSIT Press | en |
dc.relation | The original publication is available from - IACSIT Press - https://doi.org/10.7763/IJMLC.2014.V4.403 - http://www.ijmlc.org/papers/403-LC037.pdf | en |
dc.relation.uri | http://www.ijmlc.org/papers/403-LC037.pdf | en |
dc.relation.uri | https://doi.org/10.7763/IJMLC.2014.V4.403 | en |
dc.rights | Copyright © 2008-2015. International Journal of Machine Learning and Computing. All rights reserved. | en |
dc.subject | information retrieval | en |
dc.subject | information retrieval framework | en |
dc.subject | semantic web | en |
dc.title | A robust framework for web information extraction and retrieval | en |
dc.type | Journal Article | |
lu.contributor.unit | Lincoln University | en |
lu.contributor.unit | Faculty of Environment, Society and Design | en |
lu.contributor.unit | School of Landscape Architecture | en |
dc.identifier.doi | 10.7763/IJMLC.2014.V4.403 | en |
dc.subject.anzsrc | 0801 Artificial Intelligence and Image Processing | en |
dc.relation.isPartOf | International Journal of Machine Learning and Computing | en |
pubs.issue | 2 | en |
pubs.organisational-group | /LU | |
pubs.organisational-group | /LU/Faculty of Environment, Society and Design | |
pubs.organisational-group | /LU/Faculty of Environment, Society and Design/SOLA | |
pubs.organisational-group | /LU/Research Management Office | |
pubs.organisational-group | /LU/Research Management Office/QE18 | |
pubs.publication-status | Published | en |
pubs.publisher-url | http://www.ijmlc.org/papers/403-LC037.pdf | en |
pubs.volume | 4 | en |
dc.identifier.eissn | 2010-3700 | en |
lu.identifier.orcid | 0000-0002-4991-3340 | |