A Topic Modelling-Based Framework for Mining Digital Library’s Text Documents
| dc.contributor.author | Olowookere, Toluwase Ayobami | |
| dc.date.accessioned | 2022-05-05T18:42:10Z | |
| dc.date.available | 2022-05-05T18:42:10Z | |
| dc.date.issued | 2015-12 | |
| dc.description.abstract | The impacts and contributions of scholarly research work in the economic growth and sustainability of any nation cannot be overemphasized. The digital library has emerged as a reliable resource for provisioning researchers with scholarly knowledge (erudition that result from the research works) which are documented and published in form of journal articles, technical reports or conference proceedings amongst others. However, as academic institutions and publishers around the world are choosing to make their thesis, dissertation and journal articles available in digital form, this electronic repository of knowledge (the digital library), though organized, is flooded with an exploding large collections of documents filled with hidden but useful information in form of the varieties of topics of discourse inherent in them. Thus making it imperative to develop a flexible means to automatically discover the topics that pervade the collections in such digital library. Currently, the application of topic modelling technique holds great promises and has tremendous results in extracting the topical contents of document corporal. In this regard, this paper presents a Topic Modelling-based framework for mining document collections of a digital library for topical structure discovery alongside topic-based similarities search between document collection pairs, by means of integrating the base topic modelling algorithm and inverted Kullback-Leibler divergence mechanism. The framework shows potency in the automatic discovery of topical structures of document collections and it as well describes the capability of finding topic-based similarities between document collection pairs. | en_US |
| dc.identifier.citation | T.A. Olowookere, B.O. Eke. & L.U. Oghenekaro (2015): A Topic Modelling-Based Framework for Mining Digital Library’s Text Documents. Afr J. of Comp & ICTs. Vol 8, No. 4. Pp 19-26. | en_US |
| dc.identifier.issn | 2006-1781 | |
| dc.identifier.uri | http://dspace.run.edu.ng:8080/jspui/handle/123456789/2707 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | African Journal of Computing & ICT | en_US |
| dc.subject | Digital library | en_US |
| dc.subject | Document collection | en_US |
| dc.subject | Text mining | en_US |
| dc.subject | Topic modeling | en_US |
| dc.title | A Topic Modelling-Based Framework for Mining Digital Library’s Text Documents | en_US |
| dc.type | Article | en_US |