Application Of Topic Mining And Prediction Modeling Tools For Library And Information Science Journals

This chapter presents a method for analyzing text data called topic modeling and applying it to the field of Library and Information Science. It describes the importance and usage of topic mining for researchers and librarians. An experiment study is also covered which applies topic modeling in a real scenario, where five model topics for the articles published in DESIDOC Journal of Library and Information Technology for the year 2017 using Topic-Modeling-Toolkit and prediction modeling is constructed using RapidMiner toolbox.

Related Organizations

University of Delhi
India

Keywords

Text Mining, Topic Modeling, LDA, Predictive Modeling

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	2
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average