Semi-automatic Ontology Builder Based on Relation Extraction from Textual Data

Thukral, Anjali; Jain, Ayush; Aggarwal, Mudit; Sharma, Mehul

doi:10.1007/978-981-10-8237-5_33

Cited by 3 publications

(1 citation statement)

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“…There are several automated or semi-automated ways proposed for keyword extraction. These ways are complicated and some are based on expert knowledge or require the domain specific thesauri or ontologies [51,52], and some need a large corpus of the related text to learn the semantic of terms [53,54]. To avoid these complexity a simple heuristic key extraction function is developed in this study.…”

Section: Preprocessingmentioning

confidence: 99%

Evolution of IT, Management and Industrial Engineering research: a topic model approach

et al. 2020

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Information Technology (IT), Management and Industrial Engineering are correlated academic disciplines which their publications rose significantly over the last decades. The aim of this study is analyzing the research evolution, determining the important topics and areas and depiction the trend of interdisciplinary topics in these domains. To accomplish this, the text mining techniques are used and the combination of bibliographic analysis and topic modeling approach are applied on their publications in the WOS repository over the last 20 years. In the topic extraction process, a heuristic function was suggested to key extraction, and some new applicable criteria were defined to compare the topics. Moreover, a novel approach was proposed to determine the high-level category for each topic. The results determined the hot-important topics and incremented, decremented and fixed topics are identified. Subsequently, comparing the high-level research areas confirmed the strong scientific relationships between them. This study presents a deep knowledge about internal research evolution of domains and illustrates the effect of topics on each other over the past 20 years. Furthermore, the methodology of this study could be applied to determine the interdisciplinary topics and observe the research evolution of other academic domains.

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