Web Crawler for Indexing Video e-Learning Resources: A YouTube Case Study

The main objective of the current paper is to develop and validate an algorithm focused on au-tomatically indexing YouTube e-learning resources about a certain domain of interest. After identifying the keywords specific to the desired domain, a web crawler is developed for evaluat-ing video resource...

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Bibliographic Details
Main Author: Bogdan IANCU
Format: Article
Language:English
Published: Inforec Association 2019-01-01
Series:Informatică economică
Subjects:
NER
Online Access:http://revistaie.ase.ro/content/90/02%20-%20iancu.pdf
Description
Summary:The main objective of the current paper is to develop and validate an algorithm focused on au-tomatically indexing YouTube e-learning resources about a certain domain of interest. After identifying the keywords specific to the desired domain, a web crawler is developed for evaluat-ing video resources (from the YouTube platform) in terms of relevance for that domain. Once the most relevant video resources are found, they are indexed with the usage of a NER engine applied on their transcripts. In this manner, semantic queries can be used further in order to find exactly the needed information inside these multimedia resources. The crawler will repeat the indexing process daily in order to maintain the repository of semantically indexed videos up to date. The final chapter presents the obtained results together with the validation of the model.
ISSN:1453-1305
1842-8088