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Reseach Article

Creating a Semantic Academic Lecture Video Search Engine via Enrichment Textual and Temporal Features of Subtitled YouTube EDU Media Fragments

by Babak Farhadi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 96 - Number 13
Year of Publication: 2014
Authors: Babak Farhadi
10.5120/16853-6719

Babak Farhadi . Creating a Semantic Academic Lecture Video Search Engine via Enrichment Textual and Temporal Features of Subtitled YouTube EDU Media Fragments. International Journal of Computer Applications. 96, 13 ( June 2014), 13-18. DOI=10.5120/16853-6719

@article{ 10.5120/16853-6719,
author = { Babak Farhadi },
title = { Creating a Semantic Academic Lecture Video Search Engine via Enrichment Textual and Temporal Features of Subtitled YouTube EDU Media Fragments },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 96 },
number = { 13 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 13-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume96/number13/16853-6719/ },
doi = { 10.5120/16853-6719 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:21:38.559693+05:30
%A Babak Farhadi
%T Creating a Semantic Academic Lecture Video Search Engine via Enrichment Textual and Temporal Features of Subtitled YouTube EDU Media Fragments
%J International Journal of Computer Applications
%@ 0975-8887
%V 96
%N 13
%P 13-18
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we propose a new framework to annotating subtitled YouTube EDU media fragments using textual features such as exert all the basic portions extracted from the web-based natural language processors of in relation to subtitles and temporal features such as duration of the media fragments where proper entities are spotted. We've created the SY-E-MFSE (Subtitled YouTube EDU Media Fragment Search Engine) as a framework to cruising on the subtitled YouTube EDU videos resident in the Linked Open Data (LOD) cloud. For realizing this purpose, we propose Unifier Module of Outcomes of Web-Based Natural Language Processors (UM-OWNLP) for extracting the essential portions of the 10 NLP tools that are based on the web, from subtitles associated to YouTube videos in order to generate media fragments annotated with resources from the LOD cloud. Then, we propone Unifier Module of Outcomes of Web-Based Named Entity (NE) Booster Processors (UM-OWNEBP) containing the six web Application Programming Interfaces (API) to boost outcomes of NEs obtained from UM-OWNLP. We've presented 'UM-OWNLP ontology' to support all the 10 NLP web-based tools ontological features and representing them in a steadfast framework.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Subtitled YouTube EDU video textual metadata semantic web video annotation web-based natural language processor.