Details
| Original language | English |
|---|---|
| Title of host publication | Digital Libraries for Open Knowledg |
| Subtitle of host publication | e22nd International Conference on Theory and Practice of Digital Libraries, TPDL 2018, Proceedings |
| Editors | Eva Mendez, Cristina Ribeiro, Gabriel David, João Correia Lopes, Fabio Crestani |
| Publisher | Springer Verlag |
| Pages | 286-292 |
| Number of pages | 7 |
| ISBN (print) | 9783030000653 |
| Publication status | Published - 5 Sept 2018 |
| Event | 22nd International Conference on Theory and Practice of Digital Libraries, TPDL 2018 - Porto, Portugal Duration: 10 Sept 2018 → 13 Sept 2018 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 11057 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (electronic) | 1611-3349 |
Abstract
The amount of available videos in the Web has significantly increased not only for entertainment etc., but also to convey educational or scientific information in an effective way. There are several web portals that offer access to the latter kind of video material. One of them is the TIB AV-Portal of the Leibniz Information Centre for Science and Technology (TIB), which hosts scientific and educational video content. In contrast to other video portals, automatic audiovisual analysis (visual concept classification, optical character recognition, speech recognition) is utilized to enhance metadata information and semantic search. In this paper, we propose to further exploit and enrich this automatically generated information by linking it to the Integrated Authority File (GND) of the German National Library. This information is used to derive a measure to compare the similarity of two videos which serves as a basis for recommending semantically similar videos. A user study demonstrates the feasibility of the proposed approach.
Keywords
- Linked data, Semantic enrichment, Video recommendation
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
Cite this
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Digital Libraries for Open Knowledg: e22nd International Conference on Theory and Practice of Digital Libraries, TPDL 2018, Proceedings. ed. / Eva Mendez; Cristina Ribeiro; Gabriel David; João Correia Lopes; Fabio Crestani. Springer Verlag, 2018. p. 286-292 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11057 LNCS).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Recommending scientific videos based on metadata enrichment using linked open data
AU - Medrek, Justyna
AU - Otto, Christian
AU - Ewerth, Ralph
N1 - Publisher Copyright: © 2018, Springer Nature Switzerland AG. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/9/5
Y1 - 2018/9/5
N2 - The amount of available videos in the Web has significantly increased not only for entertainment etc., but also to convey educational or scientific information in an effective way. There are several web portals that offer access to the latter kind of video material. One of them is the TIB AV-Portal of the Leibniz Information Centre for Science and Technology (TIB), which hosts scientific and educational video content. In contrast to other video portals, automatic audiovisual analysis (visual concept classification, optical character recognition, speech recognition) is utilized to enhance metadata information and semantic search. In this paper, we propose to further exploit and enrich this automatically generated information by linking it to the Integrated Authority File (GND) of the German National Library. This information is used to derive a measure to compare the similarity of two videos which serves as a basis for recommending semantically similar videos. A user study demonstrates the feasibility of the proposed approach.
AB - The amount of available videos in the Web has significantly increased not only for entertainment etc., but also to convey educational or scientific information in an effective way. There are several web portals that offer access to the latter kind of video material. One of them is the TIB AV-Portal of the Leibniz Information Centre for Science and Technology (TIB), which hosts scientific and educational video content. In contrast to other video portals, automatic audiovisual analysis (visual concept classification, optical character recognition, speech recognition) is utilized to enhance metadata information and semantic search. In this paper, we propose to further exploit and enrich this automatically generated information by linking it to the Integrated Authority File (GND) of the German National Library. This information is used to derive a measure to compare the similarity of two videos which serves as a basis for recommending semantically similar videos. A user study demonstrates the feasibility of the proposed approach.
KW - Linked data
KW - Semantic enrichment
KW - Video recommendation
UR - http://www.scopus.com/inward/record.url?scp=85053825232&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-00066-0_25
DO - 10.1007/978-3-030-00066-0_25
M3 - Conference contribution
AN - SCOPUS:85053825232
SN - 9783030000653
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 286
EP - 292
BT - Digital Libraries for Open Knowledg
A2 - Mendez, Eva
A2 - Ribeiro, Cristina
A2 - David, Gabriel
A2 - Lopes, João Correia
A2 - Crestani, Fabio
PB - Springer Verlag
T2 - 22nd International Conference on Theory and Practice of Digital Libraries, TPDL 2018
Y2 - 10 September 2018 through 13 September 2018
ER -