A TV Content Augmentation System Exploiting Rule Based Named Entity Recognition Method

Date

2015-09-24

Author

Isiklar, Yunus Emre
Cicekli, Nihan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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This paper presents a TV content augmentation system that enhances the contents of TVprograms by retrieving context related data and presenting them to the viewers without the necessity of another device. The paper presents both the conceptual description of the system and a prototype implementation. The implementation utilizes program descriptions crawled from web resources in order to extract named entities such as person names, locations, organizations, etc. For this purpose, a rule based Named Entity Recognition (NER) algorithm is developed for Turkish texts. Information about the extracted entities is retrieved from Wikipedia with the help of semantic disambiguation and its summarized form is presented to the users. A set of experiments have been conducted on two different data sets in order to evaluate the performance of the rule based NER algorithm and the behavior of the TV content augmentation system.

Subject Keywords

Semantic disambiguation, Named Entity Recognition (NER), EPG (Electronic Program Guide), Content augmentation, Connected TV

URI

https://hdl.handle.net/11511/65649

DOI

https://doi.org/10.1007/978-3-319-22635-4_32

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

Y. E. Isiklar and N. Cicekli, “A TV Content Augmentation System Exploiting Rule Based Named Entity Recognition Method,” 2015, vol. 363, p. 349, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/65649.