TY - GEN
T1 - A General Process for the Semantic Annotation and Enrichment of Electronic Program Guides
AU - Gonzalez-Toral, Santiago
AU - Espinoza-Mejia, Mauricio
AU - Palacio-Baus, Kenneth
AU - Saquicela, Victor
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - Electronic Program Guides (EPGs) are usual resources aimed to inform the audience about the programming being transmitted by TV stations and cable/satellite TV providers. However, they only provide basic metadata about the TV programs, while users may want to obtain additional information related to the content they are currently watching. This paper proposes a general process for the semantic annotation and subsequent enrichment of EPGs using external knowledge bases and natural language processing techniques with the aim to tackle the lack of immediate availability of related information about TV programs. Additionally, we define an evaluation approach based on a distributed representation of words that can enable TV content providers to verify the effectiveness of the system and perform an automatic execution of the enrichment process. We test our proposal using a real-world dataset and demonstrate its effectiveness by using different knowledge bases, word representation models and similarity measures. Results showed that DBpedia and Google Knowledge Graph knowledge bases return the most relevant content during the enrichment process, while word2vec and fasttext models with Words Mover’s Distance as similarity function can be combined to validate the effectiveness of the retrieval task.
AB - Electronic Program Guides (EPGs) are usual resources aimed to inform the audience about the programming being transmitted by TV stations and cable/satellite TV providers. However, they only provide basic metadata about the TV programs, while users may want to obtain additional information related to the content they are currently watching. This paper proposes a general process for the semantic annotation and subsequent enrichment of EPGs using external knowledge bases and natural language processing techniques with the aim to tackle the lack of immediate availability of related information about TV programs. Additionally, we define an evaluation approach based on a distributed representation of words that can enable TV content providers to verify the effectiveness of the system and perform an automatic execution of the enrichment process. We test our proposal using a real-world dataset and demonstrate its effectiveness by using different knowledge bases, word representation models and similarity measures. Results showed that DBpedia and Google Knowledge Graph knowledge bases return the most relevant content during the enrichment process, while word2vec and fasttext models with Words Mover’s Distance as similarity function can be combined to validate the effectiveness of the retrieval task.
KW - Electronic programming guides
KW - Natural language processing
KW - Semantic enrichment
KW - Word embeddings
UR - https://www.scopus.com/pages/publications/85066117874
U2 - 10.1007/978-3-030-21395-4_6
DO - 10.1007/978-3-030-21395-4_6
M3 - Contribución a la conferencia
AN - SCOPUS:85066117874
SN - 9783030213947
T3 - Communications in Computer and Information Science
SP - 72
EP - 86
BT - Knowledge Graphs and Semantic Web - 1st Iberoamerican Conference, KGSWC 2019, Proceedings
A2 - Villazón-Terrazas, Boris
A2 - Hidalgo-Delgado, Yusniel
PB - Springer Verlag
T2 - 1st Iberoamerican Knowledge Graphs and Semantic Web Conference, KGSWC 2019
Y2 - 23 June 2019 through 30 June 2019
ER -