@inproceedings{236c976fd2bc4b07a111cb616f034314,
title = "Cat2Type: Wikipedia Category Embeddings for Entity Typing in Knowledge Graphs",
abstract = "The entity type information in Knowledge Graphs (KGs) such as DBpedia, Freebase, etc. is often incomplete due to automated generation. Entity Typing is the task of assigning or inferring the semantic type of an entity in a KG. This paper introduces an approach named Cat2Type which exploits the Wikipedia Categories to predict the missing entity types in a KG. This work extracts information from Wikipedia Category names and the Wikipedia Category graph which are the sources of rich semantic information about the entities. In Cat2Type, the characteristic features of the entities encapsulated in Wikipedia Category names are exploited using Neural Language Models. On the other hand, a Wikipedia Category graph is constructed to capture the connection between the categories. The Node level representations are learned by optimizing the neighbourhood information on the Wikipedia category graph. These representations are then used for entity type prediction via classification. The performance of Cat2Type is assessed on two real-world benchmark datasets DBpedia630k and FIGER. The experiments depict that Cat2Type obtained a significant improvement over state-of-the-art approaches.",
keywords = "entity type prediction, language models, node embeddings, wikipedia categories",
author = "Russa Biswas and Radina Sofronova and Harald Sack and Mehwish Alam",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 11th ACM International Conference on Knowledge Capture, K-CAP 2021 ; Conference date: 02-12-2021 Through 03-12-2021",
year = "2021",
month = dec,
day = "2",
doi = "10.1145/3460210.3493575",
language = "English",
series = "K-CAP 2021 - Proceedings of the 11th Knowledge Capture Conference",
publisher = "Association for Computing Machinery, Inc",
pages = "81--88",
booktitle = "K-CAP 2021 - Proceedings of the 11th Knowledge Capture Conference",
}