Bidirectional long-short term memory and conditional random field for tourism named entity recognition

Abstract

<p><span>The common thing to do when planning a trip is to search for a tourist destination. This process is often done using search engines and reading articles on the internet. However, it takes much time to search for such information, as to obtain relevant information, we have to read some available articles. Named entity recognition (NER) can detect named entities in a text to help users find the desired information. This study aims to create a NER model that will help to detect tourist attractions in an article. The articles used for the dataset are English articles obtained from the internet. We built our NER model using bidirectional long-short term memory (BiLSTM) and conditional random fields (CRF), with Word2Vec as a feature. Our proposed model achieved the best with an average F1-Score of 75.25% compared to all scenarios tested.</span></p>

BERT-based tourism named entity recognition: making use of social media for travel recommendations

“…The results from this research complement our previous research to give more elaborate recommendations for tourists. Furthermore, comparing our current BERT-based NER model to our previous study and experiments in developing NER model using BiLSTM-CRF ( Zahra, Hidayatullah & Rani, 2022 ), our BERT-based model is proven to deliver better performance (80% in F1-score) rather than the BiLSTM-CRF-based model (75.25% in F1-score).…”

Implementing deep learning-based named entity recognition for obtaining narcotics abuse data in Indonesia

“…Research related to NER with a general domain scope is usually characterized by the use of general entities such as name of person (PER), name of place/location (LOC), and name of organization (ORG) without any specific purpose for what needs these entities are chosen. Research related to the application of Indonesian language NER in certain specific domains, such as [11]- [14], is quite rare. In fact, many applications of NER can be carried out in certain specific domains, such as the application of NER to extract  ISSN: 2252-8938 Int J Artif Intell, Vol.…”