BiLSTM-Based Named Entity Recognition for Itihasa Digital Heritage: Towards Cultural Tourism Information Services

DOI

10.2991/978-94-6239-805-4_19How to use a DOI?

Keywords

BiLSTM; Cultural Tourism; Digital Heritage; Itihasa; Named Entity Recognition; Smart Tourism

Abstract

The Mahabharata and Ramayana are central Itihasa narratives that continue to shape literary, performative, and cultural traditions in Indonesia. Their digitization creates opportunities for cultural heritage documentation, but long narrative texts remain difficult to search and organize when entities are not represented explicitly. This study develops a Bidirectional Long Short-Term Memory (BiLSTM) model for Named Entity Recognition (NER) in digitized Itihasa texts. The model processes contextual information in both directions and assigns BIOES sequence labels to entity mentions. The corpus comprises 1,982 Ramayana sentences and 9,814 Mahabharata sentences, divided into 80% training and 20% testing sets. At 30 epochs, the reported token-level testing accuracy reached 99.79% for Ramayana and 99.95% for Mahabharata. These values show stable token classification, although entity-level precision, recall, and F1-score are required for a complete NER assessment. Beyond digital preservation, structured entities can support cultural-tourism search, heritage knowledge bases, interpretive applications, and smart-tourism services that connect characters, places, kingdoms, events, and other cultural concepts. The study therefore positions domain-specific NER as a technical layer for both digital heritage management and tourism-oriented access to classical narratives.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ni Luh Wiwik Sri Rahayu Ginantra
AU  - Ni Made Novi Sintya Dewi
AU  - Wayan Gede Suka Parwita
PY  - 2026
DA  - 2026/10/08
TI  - BiLSTM-Based Named Entity Recognition for Itihasa Digital Heritage: Towards Cultural Tourism Information Services
BT  - Proceedings of the International Conference on Sustainable Green Tourism Applied Science - Engineering Applied Science 2026 (ICOSTAS-EAS 2026)
PB  - Atlantis Press
SP  - 173
EP  - 184
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6239-805-4_19
DO  - 10.2991/978-94-6239-805-4_19
ID  - Ginantra2026
ER  -