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  4. Vol 10, Issue 2, 2026

Bayesian-Grid Hyperparameter Optimization with Bootstrap Validation for Ensemble Risk Stratification on Tabular Data

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DOI: 10.23977/acss.2026.100203 | Downloads: 2 | Views: 74

Author(s)

Weiyi Zhu 1, Can Wu 1, Hongxun Ye 1, Shengjun Xu 1, Ting Zhong 1

Affiliation(s)

1 School of Big Data and Statistics, Sichuan Tourism University, Chengdu, Sichuan, China

Corresponding Author

Ting Zhong

ABSTRACT

Constructing structured knowledge representations from large-scale unstructured text streams remains a fundamental challenge in natural language processing, requiring the joint solution of entity recognition, relation extraction, event evolution analysis, and graph visualization within a coherent end-to-end pipeline. This paper presents a knowledge graph construction framework that integrates pretrained language model based named entity recognition with rule-augmented relation triple extraction and force-directed graph layout for interactive visualization of the resulting structure. The proposed architecture employs a five-class entity schema covering events, persons, organizations, locations, and temporal expressions, applies a transformer-based sequence labeling model for entity boundary detection, and constructs subject-predicate-object triples through a dependency-guided extraction module that resolves coreference and disambiguates polysemous mentions. Event temporal evolution is recovered by chaining triples along their timestamp annotations to expose causal and sequential dependencies. The pipeline was evaluated on a corpus of 4,328 domain-specific documents collected through web crawling and preprocessed by deduplication, tokenization, and stopword removal, yielding 18,754 entity mentions and 12,463 relation triples. The proposed framework achieves a named entity recognition F1 score of 91.4% and a relation extraction F1 of 87.6%, exceeding BiLSTM-CRF and rule-based baselines by 5.2 and 7.8 percentage points respectively. The constructed graph supports interactive exploration through force-directed visualization with optimized label placement.

KEYWORDS

Named Entity Recognition, Relation Triple Extraction, Knowledge Graph Construction, Force-Directed Graph Layout, Event Temporal Evolution, Pretrained Language Model

CITE THIS PAPER

Weiyi Zhu, Can Wu, Hongxun Ye, Shengjun Xu, Ting Zhong. Bayesian-Grid Hyperparameter Optimization with Bootstrap Validation for Ensemble Risk Stratification on Tabular Data. Advances in Computer, Signals and Systems (2026). Vol. 10, No. 2, 19-29. DOI: http://dx.doi.org/10.23977/acss.2026.100203.

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