Thai Succession and Family Law Ontology Building Using Ant Colony Algorithm

Boonchom, Vi-sit; Soonthornphisaj, Nuanwan

doi:10.1007/978-3-642-14888-0_3

Cited by 4 publications

(7 citation statements)

References 9 publications

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“…Boolean and natural language 5.1 [32,41,115] Conceptual search and case-based retrieval 5.2 [77,118] Question answering 5.3 [35,88] Query expansion 5.4 [15,30,100] Query reduction 5.5 [70][71][72] Search Result Diversification 5.6 [61] Use of citation networks 5.7 [92,126] Deeper understanding of texts 5.8 [19,43,85,106] Table 3. Summary of methods and main works examined in this survey that comprise these methods.…”

Section: Methods Section Main Work Examinedmentioning

confidence: 99%

Case law retrieval: problems, methods, challenges and evaluations in the last 20 years

Locke¹,

Zuccon²

2022

Preprint

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Case law retrieval is the retrieval of judicial decisions relevant to a legal question. Case law retrieval comprises a significant amount of a lawyer's time, and is important to ensure accurate advice and reduce workload. We survey methods for case law retrieval from the past 20 years and outline the problems and challenges facing evaluation of case law retrieval systems going forward. Limited published work has focused on improving ranking in ad-hoc case law retrieval. But there has been significant work in other areas of case law retrieval, and legal information retrieval generally. This is likely due to legal search providers being unwilling to give up the secrets of their success to competitors. Most evaluations of case law retrieval have been undertaken on small collections and focus on related tasks such as question-answer systems or recommender systems. Work has not focused on Cranfield style evaluations and baselines of methods for case law retrieval on publicly available test collections are not present. This presents a major challenge going forward. But there are reasons to question the extent of this problem, at least in a commercial setting. Without test collections to baseline approaches it cannot be known whether methods are promising. Works by commercial legal search providers show the effectiveness of natural language systems as well as query expansion for case law retrieval. Machine learning is being applied to more and more legal search tasks, and undoubtedly this represents the future of case law retrieval.

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Section: Methods Section Main Work Examinedmentioning

confidence: 99%

Case law retrieval: problems, methods, challenges and evaluations in the last 20 years

Locke¹,

Zuccon²

2022

Preprint

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“…In addition, ThaiLegalWordNet is a Thai legal terminology created by a law expert that consists of legal terms and their related terms. The Thai law dictionary is used for ontology building using the expansion process [12]. However, taxonomy and a lexicon were applied for ontology construction.…”

Section: Related Workmentioning

confidence: 99%

“…Finally, a new interesting method for ontology construction is a core ontology or seed ontology. Core ontology extracted from Spanish privacy law, which consists of concepts and relations, is used for Spanish ontology building [14], whereas Thai legal ontology is constructed by the ontology expansion function using a seed ontology created by a law expert [15]. Furthermore, the Thai legal seed ontology is automatically created by the ATOB algorithm and used for automatic legal ontology construction [16].…”

Section: Related Workmentioning

confidence: 99%

“…It infers that the pheromone level affects retrieval performance. The drawback of the TLOE I algorithm is that it uses a manual seed ontology created by a legal expert and the expansion process needs too much computational time since the process is terminated after the first-level child nodes of the keyword are completed [12].…”

Section: Related Workmentioning

confidence: 99%

“…It provides a promising result in terms of retrieval performance. We found that TLOE I and TLOE II have similar efficiencies from the user’s point of view even if they have different ontology size and total processing time [15]. However, the TLOE II method uses a manual seed ontology, which makes it an expensive and time-consuming task for domain experts.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

ATOB algorithm: an automatic ontology construction for Thai legal sentences retrieval

Boonchom

Soonthornphisaj

2011

Journal of Information Science

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Ontology plays an important role in knowledge representation, especially in the domain of information retrieval. However, building ontology remains a challenging problem because it is a time-consuming task for experts. To overcome these drawbacks, we propose a novel approach called the Automatic Thai Legal Ontology Building (ATOB) algorithm for automatic legal ontology building and to improve the court sentences retrieval process. The ATOB can automatically generate seed ontology and expand the ontology using Thai legal terminology, i.e. TLlexicon. The expansion process is terminated automatically by the threshold parameter. Moreover, the ATOB applies the concept of the ant colony algorithm to improve the court sentences retrieval process. We conclude that the effective ontology should be weight-embedded. The empirical results demonstrate that the performance of the ATOB algorithm is better than that of the traditional search method. The performance figures for the ATOB framework measured in terms of precision, recall, F-measure and diversity are 0.90, 0.91, 0.90 and 0.39, respectively.

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Legal Ontology Construction Using ATOB Algorithm

Boonchom

Soonthornphisaj

2010

Business Information Systems Workshops

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Thai Succession and Family Law Ontology Building Using Ant Colony Algorithm

Cited by 4 publications

References 9 publications

Case law retrieval: problems, methods, challenges and evaluations in the last 20 years

Case law retrieval: problems, methods, challenges and evaluations in the last 20 years

ATOB algorithm: an automatic ontology construction for Thai legal sentences retrieval

Legal Ontology Construction Using ATOB Algorithm

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