English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In recent years, natural language processing has gained significantpopularity in various sectors, including the legal domain. This paper presentsNeCo Team's solutions to the Vietnamese text processing tasks provided in theAutomated Legal Question Answering Competition 2023 (ALQAC 2023), focusing onlegal domain knowledge acquisition for low-resource languages through dataenrichment. Our methods for the legal document retrieval task employ acombination of similarity ranking and deep learning models, while for thesecond task, which requires extracting an answer from a relevant legal articlein response to a question, we propose a range of adaptive techniques to handledifferent question types. Our approaches achieve outstanding results on bothtasks of the competition, demonstrating the potential benefits andeffectiveness of question answering systems in the legal field, particularlyfor low-resource languages.

NeCo@ALQAC 2023: Legal Domain Knowledge Acquisition for Low-Resource Languages through Data Enrichment