Product and Industrial Classification Code Suggestion System for Thai Language

2022 17th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP) Pub Date : 2022-11-05 DOI:10.1109/iSAI-NLP56921.2022.9960262

R. Siricharoenchai, Panchapawn Chatsuwan, Paramet Tanwanont, Sarunruk Janbradab, Navaporn Surasvadi, S. Thajchayapong

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Abstract

In this work, a system is created to suggest product/ service code and industrial classification code for Thai language. The system can suggest UNSPSC and TSIC codes relevant to query terms via indexing search. Techniques used in this work are based on knowledge of text processing and text similarity, as well as indexing. Through a complexity analysis, the system has been proved efficient as it can retrieve data about 1,000 times faster than traditional methods. Furthermore, Mean Reciprocal Rank (MRR) was employed to evaluate the search results of 1,000 products and services. The results showed that the proposed system achieved the MRR of 0.46, indicating the relevant search result is approximately in the second or third rank. Currently, the proposed system has been implemented as a part of SMEs registration process in the OSMEP website to support Thai SMEs to access government procurement.

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泰语产品和行业分类代码建议系统

在这项工作中，创建了一个系统来建议泰语的产品/服务代码和行业分类代码。通过索引搜索，系统可以推荐与查询词相关的UNSPSC和TSIC代码。在这项工作中使用的技术是基于文本处理和文本相似度的知识，以及索引。通过复杂性分析，该系统的检索速度比传统方法快1000倍左右，证明了其效率。此外，平均倒数秩(MRR)被用来评估1000个产品和服务的搜索结果。结果表明，所提系统的MRR为0.46，表明相关搜索结果大致处于第二或第三等级。目前，拟议的系统已作为中小企业注册流程的一部分在OSMEP网站上实施，以支持泰国中小企业获得政府采购。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2022 17th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)

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