The search engine process is crucial for document content retrieval. For
Khmer documents, a tool is needed to extract essential keywords. Despite the
daily generation of significant Khmer content, Cambodians struggle to find
necessary documents due to the lack of an effective semantic searching tool.
Even Google does not deliver high accuracy for Khmer content. Semantic search
engines improve search results by employing advanced algorithms to understand
various content types. With the rise in Khmer digital content such as reports,
articles, and social media feedback enhanced search capabilities are essential.
This research proposes the first Khmer Semantic Search Engine (KSE), designed
to improve traditional Khmer search methods. Utilizing semantic matching
techniques and formally annotated semantic content, our tool extracts
meaningful keywords from user queries performs precise matching, and provides
the best matching offline documents and online URL documents. We propose two
semantic search frameworks based on keyword extraction and semantic search
matching. Additionally, we developed tools for data preparation, including
document addition and manual keyword extraction. To evaluate performance, we
created a ground truth dataset and discussed issues related to searching and
semantic search. Our findings show how understanding search term semantics can
lead to more accurate results.

该研究介绍了第一种高棉语义搜索引擎（KSE），旨在改进传统高棉搜索方法，利用语义匹配和注释的语义内容从用户查询中提取有意义的关键词，进行精确匹配，并提供最匹配的离线和在线文档。研究结果表明，理解搜索术语的语义可以带来更准确的结果。