Khmer Semantic Search Engine

Research on Khmer semantic search engines aims to improve information retrieval in the Khmer language, addressing challenges posed by its complex writing system and limited existing NLP resources. Current efforts focus on developing robust keyword extraction techniques using stop word dictionaries and advanced algorithms like word embeddings and neural networks (including RNNs and CNNs) for improved text classification and semantic modeling. These advancements are crucial for enhancing the accuracy and efficiency of Khmer search engines, thereby improving access to digital information for Khmer speakers and contributing significantly to the development of NLP tools for low-resource languages.