Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Named entity equivalent has been playing a significant role in the processing of cross-language information. Hover limited by the corpora resource, few in-depth studies have been made on the extraction of the bilingual Chinese-Khmer named entity equivalents. On account of this, this paper proposes a Wikipedia-based approach, utilizes the internal b links in Wikipedia and computes the feature similarity to extract the bilingual Chinese-Khmer named entity equivalents. The experimental result shows that good effect has been achieved when the entity equivalents are acquired through the internal b links in Wikipedia with F value up to 90.67%. Also it shows that the result is quite favorable when the bilingual Chinese-Khmer named entity equivalents are acquired through the computation of feature similarity, turning out that the method proposed in this paper is able to give better effect.
['Qing Xia', 'Xin Yan', 'Zhengtao Yu', 'Shengxiang Gao']
I am writing a research paper on a idea Research on the Extraction of Wikipedia-Based Chinese-Khmer Named Entity Equivalents
[{"from": "human", "value": "I am writing a research paper on a idea Research on the Extraction of Wikipedia-Based Chinese-Khmer Named Entity Equivalents"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Named entity equivalent has been playing a significant role in the processing of cross-language information. Hover limited by the corpora resource, few in-depth studies have been made on the extraction of the bilingual Chinese-Khmer named entity equivalents. On account of this, this paper proposes a Wikipedia-based approach, utilizes the internal b links in Wikipedia and computes the feature similarity to extract the bilingual Chinese-Khmer named entity equivalents. The experimental result shows that good effect has been achieved when the entity equivalents are acquired through the internal b links in Wikipedia with F value up to 90.67%. Also it shows that the result is quite favorable when the bilingual Chinese-Khmer named entity equivalents are acquired through the computation of feature similarity, turning out that the method proposed in this paper is able to give better effect."}]