对古籍知识进行知识组织，以便深入挖掘古籍文献中的知识元素对于彰显文化自信，推动中华民族的伟大复兴具有积极意义。借助于先进的信息处理方法，知识计算能够在大量的文献载体中提取知识元素，高效完成知识获取与知识建模，从而达成古籍文献知识组织的预期目标。文章以齐普夫定律作为古籍知识计算的理论基础，发展了一套高低词频区分标准，并考虑到古籍文献中的词语存在长尾分布的现状，使用频数-位次统计法对同频词加以处理，以提高古籍文献知识组织的效率。文章的研究明确了古籍知识计算的理论基础与具体的基础指标，为后续知识组织工作的开展提供了借鉴。

It is of the significance to organize the knowledge of ancient literatures so as to deeply explore the knowledge elements in these information resources to highlight cultural self-confidence and promote the great rejuvenation of the Chinese nation. With the aids of advanced information processing methods, knowledge computing can extract knowledge elements from a large number of document carriers, efficiently complete knowledge acquisition and knowledge modeling, and achieve the expected goal of knowledge organization of ancient literatures. This paper takes Zipf's law as the theoretical basis of ancient literature knowledge computing, develops a set of word frequency turn point identification standards. Due to the long tail distribution of words in ancient literatures, a frequency position statistics procedure is conducted to deal with words with the same frequency to improve the efficiency of knowledge organization of ancient literatures. This research in clarifies the theoretical basis and specific basic indicators of ancient literature knowledge computing, and provides a reference for the follow-up work of knowledge organization.