Faced with the burgeoning volume of academic literature, researchers often need help with uncertain article quality and mismatches in term searches using traditional academic engines. We introduce IntellectSeeker, an innovative and personalized intelligent academic literature management platform to address these challenges. This platform integrates a Large Language Model (LLM)--based semantic enhancement bot with a sophisticated probability model to personalize and streamline literature searches. We adopted the GPT-3.5-turbo model to transform everyday language into professional academic terms across various scenarios using multiple rounds of few-shot learning. This adaptation mainly benefits academic newcomers, effectively bridging the gap between general inquiries and academic terminology. The probabilistic model intelligently filters academic articles to align closely with the specific interests of users, which are derived from explicit needs and behavioral patterns. Moreover, IntellectSeeker incorporates an advanced recommendation system and text compression tools. These features enable intelligent article recommendations based on user interactions and present search results through concise one-line summaries and innovative word cloud visualizations, significantly enhancing research efficiency and user experience. IntellectSeeker offers academic researchers a highly customizable literature management solution with exceptional search precision and matching capabilities. The code can be found here: https://github.com/LuckyBian/ISY5001

翻译：面对日益增长的学术文献量，研究人员在使用传统学术搜索引擎时，常面临文献质量不确定以及术语搜索不匹配的问题。为此，我们推出了IntellectSeeker——一个创新且个性化的智能学术文献管理平台，以应对这些挑战。该平台将基于大语言模型（LLM）的语义增强机器人与一个复杂的概率模型相结合，以实现个性化且高效的文献搜索。我们采用GPT-3.5-turbo模型，通过多轮少样本学习，将日常语言转化为适用于多种场景的专业学术术语。这一改进尤其有益于学术新手，能有效弥合一般性查询与学术术语之间的鸿沟。概率模型则能智能筛选学术文献，使其紧密贴合用户基于明确需求和行为模式所体现的特定兴趣。此外，IntellectSeeker还集成了先进的推荐系统和文本压缩工具。这些功能能够根据用户交互进行智能文献推荐，并通过简洁的单行摘要和创新的词云可视化呈现搜索结果，从而显著提升研究效率和用户体验。IntellectSeeker为学术研究者提供了一个高度可定制、具备卓越搜索精度与匹配能力的文献管理解决方案。相关代码可见：https://github.com/LuckyBian/ISY5001