Automatic Keyphrase Extraction involves identifying essential phrases in a document. These keyphrases are crucial in various tasks such as document classification, clustering, recommendation, indexing, searching, summarization, and text simplification. This paper introduces a platform that integrates keyphrase datasets and facilitates the evaluation of keyphrase extraction algorithms. The platform includes BibRank, an automatic keyphrase extraction algorithm that leverages a rich dataset obtained by parsing bibliographic data in BibTeX format. BibRank combines innovative weighting techniques with positional, statistical, and word co-occurrence information to extract keyphrases from documents. The platform proves valuable for researchers and developers seeking to enhance their keyphrase extraction algorithms and advance the field of natural language processing.

翻译：摘要：自动关键词提取涉及识别文档中的关键短语。这些关键短语在文档分类、聚类、推荐、索引、搜索、摘要和文本简化等多种任务中至关重要。本文介绍了一个整合关键词数据集并促进关键词提取算法评估的平台。该平台包含BibRank算法，这是一种自动关键词提取算法，通过解析BibTeX格式的文献数据来利用丰富的数据集。BibRank将创新性的加权技术与位置信息、统计信息和词语共现信息相结合，从文档中提取关键词。该平台对于希望改进其关键词提取算法并推动自然语言处理领域发展的研究人员和开发者而言具有重要价值。