BibRank:基于元数据的自动关键词提取平台

IF 2.4 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Information (Switzerland) Pub Date : 2023-10-07 DOI:10.3390/info14100549
Abdelrhman Eldallal, Eduard Barbu
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引用次数: 0

摘要

自动关键字提取涉及识别文档中的基本短语。这些关键短语在文档分类、聚类、推荐、索引、搜索、摘要和文本简化等各种任务中都是至关重要的。本文介绍了一个集成关键字数据集的平台,便于对关键字提取算法进行评估。该平台包括BibRank,这是一种自动关键字提取算法,利用通过解析BibTeX格式的书目数据获得的丰富数据集。BibRank将创新的加权技术与位置、统计和词共现信息相结合,从文档中提取关键短语。该平台对研究人员和开发人员来说是有价值的,他们希望增强他们的关键词提取算法,并推动自然语言处理领域的发展。
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BibRank: Automatic Keyphrase Extraction Platform Using Metadata
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.
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来源期刊
Information (Switzerland)
Information (Switzerland) Computer Science-Information Systems
CiteScore
6.90
自引率
0.00%
发文量
515
审稿时长
11 weeks
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