基于选择性的克罗地亚语新闻关键词抽取
Toward Selectivity Based Keyword Extraction for Croatian News
摘要：
克罗地亚语基于网络的关键词提取的初步报告是一种从复杂网络中提取关键词的无监督方法。我们建立了一个新的网络测量节点的选择性，基于图的中心性方法的研究的动机，我们的方法。节点选择性被定义为单个节点的链路上的平均权重分布。我们根据选择性值提取节点（关键字候选）。此外，我们扩展提取的节点，以字元组排名最高的进/出选择性值。基于选择性的抽取不需要语言学知识，而纯粹是从源文本中包含的统计和结构信息中得到的，这些信息反映在网络的结构中。在手动注释的关键字上评估获得的集合：对于提取的关键字候选集合，平均F1分数为24，63%，平均F2分数为21，19%;对于提取的单词元组候选，平均F1分数为25，9%，平均F2分数为24，47%。
英文摘要：
Preliminary report on network based keyword extraction for Croatian is an unsupervised method for keyword extraction from the complex network. We build our approach with a new network measure the node selectivity, motivated by the research of the graph based centrality approaches. The node selectivity is defined as the average weight distribution on the links of the single node. We extract nodes (keyword candidates) based on the selectivity value. Furthermore, we expand extracted nodes to word-tuples ranked with the highest in/out selectivity values. Selectivity based extraction does not require linguistic knowledge while it is purely derived from statistical and structural information en-compassed in the source text which is reflected into the structure of the network. Obtained sets are evaluated on a manually annotated keywords: for the set of extracted keyword candidates average F1 score is 24,63%, and average F2 score is 21,19%; for the exacted words-tuples candidates average F1 score is 25,9% and average F2 score is 24,47%.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
