合肥工业大学学报(自然科学版)
閤肥工業大學學報(自然科學版)
합비공업대학학보(자연과학판)
Journal of Hefei University of Technology (Natural Science)
2015年
9期
1215-1219
,共5页
抽取%信息抽取%统计特征%词性特征%机器学习
抽取%信息抽取%統計特徵%詞性特徵%機器學習
추취%신식추취%통계특정%사성특정%궤기학습
keyphrase extraction%information extraction%statistical feature%part-of-speech(POS) fea-ture%machine learning
互联网技术的快速发展导致信息爆炸式的增长。因此,在海量信息中查找关键信息变得非常困难,关键信息的提取技术就变得愈加重要,该关键信息通常表现为关键词。针对该问题,文章设计了一种无监督的关键词抽取算法,无需训练文档,根据候选词的统计特征和词性特征等直接从单个文档中提取关键词。实验表明,算法所提取的关键词优于现有算法所获取的关键词,同时,该算法的时间效率也优于现有的算法。
互聯網技術的快速髮展導緻信息爆炸式的增長。因此,在海量信息中查找關鍵信息變得非常睏難,關鍵信息的提取技術就變得愈加重要,該關鍵信息通常錶現為關鍵詞。針對該問題,文章設計瞭一種無鑑督的關鍵詞抽取算法,無需訓練文檔,根據候選詞的統計特徵和詞性特徵等直接從單箇文檔中提取關鍵詞。實驗錶明,算法所提取的關鍵詞優于現有算法所穫取的關鍵詞,同時,該算法的時間效率也優于現有的算法。
호련망기술적쾌속발전도치신식폭작식적증장。인차,재해량신식중사조관건신식변득비상곤난,관건신식적제취기술취변득유가중요,해관건신식통상표현위관건사。침대해문제,문장설계료일충무감독적관건사추취산법,무수훈련문당,근거후선사적통계특정화사성특정등직접종단개문당중제취관건사。실험표명,산법소제취적관건사우우현유산법소획취적관건사,동시,해산법적시간효솔야우우현유적산법。
T he rapid development of the Internet technology has led to the explosive grow th of informa‐tion ,and it becomes difficult for people to seek for the key information from a mass of information . Therefore ,the technology of extracting key information becomes increasingly important .The critical information is usually expressed as keyphrases .In this paper ,an unsupervised keyphrase extraction algorithm is presented .Without training documents ,keyphrases are extracted from a single document according to the statistical characteristics and part‐of‐speech(POS) feature of candidate phrases .The experimental results show that the proposed algorithm can improve the quality of extraction and time efficiency .