1) longest sequential frequent phrases
最长顺序频繁词组
1.
Based on the idea, an algorithm of mining the longest sequential frequent phrases for extracting features of the bibliographies is designed, and an extended feature hierarchical tree describing the relation.
基于该思想,设计了通过挖掘最长顺序频繁词组抽取文献特征的算法,提出了能够表现特征之间、文献之间、特征与文献之间关系的扩展的特征层次树结构及其构建方法。
3) 2 degree frequent word sequence
2度频繁词序列
1.
This paper assign the document to a appropriate cluster by using the verification of 2 degree frequent word sequence of the cluster label in the text,meet the disadvantage of the CFWS,improve the clustering precision.
本文通过在文本中对簇标签进行2度频繁词序列的验证将文本指定到合适的簇,弥补了基于频繁词序列文本聚类算法的不足,提高了聚类的精确度。
4) maximal frequent sequence
最大频繁序列
1.
Aimed at the massive invalid sequences caused by the complete frequent patterns,which is not con- sidered in the existing classification algorithm,a protein sequence classification algorithm is proposed based on the maximal frequent sequence.
针对现有基于频繁模式的分类算法未考虑完全频繁模式所产生的大量无效序列,提出了一种基于最大频繁序列的蛋白质分类算法,此算法每一类都以独有的最大频繁模式作为代表,执行模式裁减和测试数据分类。
2.
Mining maximal frequent sequences is an important topic in the data mining research.
最大频繁序列挖掘是数据挖掘的重要内容之一。
3.
Discovering the maximal frequent sequence is an important branch in data mining.
最大频繁序列发现是数据挖掘中的一个重要分支。
5) longest frequent closed itemset
最长频繁闭项集
6) frequent term set
频繁词集
1.
Massive short documents classification method based on frequent term set clustering;
基于频繁词集聚类的海量短文分类方法
2.
huge volume of documents,high dimensional process and understandability of the clustering results,we propose a simple hybrid algorithm called topHDC based on top-k frequent term sets and k-means.
针对上述挑战,本文提出了一个基于top-k频繁词集和k-means的混合聚类算法topHDC。
补充资料：固定词组
1.两个以上的词的紧密结合。其句法功能相当于一个词。常见的有专名和成语。如"中华人民共和国"﹑"欣欣向荣"﹑"守株待兔"等。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条