网页挖掘中的一个主要问题是对网页进行相关性挖掘。
One of the key problems of web mining is web relevant mining.
该文对这类问题进行了详细的讨论，提出了一种基于统计方法的正负时态相关性挖掘算法。
In this paper we discuss this problem in detail and put forward a method of mining positive and negative temporal correlation based on statistics.
就这种意义上来说，文本挖掘从内容收集信息的能力几乎是不可思议的，但是最好关注一下相关性评分。
In this sense, textual mining almost seems magical with respect to what can be gleaned from the content, but it's best to keep an eye on the relevance scoring.
加权关联规则挖掘是告警相关性分析的重要手段。
The mining of weighted association rules is a primary method used in alarm correlation analysis.
数据挖掘为告警相关性分析中知识获取提供了新的途径。
Data mining provides a new approach of the knowledge updating during the alarm correlation analyzing.
关联规则挖掘算法是通信网告警相关性分析中的重要方法。
Mining association rules is one of the primary methods used in telecommunication alarm correlation analysis.
第六章阐述了双向关联规则挖掘及其算法，并进行了相关性分析。
Chapter 6 proposes bidirectional association rules mining and its algorithm, and analyses the relativity of bidirectional association rules.
空间数据挖掘中所依赖的空间相关性是由空间关联规则描述的。
The spatial dependence in data mining is normally represented by spatial association rules, which provide the critical information in assessing spatial correlations in large spatial databases.
关联规则能发现数据中的属性字段之间的相关性，利用数据挖掘中的统计技术我们可以从纷繁杂乱的海量数据中得出条理清晰的统计数据报表。
Association rules can find some correlation info between these fields. By use of statistic techniques of data mining we can draw exact and plain statistics reporting from the chaotic and massive data.
采用层次化比特预测进一步挖掘比特平面的视角相关性。
Hierarchical bit-plane prediction is then employed to explore interview correlation further.
ZBP不仅充分利用了零树符号之间的相关性，而且从位数据的层面上挖掘出了小波系数值之间的相关性，从而提高了算术编码的性能。
ZBP exploits the correlation among the Zerotree symbols and the bit data of wavelet coefficients, so the efficiency of arithmetic coding is improved.
关联规则挖掘算法是通信网告警相关性分析中的重要方法。
Research of alarm correlation method based on dependency search tree in electric power communication network;
其方法被广泛应用于许多其它数据挖掘任务中，如相关性分析，周期分析，最大模式，闭合模式，查询，分类，索引等等。
It is widely applied in other data mining research such as association analysis, period's analysis, maximal and closed patterns, query, classification and index technology etc.
关联规则挖掘是数据挖掘的主要研究内容，它从大量的数据项中寻找隐藏着的联系或相关性。
As the main research content of data mining, association rule mining is to find the hidden links or relevance from a large number of data items.
通过挖掘每个节点的兴趣，将节点按照它们所表现出的相关性组成网络，使得相关性高的节点在网络中比较近。
By digging out the peer interests, and forming a network according to the relevancy that they display, peer interests that have high relevancy will be close in the network.
理论分析和模拟实验表明，新模型对事件源估计更精确，因而能更好地挖掘出网络中存在的空间相关性。
This model USES the weighs to estimate the information of the event source. Theoretically and experimentally, we show the proposed model is more accurate.
理论分析和模拟实验表明，新模型对事件源估计更精确，因而能更好地挖掘出网络中存在的空间相关性。
This model USES the weighs to estimate the information of the event source. Theoretically and experimentally, we show the proposed model is more accurate.
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