针对网络日志挖掘中的会话切分问题，提出了一种基于时间间隔的方法。
This paper presents a method for session identification based on an analysis of intervals of user access logs.
首先介绍日志挖掘，然后分析了日志挖掘在电子商务领域的应用，从而指导电子商务网站资源的组织和分配。
Web log mining was introduced, and the application of it to electronic commerce analyzed, to direct organizing and reallocateiori resources of electronic commerce sites.
在模式挖掘方面，集成了目前有效的最大向前路径挖掘算法和频繁遍历路径挖掘算法，并且将孤立点分析方法引入日志挖掘中。
Efficient mining algorithm of maximum forward path and efficient mining algorithm of frequent traversal path are integrated in the mining period; Outlier analysis is introduced into the mining system.
为此，本文对企业安全管理方法和机制进行了研究，提出了一种新型的、分布式的、支持多种协议的企业安全管理框架，即基于日志挖掘的企业安全管理中心。
So the article presents the new architecture of Enterprise Security Management Center based on log mining which is distributed and supports multi-protocol. It is extensible, reusable and migratory.
日志中的信息越多，您所能实现数据挖掘就越强有力。
The more information in the log, the more powerful the data mining you can achieve.
我还将展示如何在收集到日志信息之后挖掘信息。
I will also show you how to mine the log information once it has been gathered.
如果您对流程、数据流或挖掘流启用内容跟踪，那么CONFIG级别和该级别以上的UIMA日志将路由到InfoSphereWarehousing日志。
If you enable content tracing for a process, a data flow, or a mining flow, UIMA logs of level CONFIG and above are routed to the InfoSphere Warehousing log.
那些日志文件可能很大，但是挖掘工作将在您的Hadoop集群中的多个机器(节点)之间分配。
Those log files can be huge, but the work will be split up among the machines (nodes) in your Hadoop cluster.
还可以用于将消息记入日志，以供审核和后续数据挖掘之用。
Can also be used to log messages for audit or for subsequent data mining.
但由于这些日志审计数据量非常庞大，因此采用数据挖掘技术从中进行安全模式规则的提取。
However, as the amount of the log audit date is too large, we can apply data mining technology into security mode rule extraction.
查看InfoSphereWarehouse文档了解如何查看挖掘流或数据流的uima日志，以及如果更改uima跟踪级别获得更多信息。
See the InfoSphere Warehouse documentation for instructions on how to see the UIMA logs of a mining or data flow and how to change the UIMA trace level to get more information.
工作流挖掘的起点是收集和处理工作流日志。
The beginning of workflow mining is to collect and format the workflow log.
本系统是国内第一个针对TRIP系统的文献日志进行挖掘的个性化信息服务系统。
This System is the first personality information system using TRIP system's query log for web mining at home.
近年来，随着网络数据挖掘技术的迅猛发展，如何从搜索引擎查询日志中找到有用的信息成为一个重要的研究方向。
During the recent years, with the rapid development of Web data mining, how to find useful information in search engine log query has become an important research direction.
该文主要对移动日志数据库不断更新的问题，提出了增量挖掘的方法，挖掘用户的移动模式。
An incremental mining technique is proposed in order to solve the problem of frequent updating of moving log database and mine the user mobility patterns.
用户查询日志是大量用户长期查询行为的记录，通过挖掘用户查询与用户日志之间的联系，构建相关词表，从而实现查询扩展。
Query log is a record of query behavior by a great quantity of users, it can Fred the related word list through mining the relation between query and query log, thus to realize the query extension.
工作流挖掘技术是从工作流日志重构流程模型的方法，可以作为识别角色的方法，以尽量减少主观性的影响。
Workflow mining is a technique that reconstructs process model on the basis of workflow log. This method is used to identify roles, so that the role identification can be as objective as possible.
然而，在将数据挖掘的算法运用到服务器日志上之前，必须对日志数据进行一些预处理。
However, there are several preprocessing tasks that must be performed prior to applying data mining algorithms to the data collected from server logs.
流程挖掘的目的就是从日志数据中抽取信息构建商业流程执行时的模型，从而能跟踪改进流程。
Process mining aims at extracting information from logs to build up business processes models as they are being executed, and use them to monitor and improve business processes.
过程挖掘的方法从已经发生的业务日志记录中提炼出工作流模型，能方便地设计工作流管理系统。
Process mining aims at extracting information from event logs to capture the business process as it is being executed, and it is very convenient to design the Workflow management system.
工作流挖掘抽取系统日志信息，挖掘流程的真实运作模型。
By extracting information from workflow traces, such as system log data, workflow mining aims to discover the actual behavior of a workflow process.
基于日志建立转移矩阵，定义基本过程逻辑关系的挖掘规则，并据此规则设计了挖掘算法。
A transition matrix among activities was established based on process logs, and the mining rules of basic process logical relationships were defined.
基于日志建立转移矩阵，定义基本过程逻辑关系的挖掘规则，并据此规则设计了挖掘算法。
A transition matrix among activities was established based on process logs, and the mining rules of basic process logical relationships were defined.
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