提前给你的邮件分类并打上条码，你就可以享受大幅邮递折扣。
Pre-sort and barcode your mail to qualify for substantial discounts on postage.
提出了一个基于概念向量空间模型的电子邮件分类方法。
A new approach of email classification based on the concept vector space model was proposed.
支持多种自定义提醒方式，支持多帐号，以及邮件分类和过滤。
It supports custom notifications, multiple email accounts, sorting and filtering, and much more.
实验证明，该模型在简单、高效的同时降低了对垃圾邮件分类的错误率。
This method is simple and efficient and decreases the classification error ratio.
在垃圾邮件分类和朴素贝叶斯算法研究的基础上，提出了基于用户知识的贝叶斯分类算法。
An user knowledge based na? Ve bayes classifier was proposed in order to conquer the problem that most of the E-mail is unstructured and need users decoding.
本文提出了一种基于贝叶斯方法的电子邮件分类器，讨论了其基本思想，给出了实现的系统结构。
This paper proposes a Bayesian method based E-mail classifier, discusses the idea and gives the system structure.
BP算法具有智能性和自学习性的特点，因此，本文提出采用BP神经网络来构造邮件分类识别器。
BP algorithm has aptitude and auto-learning characters, so my paper choose BP neural net algorithm to set up mail classification and recognition model.
该文对现有电子邮件系统中存在的安全性、垃圾邮件、邮件分类、信箱命名资源等问题进行了分析。
In current E-mail system, there are some problem which must be solved, such as the safety of E-mail, junk E-mail, classification of E-mail, name resource and so on.
该文对现有电子邮件系统中存在的安全性、垃圾邮件、邮件分类、信箱命名资源等问题进行了分析。
The authors analyze the essence of some existing algorithms of junk E-mail filtering rules and give the way to represent an E-mail as a transaction.
针对这一现状，本文研究了电子邮件分类管理的模型与技术，以提高企业对电子邮件信息管理的能力。
Under this situation, this paper undertakes the study of email management model and technology in order to improve the email message analysis ability of the enterprises.
将粗糙集与决策树结合，提出一个基于RS - DT的邮件分类方案与模型，并进行了实验及结果分析。
Combining rough sets with decision tree, a spam filtering solution based on rough sets and decision tree (RS-DT) was proposed.
最后使用真实邮件训练集进行了邮件分类的实验，实验结果证明对互信息算法的改进能有效提高邮件分类性能。
At last, simulation test with real E-mail set, was conducted, which shows that the improved mutual information algorithm provides a better result for spam classification.
根据邮件特征出现在垃圾邮件和非垃圾邮件中概率不同，提出了特征对邮件分类贡献度的概念，并给出了其计算公式。
We advance a concept of degree-of-contribution(DC) witch measure a feature's contributions to Spam Filtering, based on the probability of it appears in Spam and Ham.
本文借鉴邮件过滤算法，通过对中文邮件语料的研究，提出了建设一个基于平凡算法和规则相结合的、具有自适应能力的、实用的邮件分类系统。
So this thesis brings forward to construct a self-adaptive and practical mail classification system based on the integration of normal algorithm with regulations after studying Chinese mail corpus.
一种解决的方法是利用CommunicationsCenter在同一个公共消息留言板进行集中交流、保存联系人列表和进行电子邮件分类。
One solution is to have the Communications Center to centralize communication, maintain contacts lists, and categorize your e-mails on the same common message board.
它是从例如评估贷款申请的信用风险，阅读手写的邮政编码来分类邮件等开始的。
It started with things like assessing credit risk from loan applications, sorting the mail by reading handwritten zip codes.
可以在用户的邮件数据库中创建新的视图或文件夹(只能创建不加分类的)，并将它们添加到当前视图左边的大纲中。
You can create new views or folders (non-categorized only) in the user's mail database and add them to the outline that appears to the left of the current view.
减少流入文件的数量，利用垃圾桶来分类邮件，仅仅保留那些需要处理或归档的文件。
Reduce the volume of paper coming in by sorting mail over the recycling bin or trash, keeping only those papers that require an action or filing.
假设你对以下事情很在行，比如说，你可以把你所有的邮件存档到100个文件夹中并恰当分类，然后编辑到电子表格里，这确实很棒。
That is, if you're really efficient at creating a 100 folders and rules for all your email and having them all sorted properly and compiled into a nice spreadsheet, that's great.
分类最常见的用途之一是，识别垃圾邮件与有用邮件。
One of the most common USES of classification is to identify spam or unwanted email versus wanted email.
卡片分类，现场研究，参与式设计，纸上原型和用户体验研究，合意性(desirability)研究，客户邮件。
Cardsorting, field studies, participatory design, paper prototype and usability studies, desirability studies, customer emails.
(我将可能的垃圾邮件进行分类，放在几个不同的文件夹中，然后保存它们以形成消息语言资料库(corpora)。)
(I sort probable spam into several different folders, and I save them all to develop message corpora.)
此过程的第一步将会为减少垃圾邮件为目的而对电子邮件按来自给定组织而进行分类（基于一组指纹）。
The first step in this process was to classify email messages for the purpose of reducing them (based on a set of fingerprints) as coming from a given organization.
它具有和许多电子邮件程序相同的外观，允许根据日期、标题或主题分类和过滤内容。
It has the same look and feel as many E-mail programs, and allows you to sort and filter content based on the date, title, or subject.
监管学习的常见例子包括将电子邮件消息分类为垃圾邮件，根据类别标记网页，以及识别手写输入。
Common examples of supervised learning include classifying E-mail messages as spam, labeling Web pages according to their genre, and recognizing handwriting.
你是不是可以给你的邮件分分类，完成那些被你推迟了的道谢信，读一读你一直打算读的书，回顾整理下你的待完成清单。
How about sorting through your snail mail or email, writing those thank you notes you've been putting off, reading the book you keep meaning to read, reviewing/editing your to-do lists, etc.
能够完成像“电子-证据开示(对用作证据的电子邮件和其它数据记录材料进行分类整理)”之类任务的软件，为律师行节约了成本。
Software that can perform tasks like "e-discovery", sorting through e-mails and other digital records for evidence, is saving firms money.
能够完成像“电子-证据开示(对用作证据的电子邮件和其它数据记录材料进行分类整理)”之类任务的软件，为律师行节约了成本。
Software that can perform tasks like "e-discovery", sorting through e-mails and other digital records for evidence, is saving firms money.
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