聊天机器人--文档

MSN的类库DotMSN介绍（英文原文）

DotMSN

DotMSN is an open-source stand-alone class library to provide connectivity with the MSN Messenger service. The library is built in C# and can therefore be used by all languages the .NET environment supports. Because of a clean natural Object-Oriented approach the library is easy to use and implement. DotMSN is designed to be a flexible, robust and lightweight enhancement to any application. Applications of DotMSN vary from creating messaging robots to creating custom clients. If your application needs to communicate through the messenger service, DotMSN is your tool.

Features

The library currently supports the following features:

Connecting / disconnecting with the MSN Messenger service
Setting presence status
Event-based design to notify contact presence status changes
Personal data of a contact
Owner profile details
Automatically synchronizes contact lists and keeps contactlist data up to date
Creating and changing contactgroups
Convenient enumerating through contacts in different lists
Request or receive conversations
Multiple users in one conversation
Sending and receiving decorated text messages
Sending typing messages
Privacy settings of the contactlist owner
Hotmail mailbox status
Notifications of new mail
Flexible tracing of warnings and errors
File transfers
User display images
Proxy support and custom servers
P2P framework support
Custom extendable DotMSN framework
MSNP9 protocol
Source code provided

DotMSN is a stand-alone library. This means there is no interaction with the official MSN Messenger client and therefore it does not need to be installed when using DotMSN. Multiple instances of DotMSN can be executed on the same machine, or even in the same process. Thus making it easy to deploy applications on a single server.

How does DotMSN integrate with your application? The following diagram makes clear how DotMSN interacts with your application as well as remote parties.

Get DotMSN

You can download DotMSN at the download page.

MSN Messenger新增两聊天机器人!

微软上周发布了两个新的聊天机器人，采取了与众不同的方向推荐给用户。而微软的竞争对手AOL，在本月为用户密友列表自动添加了两个AIM的聊天机器人后，却引起了用户的连连抱怨。

　　微软这两个聊天机器人是参考微软的Encarta百科全书和BBC的电视列表来回答问题的。用户可以用这项自动化的服务通过说“hello”并且按照提示进行会话。那些有兴趣的用户可以把encarta@conversagent.com和 bbcbackstage@hotmail.com添加到他们的联系人列表中，这样就可以测试这两个聊天机器人了。

　　BBC的电视列表机器人好像对国内用户用处不大，笔者添加了encarta@conversagent.com，问它：who is michael jordan?它居然回答：目前对这个问题的答案不可用，请给它点时间。不过如果问它某个地方的话，它会在聊天窗口右边用地图显示出这个地方来，以下是笔者问它广州在哪里的答案：

500)this.style.width=500;">

来源：huazi817的BLOG http://blog.sina.com.cn/u/45788636010000v2

dotnet+xml开发简单聊天机器人

做一个智能的聊天机器人并不容易，我这里只是实现了一个很简易的聊天机器人。

当你和这个机器人聊天的时候，每次机器人会根据你说的话的关键词找到回答的语句。如果找不到就随机的说一句默认语言。数据存储格式是xml。

以下是xml的原文件：

<?xml version="1.0" encoding="UTF-8"?>
<chat>

<default>
<content>你在哪里？</content>
<content>你还是学生吗？</content>

.........

</default>

    <content key="怪"> 不怪</content>
    <content key="慢">是啊，慢</content>
    <content key="喂">什么事？</content>
    <content key="88">再见</content>
    <content key="谢">没什么好谢的</content>
    <content key="滚">我不会滚，我会走</content>

......

////////////////////////////////////////////////////////////////////

以下是主要的源代码：

Imports System.Xml
Public Class Form1
Inherits System.Windows.Forms.Form

#Region " Windows 窗体设计器生成的代码 "

Public Sub New()
MyBase.New()

'该调用是 Windows 窗体设计器所必需的。
InitializeComponent()

'在 InitializeComponent() 调用之后添加任何初始化

End Sub

    '窗体重写 dispose 以清理组件列表。
    Protected Overloads Overrides Sub Dispose(ByVal disposing As Boolean)
        If disposing Then
            If Not (components Is Nothing) Then
                components.Dispose()
            End If
        End If
        MyBase.Dispose(disposing)
    End Sub

'Windows 窗体设计器所必需的
Private components As System.ComponentModel.IContainer

    '注意: 以下过程是 Windows 窗体设计器所必需的
    '可以使用 Windows 窗体设计器修改此过程。
    '不要使用代码编辑器修改它。
    Friend WithEvents RichTextBox1 As System.Windows.Forms.RichTextBox
    Friend WithEvents TextBox1 As System.Windows.Forms.TextBox
    Friend WithEvents Button1 As System.Windows.Forms.Button
    <System.Diagnostics.DebuggerStepThrough()> Private Sub InitializeComponent()
        Dim resources As System.Resources.ResourceManager = New System.Resources.ResourceManager(GetType(Form1))
        Me.RichTextBox1 = New System.Windows.Forms.RichTextBox
        Me.TextBox1 = New System.Windows.Forms.TextBox
        Me.Button1 = New System.Windows.Forms.Button
        Me.SuspendLayout()
        '
        'RichTextBox1
        '
        Me.RichTextBox1.Location = New System.Drawing.Point(0, 0)
        Me.RichTextBox1.Name = "RichTextBox1"
        Me.RichTextBox1.ReadOnly = True
        Me.RichTextBox1.Size = New System.Drawing.Size(560, 304)
        Me.RichTextBox1.TabIndex = 2
        Me.RichTextBox1.Text = ""
        '
        'TextBox1
        '
        Me.TextBox1.Location = New System.Drawing.Point(0, 312)
        Me.TextBox1.Name = "TextBox1"
        Me.TextBox1.Size = New System.Drawing.Size(456, 21)
        Me.TextBox1.TabIndex = 0
        Me.TextBox1.Text = ""
        '
        'Button1
        '
        Me.Button1.Location = New System.Drawing.Point(472, 312)
        Me.Button1.Name = "Button1"
        Me.Button1.Size = New System.Drawing.Size(72, 24)
        Me.Button1.TabIndex = 1
        Me.Button1.Text = "Enter"
        '
        'Form1
        '
        Me.AutoScaleBaseSize = New System.Drawing.Size(6, 14)
        Me.ClientSize = New System.Drawing.Size(560, 341)
        Me.Controls.Add(Me.Button1)
        Me.Controls.Add(Me.TextBox1)
        Me.Controls.Add(Me.RichTextBox1)
        Me.FormBorderStyle = System.Windows.Forms.FormBorderStyle.FixedSingle
        Me.Icon = CType(resources.GetObject("$this.Icon"), System.Drawing.Icon)
        Me.MaximizeBox = False
        Me.Name = "Form1"
        Me.StartPosition = System.Windows.Forms.FormStartPosition.CenterScreen
        Me.Text = "青蛙王子"
        Me.ResumeLayout(False)

End Sub

#End Region

    Private Sub Form1_Load(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles MyBase.Load
        readxml()
    End Sub

    Dim xmlFile As String = "./robot.xml"
    Dim chatList As New ArrayList
    Dim answerList As New Hashtable
    Dim random As New System.Random

    Private Sub readxml()
        Try
            Dim doc As XmlDocument = New XmlDocument
            doc.Load(xmlFile)
            Dim nodeList As XmlNodeList
            Dim root As XmlElement = doc.DocumentElement
            '--默认的聊天语句--
            nodeList = root.SelectNodes("/chat/default/content")
            Dim node As XmlNode
            For Each node In nodeList
                chatList.Add(node.InnerText)
            Next
            '回答指定关键词的语句序列--
            nodeList = root.SelectNodes("/chat/answer/content")
            For Each node In nodeList
                answerList.Add(node.Attributes("key").Value, node.InnerText)
            Next
        Catch ex As Exception
            MsgBox(ex.Message)
        End Try
    End Sub

    Private Sub Button1_Click(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles Button1.Click
        'RichTextBox1.SelectionBullet = True
        Dim Content$ = TextBox1.Text.Trim
        If (Content = "") Then
            RichTextBox1.AppendText("请不要欺骗我的感情,谢谢!" + ControlChars.Lf)
            Exit Sub
        End If
        If (Content.IndexOf(":") <> -1) Then
            If learnNewWord(Content) Then
                RichTextBox1.AppendText("我又学会了新的东西,谢谢!" + ControlChars.Lf)
            End If
            Exit Sub
        End If
        RichTextBox1.AppendText(Content + ControlChars.Lf)
        Dim aStr$ = getSimilarContent(Content)
        If (aStr = Nothing) Then
            Dim i% = random.Next(1, chatList.Count)
            aStr = chatList.Item(i)
        End If
        RichTextBox1.AppendText(aStr.Trim + ControlChars.Lf)
        RichTextBox1.Refresh()
    End Sub
    '得到相似的字符串
    Function getSimilarContent(ByVal content As String) As String
        Dim keys As System.Collections.ICollection = answerList.Keys
        Dim enumR As System.Collections.IEnumerator = keys.GetEnumerator
        While (enumR.MoveNext)
            Dim str$ = enumR.Current
            If content.Equals(str) Then
                Return answerList(str)
            End If
        End While
        enumR.Reset()
        While (enumR.MoveNext)
            Dim str$ = enumR.Current
            If (content.IndexOf(str) <> -1) Or (str.IndexOf(content) <> -1) Then
                Return answerList(str)
            End If
        End While
        Return Nothing
    End Function

    '添加新的语句
    Function learnNewWord(ByVal content As String) As Boolean
        Try
            Dim doc As XmlDocument = New XmlDocument
            Dim i% = content.IndexOf(":")
            Dim str1$ = content.Substring(0, i)
            Dim str2$ = content.Substring(i + 1)
            doc.Load(xmlFile)
            Dim elem As XmlElement = doc.CreateElement("content")
            Dim attr As XmlAttribute = doc.CreateAttribute("key")
            attr.Value = str1
            elem.InnerText = str2
            elem.Attributes.Append(attr)
            '添加新的语句--
            Dim root As XmlElement = doc.DocumentElement
            Dim xmlNode As XmlNode = root.SelectSingleNode("/chat/answer")
            xmlNode.AppendChild(elem)
            answerList.Add(str1, str2)
            doc.Save(xmlFile)
            Return True
        Catch ex As Exception
            MsgBox(ex.Message)
            Return False
        End Try
    End Function

    Private Sub TextBox1_KeyPress(ByVal sender As Object, ByVal e As System.Windows.Forms.KeyPressEventArgs) Handles TextBox1.KeyPress
        If e.KeyChar.Equals(ControlChars.Cr) Then
            Button1_Click(Nothing, Nothing)
        End If
    End Sub
End Class

来自：Cral的BLOG http://blog.sina.com.cn/u/55fd94d3010000s1

几个免费的中文分词模块

几个月前做毕业论文的时候需要用到中文分词技术，现在总结一下我所找到的资料。一、什么是中文分词众所周知，英文是以词为单位的，词和词之间是靠空格隔开，而中文是以字为单位，句子中所有的字连起来才能描述一个意思。例如，英文句子“I am a student”，用中文则为：“我是一个学生”。计算机可以很简单通过空格知道“student”是一个单词，但是不能很容易明白「学」、「生」两个字合起来才表示一个词。把中文的汉字序列切分成有意义的词，就是中文分词，有些人也称为切词。“我是一个学生”，分词的结果是：“我是一个学生”。中文分词是其他中文信息处理的基础，搜索引擎只是中文分词的一个应用。其他的比如机器翻译（MT）、语音合成、自动分类、自动摘要、自动校对等等，都需要用到分词。目前研究中文分词的大多是科研院校，清华、北大、中科院、北京语言学院、东北大学、IBM研究院、微软中国研究院等都有自己的研究队伍，而真正专业研究中文分词的商业公司除了海量科技以外，几乎没有了。 Google的中文分词技术采用的是美国一家名叫 Basis Technology（http://www.basistech.com）的公司提供的中文分词技术，百度使用的是自己公司开发的分词技术，中搜使用的是国内海量科技（http://www.hylanda.com）提供的分词技术。业界评论海量科技的分词技术目前被认为是国内最好的中文分词技术，其分词准确度超过99%，由此也使得中搜在搜索结果中搜索结果的错误率很低。（以上内容摘录自附录1）