今日去被大佬问到如何实现一个敏感词的匹配,所以写了一个简版的敏感词匹配结构,还待后期优化!
**注:暂时不可以投放到生产环境使用**
**有喜欢的可以提交代码给我,或者拿走自己维护**
希望各位大佬指点 谢谢~, 关键词为网上找到的所以不是很全,望大家海涵~谢谢!
源码地址:https://github.com/tianye/sensitive_words
源码实现方式:
```
package decision
import (
"fmt"
"strings"
)
type Node struct {
Word string
Node [] *Node
Location int
IsSensitive bool
}
type Tree struct {
TreeNode [] *Node
}
//创建一个叶子节点
func CreateNode(word string, location int, isSensitive bool) *Node {
return &Node{Word: word, Location: location, IsSensitive: isSensitive}
}
//创建一个树
func CreateTree() *Tree {
tree := &Tree{}
return tree
}
//查找一个Node节点
func SearchNode(str string, nodeList [] *Node) *Node {
//查找当前层级的所有node
for _, v := range nodeList {
//存在则直接返回当前node
if v.Word == str {
return v
}
}
return nil
}
//插入一个子节点
func AppendNode(nowNode, newNode *Node) (*Node) {
nowNode.Node = append(nowNode.Node, newNode)
return newNode
}
//Build一个树
func BuildTrue(str string, tree *Tree) *Tree {
end := strings.Count(str, "") - 1
var nowNode = &Node{}
var i = 0
for _, val := range str {
i++
isSensitive := false
if i == end {
isSensitive = true
}
newNode := CreateNode(string(val), i, isSensitive)
if i == 1 {
nowNode = SearchNode(newNode.Word, tree.TreeNode)
if nowNode != nil {
continue
}
tree.TreeNode = append(tree.TreeNode, newNode)
nowNode = newNode
continue
}
if nowNode.Node != nil {
nowNode := SearchNode(newNode.Word, nowNode.Node)
if nowNode != nil {
continue
}
}
nowNode = AppendNode(nowNode, newNode)
}
return tree
}
//匹配的敏感词汇
func MatchingSensitiveWords(tree *Tree, str string) (isSensitive bool, allLocationStr []int) {
node := tree.TreeNode
isSensitive = false
locationStr := make([]int, 0)
allLocationStr = make([]int, 0)
var i = 0
for _, v := range str {
i++
node, isSensitive = SearchLeavesNode(string(v), node)
//没有下一个节点了 并且当前不是敏感词
if node == nil && isSensitive == false {
//节点回到最初
node = tree.TreeNode
//当前子重新匹配
node, isSensitive = SearchLeavesNode(string(v), node)
//记录新的本次匹配地址
locationStr = []int{i}
} else {
//追加记录位置
locationStr = append(locationStr, i)
}
//如果是敏感词则记录到位置中
if isSensitive == true {
node = tree.TreeNode
allLocationStr = append(allLocationStr, locationStr...)
locationStr = []int{}
}
}
//匹配到了关键词
if len(allLocationStr) > 0 {
isSensitive = true
}
return isSensitive, allLocationStr
}
//搜索层级关键字
func SearchLeavesNode(str string, params []*Node) (node []*Node, isSensitive bool) {
for _, node := range params {
if node.Word == str {
return node.Node, node.IsSensitive
}
}
return nil, false
}
//观察树结构
func WatchPrint(params []*Node) {
for _, watch := range params {
fmt.Print("watch.Word:", " ", watch.Word, " ", watch.Location, watch.IsSensitive, "-----", watch, "\n")
if watch.Node != nil {
WatchPrint(watch.Node)
}
}
}
```
使用方法:
#####1.先构建敏感关键词树 (应为树在初始化时候建立完成 后期可以直接使用,减少后期构建过程)
```
var tree = decision.CreateTree()
//初始化 构建 敏感词数
func init() {
strList := [] string{
"考前答案","答案","前答",
}
for _, strItem := range strList {
//构建敏感词树
decision.BuildTrue(strItem, tree)
}
}
```
#####2.匹配敏感关键词
```
//等待匹配的数据
str := "啊前答我是一个文字啦啦啦考前答案答案前答我也是文答案字啦"
//匹配关键词
res, loc := decision.MatchingSensitiveWords(tree, str)
fmt.Println("\n结果:", "是否存在敏感词:", res, "敏感词每个字所在位置:", loc)
```
输出结果:
```
结果: 是否存在敏感词: true 敏感词每个字所在位置: [2 3 13 14 15 16 17 18 19 20 25 26]
```
使用实例: build_decision.go 文件查看,谢谢
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