224 lines
6.6 KiB
TeX
224 lines
6.6 KiB
TeX
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% !TeX root = ../main.tex
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\lstdefinestyle{lfonts}{
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basicstyle = \scriptsize\ttfamily,
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stringstyle = \color{purple},
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keywordstyle = \color{blue!60!black}\bfseries,
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commentstyle = \color{olive}\scshape,
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}
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\lstdefinestyle{lnumbers}{
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numbers = left,
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numberstyle = \tiny,
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numbersep = 1em,
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firstnumber = 1,
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stepnumber = 1,
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}
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\lstdefinestyle{llayout}{
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breaklines = true,
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tabsize = 2,
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% columns = spacefixed,
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}
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\lstdefinestyle{lgeometry}{
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xleftmargin = 20pt,
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xrightmargin = 0pt,
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frame = tb,
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framesep = \fboxsep,
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framexleftmargin = 20pt,
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}
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\lstdefinestyle{lgeneral}{
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style = lfonts,
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style = lnumbers,
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style = llayout,
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style = lgeometry,
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}
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\lstdefinelanguage{JavaScript}{
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keywords={typeof, new, true, false, catch, function, return, null, catch, switch, var, if, in, while, do, else, case, break, import, const, from},
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keywordstyle=\color{blue}\bfseries,
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ndkeywords={class, export, boolean, throw, implements, import, this},
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ndkeywordstyle=\color{darkgray}\bfseries,
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identifierstyle=\color{black},
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sensitive=false,
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comment=[l]{//},
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morecomment=[s]{/*}{*/},
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commentstyle=\color{purple}\ttfamily,
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stringstyle=\color{red}\ttfamily,
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morestring=[b]',
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morestring=[b]"
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}
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\chapter{成语接龙算法流程}
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\section{成语词库}
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我们站在巨人的肩膀上,前人已经收集了足够的成语词库。成语词库来源于 \href{https://github.com/pwxcoo/chinese-xinhua}{chinese-xinhua},此项目以 MIT 协议开源。
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以下是其中一个成语的数据结构:
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\lstset{language = JavaScript, style = lgeneral}
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\begin{lstlisting}
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{
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"derivation": "语出《法华经·法师功德品》下至阿鼻地狱。”",
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"example": "但也有少数意志薄弱的……逐步上当,终至堕入~。★《上饶集中营·炼狱杂记》",
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"explanation": "阿鼻梵语的译音,意译为无间”,即痛苦无有间断之意。常用来比喻黑暗的社会和严酷的牢狱。又比喻无法摆脱的极其痛苦的境地。",
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"pinyin": "ā bí dì yù",
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"word": "阿鼻地狱",
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"abbreviation": "abdy",
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"id": 0
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},
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\end{lstlisting}
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经统计,共收录了 30895 个成语,但其中还包括了非四字成语。我们使用如下 JavaScript 代码剔除:
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\lstset{language = JavaScript, style = lgeneral}
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\begin{lstlisting}
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import fs from 'node:fs'
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import path from 'node:path'
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import idioms from './idiom.json' assert { type: 'json' }
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const new_idioms = idioms.filter(value => value.word.length === 4)
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console.log(new_idioms.length)
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const idioms_json = JSON.stringify(new_idioms)
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fs.writeFile('./four_letter_idioms.json', idioms_json, (err) => {
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if (err)
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throw err
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})
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\end{lstlisting}
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\section{后端}
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\subsection{索引}
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为便于查询成语,首先为每个成语以其首拼音和末拼音索引。
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再采用递推法,以成语“一个顶俩”的“yi”为初始值,遍历末拼音为“yi”的成语,以第一次循环为“第一层”,为每个成语添加层级属性。
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以下为核心代码:
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\lstset{language = Go, style = lgeneral}
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\begin{lstlisting}
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func initIdiomsDB() {
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lastPinyins := mapset.NewSet[string]()
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lastPinyins.Add("yi") // 初始化,以“yi”为起点递推
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level := 1
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for lastPinyins.Cardinality() > 0 { // 直到无需要遍历的拼音结束循环
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firstPinyins := mapset.NewSet[string]()
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for pinyin := range lastPinyins.Iter() {
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err := func() error {
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txn := IdiomsDB.Txn(true)
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defer txn.Abort()
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result, err := txn.Get("lastPinyin", "pinyin", pinyin)
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if err != nil {
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return err
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}
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for item := result.Next(); item != nil; item = result.Next() {
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lastPinyin := item.(*models.LastPinyin)
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if lastPinyin != nil && level > 0 {
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if lastPinyin.Idiom.Level == 0 {
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lastPinyin.Idiom.Level = level
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err := txn.Insert("idioms", lastPinyin.Idiom)
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if err != nil {
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return err
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}
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firstPinyins.Add(utils.GetFirstPinyin(lastPinyin.Idiom.Pinyin))
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}
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}
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}
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txn.Commit()
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return nil
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}()
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if err != nil {
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log.Fatal(err)
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}
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}
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lastPinyins = firstPinyins // 以在下一次循环查询成语
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level++
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}
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}
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\end{lstlisting}
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本算法实际上是递推思想的应用。算法前期对成语索引,为每个成语添加Level属性,以便于之后的正向查询成语接龙。
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以下为流程图:
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\begin{figure}[H]
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\centering
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\includegraphics[width=12cm]{index.pdf}
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\caption{}
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\label{fig:index}
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\end{figure}
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\subsection{遍历查询}
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得到这些成语后再分别遍历以每个成语首拼音为末拼音的成语。
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以下为核心代码:
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\lstset{language = Go, style = lgeneral}
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\begin{lstlisting}
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func Solitaire(c echo.Context) error {
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var r *solitaireRequest
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err := c.Bind(&r)
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if err != nil {
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return c.String(http.StatusBadRequest, "")
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}
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idiom, err := db.GetIdiom(r.Word)
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if err != nil {
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return c.String(http.StatusBadRequest, "")
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}
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idioms := linkedhashset.New()
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for idiom != nil {
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idioms.Add(idiom)
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level := idiom.Level
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if level > 1 {
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pinyinIdioms, err := db.GetFirstPinyinIdioms(utils.GetLastPinyin(idiom.Pinyin))
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if err != nil {
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return err
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}
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filtered := utils.Filter(pinyinIdioms, func(i *models.Idiom) bool {
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return i.Level < idiom.Level
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}) // 检出比当前成语低Level的成语
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idiom = utils.RandomItem(filtered) // 成语可能不止一个,随机取一个
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} else if utils.GetLastPinyin(idiom.Pinyin) == "yi" {
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idioms.Add(&models.Idiom{ // 遍历结束,加一个顶俩
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Data: models.Data{
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Id: 29502,
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Derivation: "无",
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Example: "董同学在项目中起到了~的效果。",
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Explanation: "形容一个人做事有效果,一个人能代替两个人。",
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Pinyin: "yī gè dǐng liǎ",
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Word: "一个顶俩",
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Abbreviation: "无",
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},
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})
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break
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} else {
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return c.String(http.StatusNoContent, "") // 找不到成语
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}
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}
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return c.JSON(http.StatusOK, idioms) // 成功,输出
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}
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\end{lstlisting}
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经过测试,循环遍历5次后需要遍历的成语列表为空,即最多4个成语就能到达“一个顶俩”这一成语。
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每个成语的Level属性接龙到成语“一个顶俩”的“距离”。
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在得到目标成语后,只需查询首拼音与该成语末拼音相同的成语中比该成语层级属性更低的成语,就能保证查询的方向是在步步逼近成语“一个顶俩”。
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