智能推荐与内容营销系统¶

// 智能推荐算法框架
class TechInsightRecommendationEngine {
  constructor() {
    this.userProfiles = new Map();
    this.contentVectors = new Map();
    this.trendingTopics = [];
  }

  // 基于用户行为分析推荐内容
  generateRecommendations(userId, maxResults = 10) {
    const userProfile = this.getUserProfile(userId);
    const recommendations = [];

    // 1. 基于技能等级推荐
    const skillBasedContent = this.getSkillBasedContent(userProfile.skillLevel);

    // 2. 基于阅读历史推荐
    const historyBasedContent = this.getHistoryBasedContent(userProfile.readingHistory);

    // 3. 基于当前热门趋势推荐
    const trendBasedContent = this.getTrendBasedContent();

    // 4. 基于学习路径推荐
    const pathBasedContent = this.getPathBasedContent(userProfile.learningPath);

    return this.mergeAndRankRecommendations([
      ...skillBasedContent,
      ...historyBasedContent,
      ...trendBasedContent,
      ...pathBasedContent
    ], maxResults);
  }

  // 实时更新用户画像
  updateUserProfile(userId, interaction) {
    const profile = this.getUserProfile(userId);

    // 更新技能标签
    if (interaction.type === 'read') {
      profile.skillTags = this.updateSkillTags(profile.skillTags, interaction.content.tags);
    }

    // 更新学习偏好
    if (interaction.type === 'like' || interaction.type === 'share') {
      profile.preferences = this.updatePreferences(profile.preferences, interaction.content);
    }

    // 更新学习进度
    if (interaction.type === 'complete') {
      profile.learningProgress = this.updateLearningProgress(profile.learningProgress, interaction.content);
    }

    this.userProfiles.set(userId, profile);
  }
}

// 自动内容标签和分类系统
class ContentTaggingSystem {
  constructor() {
    this.techKeywords = new Map([
      ['spring', { category: 'framework', difficulty: 'intermediate', trending: 0.8 }],
      ['kubernetes', { category: 'platform', difficulty: 'advanced', trending: 0.9 }],
      ['ai', { category: 'emerging', difficulty: 'intermediate', trending: 0.95 }],
      ['microservices', { category: 'architecture', difficulty: 'advanced', trending: 0.85 }]
    ]);
  }

  // 自动分析内容并生成标签
  analyzeContent(content) {
    const analysis = {
      primaryTags: [],
      secondaryTags: [],
      difficulty: 'beginner',
      estimatedReadTime: 0,
      prerequisites: [],
      relatedTopics: []
    };

    // AI驱动的内容分析
    analysis.primaryTags = this.extractPrimaryTags(content);
    analysis.difficulty = this.assessDifficulty(content);
    analysis.estimatedReadTime = this.calculateReadTime(content);
    analysis.prerequisites = this.identifyPrerequisites(content);

    return analysis;
  }
}

// 实时技术热度监控
class TechTrendTracker {
  constructor() {
    this.trendData = new Map();
    this.socialMediaAPI = new SocialMediaAPI();
    this.githubAPI = new GitHubAPI();
    this.stackOverflowAPI = new StackOverflowAPI();
  }

  // 实时追踪技术热度
  async trackTechTrends() {
    const trends = await Promise.all([
      this.getGitHubTrends(),
      this.getStackOverflowTrends(),
      this.getSocialMediaTrends(),
      this.getJobMarketTrends()
    ]);

    return this.mergeTrendData(trends);
  }

  // 预测技术发展趋势
  predictTechEvolution(techName, timeframe = '6months') {
    const historicalData = this.getTrendHistory(techName);
    const currentMetrics = this.getCurrentMetrics(techName);

    return {
      confidence: this.calculateConfidence(historicalData),
      prediction: this.generatePrediction(historicalData, currentMetrics, timeframe),
      factors: this.identifyKeyFactors(techName),
      recommendations: this.generateRecommendations(techName)
    };
  }
}

// 区分真实趋势和炒作泡沫
class AntiHypeAnalyzer {
  constructor() {
    this.hypeIndicators = [
      'excessive_media_coverage',
      'lack_of_real_world_adoption',
      'vendor_driven_promotion',
      'unrealistic_promises'
    ];
  }

  // 分析技术是否存在过度炒作
  analyzeHypeLevel(techName) {
    const metrics = {
      mediaAttention: this.getMediaAttentionScore(techName),
      realWorldAdoption: this.getRealWorldAdoptionScore(techName),
      technicalMaturity: this.getTechnicalMaturityScore(techName),
      communityGrowth: this.getCommunityGrowthScore(techName)
    };

    const hypeScore = this.calculateHypeScore(metrics);
    const realityScore = this.calculateRealityScore(metrics);

    return {
      hypeLevel: hypeScore > 0.7 ? 'high' : hypeScore > 0.4 ? 'medium' : 'low',
      realityCheck: realityScore,
      recommendation: this.generateHypeRecommendation(hypeScore, realityScore),
      timeline: this.predictHypeCycle(techName)
    };
  }
}

// 基于用户行为和趋势的内容分发
class ContentDistributionEngine {
  constructor() {
    this.channels = ['homepage', 'newsletter', 'social', 'push'];
    this.contentPriority = new Map();
  }

  // 智能内容分发决策
  optimizeContentDistribution(content, targetAudience) {
    const distribution = {
      channels: [],
      timing: null,
      messaging: null,
      expectedReach: 0
    };

    // 基于内容类型选择最佳渠道
    distribution.channels = this.selectOptimalChannels(content, targetAudience);

    // 基于用户活跃时间选择发布时机
    distribution.timing = this.getOptimalTiming(targetAudience);

    // 为不同渠道定制消息
    distribution.messaging = this.customizeMessaging(content, distribution.channels);

    return distribution;
  }
}