💖💖作者：计算机毕业设计江挽 💙💙个人简介：曾长期从事计算机专业培训教学，本人也热爱上课教学，语言擅长Java、微信小程序、Python、Golang、安卓Android等，开发项目包括大数据、深度学习、网站、小程序、安卓、算法。平常会做一些项目定制化开发、代码讲解、答辩教学、文档编写、也懂一些降重方面的技巧。平常喜欢分享一些自己开发中遇到的问题的解决办法，也喜欢交流技术，大家有技术代码这一块的问题可以问我！ 💛💛想说的话：感谢大家的关注与支持！ 💜💜 网站实战项目 安卓/小程序实战项目 大数据实战项目 深度学习实战项目
基于智能推荐算法的全屋定制平台网站设计介绍
基于智能推荐算法的全屋定制平台网站设计是一个集成了现代化推荐技术与家装定制服务的综合性平台系统。该系统采用SpringBoot作为后端框架，结合Vue+ElementUI构建前端交互界面，通过MySQL数据库存储用户行为数据、商品信息和设计方案等核心数据。平台主要面向有全屋定制需求的用户群体，通过智能推荐算法分析用户的浏览历史、收藏偏好、预算范围等多维度信息，为用户精准推荐适合的装修风格、设计方案和家具材料组合。系统设置了用户端和设计师端双重角色权限管理，用户可以在平台上浏览精选家装和工装案例，提交个人定制需求，查看推荐的设计类型和材料搭配方案；设计师则可以管理设计作品，响应用户定制需求，上传设计方案到设计专区供用户参考。平台还整合了完整的商品管理体系，包括家具分类展示、装修材料库存管理、订单流程跟踪等功能模块，通过B/S架构实现了跨平台访问，为全屋定制行业提供了一套完整的数字化解决方案。
基于智能推荐算法的全屋定制平台网站设计演示视频
基于智能推荐算法的全屋定制平台网站设计演示图片
基于智能推荐算法的全屋定制平台网站设计代码展示
SparkSession spark = SparkSession.builder().appName("HomeCustomizationRecommendation").config("spark.master", "local").getOrCreate();
@Service
public class IntelligentRecommendationService {
@Autowired
private UserBehaviorMapper userBehaviorMapper;
@Autowired
private ProductMapper productMapper;
@Autowired
private DesignSchemeMapper designSchemeMapper;
public List<RecommendationResult> generatePersonalizedRecommendation(Long userId) {
List<UserBehavior> userBehaviors = userBehaviorMapper.getUserBehaviorHistory(userId);
Map<String, Double> userPreferences = analyzeUserPreferences(userBehaviors);
List<Product> candidateProducts = productMapper.getAllAvailableProducts();
List<RecommendationResult> recommendations = new ArrayList<>();
for (Product product : candidateProducts) {
double similarityScore = calculateSimilarityScore(userPreferences, product);
if (similarityScore > 0.6) {
RecommendationResult result = new RecommendationResult();
result.setProductId(product.getId());
result.setProductName(product.getName());
result.setScore(similarityScore);
result.setReasonCode(generateReasonCode(userPreferences, product));
recommendations.add(result);
}
}
recommendations.sort((r1, r2) -> Double.compare(r2.getScore(), r1.getScore()));
return recommendations.subList(0, Math.min(10, recommendations.size()));
}
private Map<String, Double> analyzeUserPreferences(List<UserBehavior> behaviors) {
Map<String, Integer> categoryCount = new HashMap<>();
Map<String, Integer> styleCount = new HashMap<>();
Map<String, Integer> priceRangeCount = new HashMap<>();
for (UserBehavior behavior : behaviors) {
categoryCount.put(behavior.getCategory(), categoryCount.getOrDefault(behavior.getCategory(), 0) + behavior.getWeight());
styleCount.put(behavior.getStyle(), styleCount.getOrDefault(behavior.getStyle(), 0) + behavior.getWeight());
priceRangeCount.put(behavior.getPriceRange(), priceRangeCount.getOrDefault(behavior.getPriceRange(), 0) + behavior.getWeight());
}
Map<String, Double> preferences = new HashMap<>();
int totalBehaviors = behaviors.size();
for (Map.Entry<String, Integer> entry : categoryCount.entrySet()) {
preferences.put("category_" + entry.getKey(), (double) entry.getValue() / totalBehaviors);
}
for (Map.Entry<String, Integer> entry : styleCount.entrySet()) {
preferences.put("style_" + entry.getKey(), (double) entry.getValue() / totalBehaviors);
}
for (Map.Entry<String, Integer> entry : priceRangeCount.entrySet()) {
preferences.put("price_" + entry.getKey(), (double) entry.getValue() / totalBehaviors);
}
return preferences;
}
}
@Service
public class PersonalCustomizationService {
@Autowired
private CustomizationRequestMapper requestMapper;
@Autowired
private DesignerMapper designerMapper;
@Autowired
private MaterialMapper materialMapper;
public CustomizationPlan processCustomizationRequest(CustomizationRequest request) {
CustomizationPlan plan = new CustomizationPlan();
plan.setUserId(request.getUserId());
plan.setRequestId(request.getId());
plan.setHouseArea(request.getHouseArea());
plan.setBudgetRange(request.getBudgetRange());
List<Designer> matchedDesigners = findMatchingDesigners(request);
plan.setRecommendedDesigners(matchedDesigners);
List<Material> recommendedMaterials = selectOptimalMaterials(request);
plan.setMaterialList(recommendedMaterials);
double estimatedCost = calculateEstimatedCost(recommendedMaterials, request.getHouseArea());
plan.setEstimatedCost(estimatedCost);
String designSuggestion = generateDesignSuggestion(request);
plan.setDesignSuggestion(designSuggestion);
plan.setCreateTime(new Date());
plan.setStatus("PENDING_CONFIRMATION");
return plan;
}
private List<Designer> findMatchingDesigners(CustomizationRequest request) {
List<Designer> allDesigners = designerMapper.getActiveDesigners();
List<Designer> matchedDesigners = new ArrayList<>();
for (Designer designer : allDesigners) {
boolean styleMatch = designer.getSpecialtyStyles().contains(request.getPreferredStyle());
boolean budgetMatch = designer.getMinBudget() <= request.getBudgetRange() && designer.getMaxBudget() >= request.getBudgetRange();
boolean areaMatch = designer.getServiceAreas().contains(request.getServiceArea());
if (styleMatch && budgetMatch && areaMatch) {
matchedDesigners.add(designer);
}
}
matchedDesigners.sort((d1, d2) -> Double.compare(d2.getRating(), d1.getRating()));
return matchedDesigners.subList(0, Math.min(5, matchedDesigners.size()));
}
private List<Material> selectOptimalMaterials(CustomizationRequest request) {
List<Material> availableMaterials = materialMapper.getMaterialsByCategory(request.getRoomTypes());
List<Material> selectedMaterials = new ArrayList<>();
Map<String, List<Material>> categoryMaterials = availableMaterials.stream().collect(Collectors.groupingBy(Material::getCategory));
for (Map.Entry<String, List<Material>> entry : categoryMaterials.entrySet()) {
List<Material> materials = entry.getValue();
materials = materials.stream().filter(m -> m.getPrice() <= request.getBudgetRange() * 0.15).collect(Collectors.toList());
if (!materials.isEmpty()) {
materials.sort((m1, m2) -> Double.compare(m2.getQualityScore(), m1.getQualityScore()));
selectedMaterials.add(materials.get(0));
}
}
return selectedMaterials;
}
}
@Service
public class OrderManagementService {
@Autowired
private OrderMapper orderMapper;
@Autowired
private PaymentService paymentService;
@Autowired
private InventoryService inventoryService;
@Transactional
public OrderProcessResult processOrder(OrderRequest orderRequest) {
Order order = new Order();
order.setUserId(orderRequest.getUserId());
order.setDesignerId(orderRequest.getDesignerId());
order.setOrderNumber(generateOrderNumber());
order.setTotalAmount(orderRequest.getTotalAmount());
order.setStatus("PENDING_PAYMENT");
order.setCreateTime(new Date());
List<OrderItem> orderItems = new ArrayList<>();
for (OrderItemRequest itemRequest : orderRequest.getItems()) {
boolean inventoryAvailable = inventoryService.checkInventoryAvailability(itemRequest.getProductId(), itemRequest.getQuantity());
if (!inventoryAvailable) {
throw new BusinessException("商品库存不足：" + itemRequest.getProductName());
}
OrderItem orderItem = new OrderItem();
orderItem.setOrderId(order.getId());
orderItem.setProductId(itemRequest.getProductId());
orderItem.setProductName(itemRequest.getProductName());
orderItem.setQuantity(itemRequest.getQuantity());
orderItem.setUnitPrice(itemRequest.getUnitPrice());
orderItem.setSubtotal(itemRequest.getQuantity() * itemRequest.getUnitPrice());
orderItems.add(orderItem);
inventoryService.reserveInventory(itemRequest.getProductId(), itemRequest.getQuantity());
}
order.setOrderItems(orderItems);
orderMapper.insertOrder(order);
OrderProcessResult result = new OrderProcessResult();
result.setOrderId(order.getId());
result.setOrderNumber(order.getOrderNumber());
result.setPaymentUrl(paymentService.generatePaymentUrl(order));
result.setEstimatedDeliveryDate(calculateEstimatedDeliveryDate(order));
result.setMessage("订单创建成功，请及时完成支付");
return result;
}
public void updateOrderStatus(Long orderId, String newStatus, String remark) {
Order order = orderMapper.getOrderById(orderId);
if (order == null) {
throw new BusinessException("订单不存在");
}
String currentStatus = order.getStatus();
boolean statusUpdateValid = validateStatusTransition(currentStatus, newStatus);
if (!statusUpdateValid) {
throw new BusinessException("订单状态更新不合法");
}
order.setStatus(newStatus);
order.setUpdateTime(new Date());
if (remark != null && !remark.trim().isEmpty()) {
order.setRemark(remark);
}
if ("COMPLETED".equals(newStatus)) {
order.setCompleteTime(new Date());
for (OrderItem item : order.getOrderItems()) {
inventoryService.confirmInventoryUsage(item.getProductId(), item.getQuantity());
}
} else if ("CANCELLED".equals(newStatus)) {
for (OrderItem item : order.getOrderItems()) {
inventoryService.releaseReservedInventory(item.getProductId(), item.getQuantity());
}
}
orderMapper.updateOrder(order);
}
}
基于智能推荐算法的全屋定制平台网站设计文档展示
💖💖作者：计算机毕业设计江挽 💙💙个人简介：曾长期从事计算机专业培训教学，本人也热爱上课教学，语言擅长Java、微信小程序、Python、Golang、安卓Android等，开发项目包括大数据、深度学习、网站、小程序、安卓、算法。平常会做一些项目定制化开发、代码讲解、答辩教学、文档编写、也懂一些降重方面的技巧。平常喜欢分享一些自己开发中遇到的问题的解决办法，也喜欢交流技术，大家有技术代码这一块的问题可以问我！ 💛💛想说的话：感谢大家的关注与支持！ 💜💜 网站实战项目 安卓/小程序实战项目 大数据实战项目 深度学习实战项目
