优化产品搜索逻辑，提升匹配准确性

boyang
1 parent 51e537e0
Showing 1 changed file with 71 additions and 20 deletions
shop/src/main/java/com/canrd/shop/service/impl/ProductServiceImpl.java
@@ -462,54 +462,105 @@ public class ProductServiceImpl extends ServiceImpl&lt;ProductMapper, ProductDO&gt; im
         Set<String> productIds = null;
         Map<String,List<TicketTypeDO>> pId2ttDOsMap = null;
         boolean needLikeMatch = false;
-        if(StringUtils.isNotBlank(productQueryVO.getKeyword())){
-            List<TicketTypeDO> tickeyTypeDOList = ticketTypeService.lambdaQuery().like(TicketTypeDO::getRank, productQueryVO.getKeyword()).list();
+//        if(StringUtils.isNotBlank(productQueryVO.getKeyword())){
+//            List<TicketTypeDO> tickeyTypeDOList = ticketTypeService.lambdaQuery().like(TicketTypeDO::getRank, productQueryVO.getKeyword()).list();
+//            productIds = tickeyTypeDOList.stream().map(TicketTypeDO::getProductId).collect(Collectors.toSet());
+//            needLikeMatch = true;
+//            pId2ttDOsMap = new HashMap<>();
+//            for (TicketTypeDO ticketTypeDO : tickeyTypeDOList) {
+//                pId2ttDOsMap.computeIfAbsent(ticketTypeDO.getProductId(), k -> new ArrayList<>());
+//                pId2ttDOsMap.get(ticketTypeDO.getProductId()).add(ticketTypeDO);
+//            }
+//            Set<String> finalProductIds = productIds;
+//            queryWapper.and(subQueryWapper -> {
+//                subQueryWapper.like("p.name", productQueryVO.getKeyword()).or().in(CollUtil.isNotEmpty(finalProductIds),"p.id", finalProductIds);
+//            });
+//        }
+        String keyword = productQueryVO.getKeyword().trim();
+        if (StringUtils.isNotBlank(productQueryVO.getKeyword())) {
+//            String keyword = productQueryVO.getKeyword().trim();
+
+            // 先精确匹配完整的关键字
+            List<TicketTypeDO> tickeyTypeDOList = ticketTypeService.lambdaQuery()
+                    .like(TicketTypeDO::getRank, keyword)
+                    .list();
+
             productIds = tickeyTypeDOList.stream().map(TicketTypeDO::getProductId).collect(Collectors.toSet());
             needLikeMatch = true;
             pId2ttDOsMap = new HashMap<>();
+
             for (TicketTypeDO ticketTypeDO : tickeyTypeDOList) {
                 pId2ttDOsMap.computeIfAbsent(ticketTypeDO.getProductId(), k -> new ArrayList<>());
                 pId2ttDOsMap.get(ticketTypeDO.getProductId()).add(ticketTypeDO);
             }
-            Set<String> finalProductIds = productIds;
-            queryWapper.and(subQueryWapper -> {
-                subQueryWapper.like("p.name", productQueryVO.getKeyword()).or().in(CollUtil.isNotEmpty(finalProductIds),"p.id", finalProductIds);
-            });
+
+            if (productIds.isEmpty()) {
+                // 如果没有匹配到，分词处理
+                String[] keywords = keyword.split("\\s+");
+
+                queryWapper.and(subQueryWapper -> {
+                    // 查询包含所有分词的记录
+                    for (String key : keywords) {
+                        subQueryWapper.like("p.name", key).or();
+                    }
+                });
+            } else {
+                Set<String> finalProductIds = productIds;
+
+                queryWapper.and(subQueryWapper -> {
+                    subQueryWapper.like("p.name", keyword).or().in(CollUtil.isNotEmpty(finalProductIds), "p.id", finalProductIds);
+                });
+            }
         }
         List<ProductDO> productDOS = this.baseMapper.queryList(queryWapper);
+        // Split the keyword into individual words
+        String[] keywords = keyword.split("\\s+");
+        Map<ProductDO, Integer> collect = productDOS.stream().collect(Collectors.toMap(Function.identity(), productDO -> {
+            int matchCount = 0;
+            for (String key : keywords) {
+                if (productDO.getName().toLowerCase().contains(key.toLowerCase())) {
+                    matchCount++;
+                }
+            }
+            return matchCount;
+        }));
+        productDOS.sort((product1, product2) -> {
+            int matchCount1 = collect.get(product1);
+            int matchCount2 = collect.get(product2);
+            // Return the comparison result: higher match count comes first
+            return Integer.compare(matchCount2, matchCount1);
+        });
         List<ProductDO> accurateProducts = Lists.newArrayList();
         Set<String> accurateProductIdSet = Sets.newHashSet();
         //区分大小写
         productDOS.forEach(x -> {
-            if(x.getName().trim().contains(productQueryVO.getKeyword().trim())){
-                accurateProducts.add(x);
-                accurateProductIdSet.add(x.getId());
-            }
+            accurateProducts.add(x);
+            accurateProductIdSet.add(x.getId());
         });
         List<ProductDO> similarProductList = Lists.newArrayList();
-        for(ProductDO product:productDOS){
-            if(accurateProductIdSet.contains(product.getId())){
+        for (ProductDO product : productDOS) {
+            if (accurateProductIdSet.contains(product.getId())) {
                 continue;
             }
             String name = product.getName();
-            int similar = LevenshteinDistanceService.LevenshteinDistancePercent(productQueryVO.getKeyword(),name);
-            if(similar>=0) {//模糊匹配
+            int similar = LevenshteinDistanceService.LevenshteinDistancePercent(productQueryVO.getKeyword(), name);
+            if (similar >= 0) {//模糊匹配
                 similarProductList.add(product);
                 product.setSimilar(similar);
             }
-            if(needLikeMatch&&productIds.contains(product.getId())){
+            if (needLikeMatch && productIds.contains(product.getId())) {
                 pId2ttDOsMap.get(product.getId()).forEach(x -> {
-                    int ttSimilar = LevenshteinDistanceService.LevenshteinDistancePercent(productQueryVO.getKeyword(),x.getRank());
+                    int ttSimilar = LevenshteinDistanceService.LevenshteinDistancePercent(productQueryVO.getKeyword(), x.getRank());
                     product.setTtsTotalSimilar(product.getTtsTotalSimilar() + ttSimilar);
                 });
             }
         }
         Collections.sort(similarProductList, (o1, o2) ->
                 {
-                    if (o2.getSimilar()-o1.getSimilar()!=0) {
-                        return o2.getSimilar()-o1.getSimilar();
-                    }else {
-                        return o2.getTtsTotalSimilar()-o1.getTtsTotalSimilar();
+                    if (o2.getSimilar() - o1.getSimilar() != 0) {
+                        return o2.getSimilar() - o1.getSimilar();
+                    } else {
+                        return o2.getTtsTotalSimilar() - o1.getTtsTotalSimilar();
                     }
                 }
         );