走conversion的情况不再出现组合词，直接走精确匹配，效果更好

@@ -113,7 +113,7 @@ public class SearchRecommendServiceImpl implements ISearchRecommendService {
             Double count = searchKeyWordService.getKeywordCount(RedisKeys.YOHO_SEARCH_KEYWORDS_EMPTY, queryWord);
             if (count == null || queryWord.length() >= 5) {
                 // 1.3) 如果该关键词一次都没有出现在空结果列表或者长度大于5 则该词很有可能是可以搜索出结果的 因此优先取suggest去搜索一把 减少后面的查询动作
-                JSONObject recommendResult = recommendBySuggestIndex(paramMap, keywordsToSearch);
+                JSONObject recommendResult = recommendBySuggestIndex(paramMap, keywordsToSearch, false);
                 if (recommendResult == null) {
                     return defaultSuggestRecommendation();
                 } else if (CollectionUtils.isNotEmpty((List) recommendResult.get("terms_suggestion"))) {
@@ -135,7 +135,7 @@ public class SearchRecommendServiceImpl implements ISearchRecommendService {
                 return defaultSuggestRecommendation();
             }
 
-            JSONObject recommendResult = recommendBySuggestIndex(paramMap, keywordsToSearch);
+            JSONObject recommendResult = recommendBySuggestIndex(paramMap, keywordsToSearch, dest != null);
             if (recommendResult == null || CollectionUtils.isEmpty((List) recommendResult.get("terms_suggestion"))) {
                 recommendResult = defaultSuggestRecommendation();
             }
@@ -182,9 +182,10 @@ public class SearchRecommendServiceImpl implements ISearchRecommendService {
      *
      * @param paramMap         搜索参数，用于判断取哪个count
      * @param keywordsToSearch 计算获取的推荐词列表
+     * @param isLimitKeywords  是否限制只能是推荐词列表里面的词
      * @return 搜推荐结果
      */
-    private JSONObject recommendBySuggestIndex(Map<String, String> paramMap, String keywordsToSearch) {
+    private JSONObject recommendBySuggestIndex(Map<String, String> paramMap, String keywordsToSearch, boolean isLimitKeywords) {
         String srcQueryWord = paramMap.get(SearchRequestParams.PARAM_SEARCH_KEYWORD);
         long begin = System.currentTimeMillis();
         logger.info("[func=recommendBySuggestIndex][srcQueryWord={}][keywordsToSearch={}][begin={}]", srcQueryWord, keywordsToSearch, begin);
@@ -195,7 +196,13 @@ public class SearchRecommendServiceImpl implements ISearchRecommendService {
         }
 
         // 2) 先对keywordsToSearch进行分词
-        List<String> terms = searchKeyWordService.getAnalyzeTerms(keywordsToSearch, "ik_smart", true);
+        List<String> terms = null;
+        if (isLimitKeywords) {
+            terms = Arrays.stream(keywordsToSearch.split(",")).filter(term -> term != null && term.length() > 1).distinct().collect(Collectors.toList());
+        } else {
+            terms = searchKeyWordService.getAnalyzeTerms(keywordsToSearch, "ik_smart", true);
+        }
+
         if (CollectionUtils.isEmpty(terms)) {
             return new JSONObject();
         }
@@ -207,39 +214,8 @@ public class SearchRecommendServiceImpl implements ISearchRecommendService {
         final String countField = suggestService.getCountField(paramMap);
         SearchParam searchParam = new SearchParam();
 
-        // 3.1) 对于suggest的multi-fields至少要有一个字段匹配到 匹配打分为常量1
-        MultiMatchQueryBuilder queryBuilder = QueryBuilders.multiMatchQuery(keywordsToSearch.trim().toLowerCase(),
-                "keyword", "keyword.keyword_ik", "keyword.keyword_pinyin", "keyword.keyword_jianpin", "keyword.keyword_lowercase")
-                .analyzer("ik_smart")
-                .type(MultiMatchQueryBuilder.Type.BEST_FIELDS)
-                .operator(MatchQueryBuilder.Operator.OR)
-                .minimumShouldMatch("1");
-
-
-        FunctionScoreQueryBuilder functionScoreQueryBuilder = new FunctionScoreQueryBuilder(QueryBuilders.constantScoreQuery(queryBuilder));
-        for (String term : termSet) {
-            // 3.2) 对于完全匹配Term的加1分
-            functionScoreQueryBuilder.add(QueryBuilders.termQuery("standardKeyword", CharUtils.standardized(term)),
-                    ScoreFunctionBuilders.weightFactorFunction(1));
-
-            // 3.3) 对于匹配到一个Term的加2分
-            functionScoreQueryBuilder.add(QueryBuilders.termQuery("keyword.keyword_ik", term),
-                    ScoreFunctionBuilders.weightFactorFunction(2));
-        }
-
-        // 3.4) 处理性别相关的关键词
-        if (terms.contains("男") && !terms.contains("女")) {
-            // 给女生相关减分
-            functionScoreQueryBuilder.add(QueryBuilders.termQuery("keyword.keyword_ik", "女"),
-                    ScoreFunctionBuilders.weightFactorFunction(-5));
-        } else if (!terms.contains("男") && terms.contains("女")) {
-            // 给男生相关减分
-            functionScoreQueryBuilder.add(QueryBuilders.termQuery("keyword.keyword_ik", "男"),
-                    ScoreFunctionBuilders.weightFactorFunction(-5));
-        }
-
-        functionScoreQueryBuilder.boostMode(CombineFunction.SUM);
-        searchParam.setQuery(functionScoreQueryBuilder);
+        QueryBuilder queryBuilder = isLimitKeywords ? buildQueryBuilderByLimit(terms) : buildQueryBuilder(keywordsToSearch, termSet);
+        searchParam.setQuery(queryBuilder);
         searchParam.setPage(1);
         searchParam.setSize(SMART_SUGGESTION_TERM_COUNT);
 
@@ -248,6 +224,9 @@ public class SearchRecommendServiceImpl implements ISearchRecommendService {
         boolFilter.must(QueryBuilders.termQuery("status", VALID_STATUS));
         boolFilter.must(QueryBuilders.rangeQuery(countField).gte(SMART_SUGGESTION_COUNT_LIMIT));
         boolFilter.mustNot(QueryBuilders.termQuery("standardKeyword", CharUtils.standardized(srcQueryWord)));
+        if (isLimitKeywords) {
+            boolFilter.must(QueryBuilders.termsQuery("standardKeyword", termSet.stream().map(term -> CharUtils.standardized(term)).collect(Collectors.toList())));
+        }
         searchParam.setFiter(boolFilter);
 
         // 3.6) 按照得分、权重、数量的规则降序排序
@@ -281,6 +260,57 @@ public class SearchRecommendServiceImpl implements ISearchRecommendService {
         return suggestResult;
     }
 
+    private QueryBuilder buildQueryBuilderByLimit(List<String> terms) {
+        FunctionScoreQueryBuilder functionScoreQueryBuilder = new FunctionScoreQueryBuilder(QueryBuilders.matchAllQuery());
+
+        // 给品类类型的关键词加分
+        functionScoreQueryBuilder.add(QueryBuilders.termQuery("type", Integer.valueOf(2)),
+                ScoreFunctionBuilders.weightFactorFunction(3));
+
+        // 按词出现的顺序加分
+        for (int i = 0; i < terms.size(); i++) {
+            functionScoreQueryBuilder.add(QueryBuilders.termQuery("standardKeyword", CharUtils.standardized(terms.get(i))),
+                    ScoreFunctionBuilders.weightFactorFunction(terms.size() - i));
+        }
+
+        functionScoreQueryBuilder.boostMode(CombineFunction.SUM);
+        return functionScoreQueryBuilder;
+    }
+
+    private QueryBuilder buildQueryBuilder(String keywordsToSearch, Set<String> termSet) {
+        // 3.1) 对于suggest的multi-fields至少要有一个字段匹配到 匹配打分为常量1
+        MultiMatchQueryBuilder queryBuilder = QueryBuilders.multiMatchQuery(keywordsToSearch.trim().toLowerCase(),
+                "keyword", "keyword.keyword_ik", "keyword.keyword_pinyin", "keyword.keyword_jianpin", "keyword.keyword_lowercase")
+                .analyzer("ik_smart")
+                .type(MultiMatchQueryBuilder.Type.BEST_FIELDS)
+                .operator(MatchQueryBuilder.Operator.OR)
+                .minimumShouldMatch("1");
+
+
+        FunctionScoreQueryBuilder functionScoreQueryBuilder = new FunctionScoreQueryBuilder(QueryBuilders.constantScoreQuery(queryBuilder));
+        for (String term : termSet) {
+            // 3.2) 对于完全匹配Term的加1分
+            functionScoreQueryBuilder.add(QueryBuilders.termQuery("standardKeyword", CharUtils.standardized(term)),
+                    ScoreFunctionBuilders.weightFactorFunction(1));
+
+            // 3.3) 对于匹配到一个Term的加2分
+            functionScoreQueryBuilder.add(QueryBuilders.termQuery("keyword.keyword_ik", term),
+                    ScoreFunctionBuilders.weightFactorFunction(2));
+        }
+
+        // 3.4) 处理性别相关的关键词
+        if (termSet.contains("男") && !termSet.contains("女")) {
+            functionScoreQueryBuilder.add(QueryBuilders.termQuery("keyword.keyword_ik", "女"),
+                    ScoreFunctionBuilders.weightFactorFunction(-5));
+        } else if (!termSet.contains("男") && termSet.contains("女")) {
+            functionScoreQueryBuilder.add(QueryBuilders.termQuery("keyword.keyword_ik", "男"),
+                    ScoreFunctionBuilders.weightFactorFunction(-5));
+        }
+
+        functionScoreQueryBuilder.boostMode(CombineFunction.SUM);
+        return functionScoreQueryBuilder;
+    }
+
     private boolean containsProductInSearchResult(SearchApiResult searchResult) {
         JSONObject dataMap = ((JSONObject) searchResult.getData());
         return CollectionUtils.isNotEmpty((List) dataMap.get("product_list"));