搜索学习基础--代码模拟倒排索引过程

超、凢脫俗 2022-06-06 05:43 155阅读 0赞

之前已经分析了倒排索引的过程[倒排索引过程解读][Link 1] 那么，接下来用代码实现一下其过程，加深了解：

package search;
    
    
    import java.util.*;
    
    /**
     * 模拟倒排索引（只支持英文）
     *
     * @author yuyufeng
     * @date 2017/10/31
     */
    public class InvertedIndex {
    
        /**
         * 倒排索引表
         */
        Map<String, IndexTable> keywordsIndexTableMap = new HashMap<>();
    
        /**
         * 停顿词
         */
        Set<String> stopwords = new HashSet<>();
    
        /**
         * 存储文档
         */
        List<String> store;
    
        public InvertedIndex(List<String> list) {
            store = list;
            for (int i = 0; i < list.size(); i++) {
                String li = keywordsHandler(list.get(i));
                String[] array = li.split(" ");
                for (int j = 0; j < array.length; j++) {
                    addKeyWords(array[j], i, j);
                }
            }
            //停顿词 非关键词
            stopwords.add("is");
            stopwords.add("and");
            stopwords.add("or");
            stopwords.add("the");
        }
    
        /**
         * 建立索引 建立倒排索引表
         */
        public void addKeyWords(String keywords, Integer i, Integer j) {
            //去空
            if ("".equals(keywords)) {
                return;
            }
            IndexTable indexTable = keywordsIndexTableMap.get(keywords);
            if (indexTable == null) {
                //插入关键词信息
                indexTable = new IndexTable();
                indexTable.keywords = keywords;
                //插入关键词出现的文档Id,次数为1（首次出现）
                indexTable.docTimes.put(i, 1);
                //插入关键词出现的文档Id,在文档中位置
                indexTable.docIndex.put(i, " "+j);
                keywordsIndexTableMap.put(keywords, indexTable);
            } else {
                //更新关键词出现的文档、频率
                indexTable.docTimes.put(i, indexTable.docTimes.get(i) == null ? 1 : indexTable.docTimes.get(i) + 1);
                //更新关键词出现的文档、位置
                indexTable.docIndex.put(i, (indexTable.docIndex.get(i) == null ? "" : indexTable.docIndex.get(i)) + " " + j);
                keywordsIndexTableMap.put(keywords, indexTable);
            }
        }
    
    
        //去除无关词，统一大小写
        private String keywordsHandler(String doc) {
            doc = doc.replaceAll(",|:|\\.", " ");
            doc = doc.toLowerCase();
            return doc;
        }
    
        /**
         * 查询
         * @param keywords
         * @return
         */
        public List<String> search(String keywords) {
            keywords = keywordsHandler(keywords);
    
            //用Set可以去重
            String[] kewordsArray = keywords.split(" ");
    
            List<String> result = new ArrayList<>();
    
            //<文档，出现次数>
            Map<Integer, DocTemp> docSortTimes = new HashMap();
    
            for (int i = 0; i < kewordsArray.length; i++) {
                String key = kewordsArray[i];
                IndexTable indexTable = keywordsIndexTableMap.get(key);
                if (indexTable == null) {
                    continue;
                }
                //找到关键词，统计出现的文档，频率，出现的文档数
                for (Integer integer : indexTable.docTimes.keySet()) {
                    if (docSortTimes.get(integer) == null) {
                        DocTemp docTemp = new DocTemp();
                        docTemp.docId = integer;
                        docTemp.times = 1;
                        docTemp.allTimes = indexTable.docTimes.get(integer);
                        docSortTimes.put(integer, docTemp);
                    } else {
                        DocTemp docTemp = docSortTimes.get(integer);
                        docTemp.times++;
                        docTemp.allTimes += indexTable.docTimes.get(integer);
                    }
                }
            }
    
            List<DocTemp> docTemps = new ArrayList<>();
            //转化List 排序
            for (Integer docId : docSortTimes.keySet()) {
                DocTemp docTemp = docSortTimes.get(docId);
                docTemps.add(docTemp);
            }
    
            //对结果排序，一个Doc包含关键词越多，排名越前。如相等，则比较出现总次数  \\这个规则可以自定义
            docTemps.sort(new Comparator<DocTemp>() {
                @Override
                public int compare(DocTemp o1, DocTemp o2) {
                    if(o1.times.equals(o2.times)){
                        return o2.allTimes - o1.times;
                    }
                    return o2.times-o1.times;
                }
            });
    
            //包装结果
            for (int i = 0; i < docTemps.size(); i++) {
                result.add(store.get(docTemps.get(i).docId));
            }
    
            return result;
        }
    
        public static void main(String[] args) {
            List<String> docs = new ArrayList<>();
            //docId = 0
            String doc = "Inverted index comes from the actual application, it needs to find the record according to the value of the attribute.";
            docs.add(doc);
            //docId = 1
            doc = "Each item Each in the index table includes an attribute value and the address of each record with the attribute value";
            docs.add(doc);
            //docId = 2
            doc = "Attribute values are not determined by records";
            docs.add(doc);
            //docId = 3
            doc = "Rather, the location of the record is determined by the attribute value";
            docs.add(doc);
            //docId = 4
            doc = "It is called inverted index";
            docs.add(doc);
            //docId = 5
            doc = "The data operation is simple: the data used by the search engine is easy to operate, generally speaking, only need to add, delete, change, check several functions";
            docs.add(doc);
            //docId = 6
            doc = "And data has a specific format, you can design simple and efficient applications for these applications";
            docs.add(doc);
            //建立索引
            InvertedIndex invertedIndex = new InvertedIndex(docs);
    
            //查看倒排索引表
            System.out.println("关键词 出现doc[次数],{位置}");
            for (String key : invertedIndex.keywordsIndexTableMap.keySet()) {
                System.out.print(key + " ");
                IndexTable indexTable = invertedIndex.keywordsIndexTableMap.get(key);
                for (Integer integer : indexTable.docTimes.keySet()) {
                    System.out.print(integer + "[" + indexTable.docTimes.get(integer) + "],");
                    System.out.print("{" + indexTable.docIndex.get(integer) + "} ");
                }
                System.out.println("");
            }
    
    
            //执行查询
            List<String> results = invertedIndex.search("specific format location determined attribute");
    
            System.out.println("=========== 查询结果 ==========");
            for (String result : results) {
                System.out.println(result);
            }
        }
    }
    
    /**
     * 倒排索引表
     */
    class IndexTable {
        /**
         * 关键词
         */
        String keywords;
    
        /**
         * 出现频率
         */
        Map<Integer, Integer> docTimes = new HashMap<>();
    
        /**
         * 出现位置
         */
        Map<Integer, String> docIndex = new HashMap<>();
    }
    
    /**
     * 用于排序
     */
    class DocTemp {
        Integer docId;
        Integer times;  //出现在多少Doc中
        Integer allTimes;  //出现总次数
    }

### 运行结果 ###

关键词 出现doc[次数],{位置}
    called 4[1],{ 2} 
    data 5[2],{ 1 7} 6[1],{ 1} 
    functions 5[1],{ 32} 
    several 5[1],{ 31} 
    simple 5[1],{ 4} 6[1],{ 10} 
    used 5[1],{ 8} 
    these 6[1],{ 15} 
    speaking 5[1],{ 19} 
    find 0[1],{ 11} 
    record 0[1],{ 13} 1[1],{ 16} 3[1],{ 6} 
    only 5[1],{ 21} 
    from 0[1],{ 3} 
    has 6[1],{ 2} 
    inverted 0[1],{ 0} 4[1],{ 3} 
    you 6[1],{ 7} 
    needs 0[1],{ 9} 
    add 5[1],{ 24} 
    actual 0[1],{ 5} 
    item 1[1],{ 1} 
    in 1[1],{ 3} 
    need 5[1],{ 22} 
    format 6[1],{ 5} 
    index 0[1],{ 1} 1[1],{ 5} 4[1],{ 4} 
    includes 1[1],{ 7} 
    is 3[1],{ 7} 4[1],{ 1} 5[2],{ 3 13} 
    it 0[1],{ 8} 4[1],{ 0} 
    check 5[1],{ 30} 
    an 1[1],{ 8} 
    easy 5[1],{ 14} 
    each 1[3],{ 0 2 15} 
    operate 5[1],{ 16} 
    determined 2[1],{ 4} 3[1],{ 8} 
    records 2[1],{ 6} 
    rather 3[1],{ 0} 
    values 2[1],{ 1} 
    comes 0[1],{ 2} 
    according 0[1],{ 14} 
    for 6[1],{ 14} 
    delete 5[1],{ 26} 
    can 6[1],{ 8} 
    not 2[1],{ 3} 
    search 5[1],{ 11} 
    are 2[1],{ 2} 
    engine 5[1],{ 12} 
    and 1[1],{ 11} 6[2],{ 0 11} 
    of 0[1],{ 18} 1[1],{ 14} 3[1],{ 4} 
    by 2[1],{ 5} 3[1],{ 9} 5[1],{ 9} 
    design 6[1],{ 9} 
    attribute 0[1],{ 20} 1[2],{ 9 19} 2[1],{ 0} 3[1],{ 11} 
    value 0[1],{ 17} 1[2],{ 10 20} 3[1],{ 12} 
    table 1[1],{ 6} 
    a 6[1],{ 3} 
    address 1[1],{ 13} 
    efficient 6[1],{ 12} 
    change 5[1],{ 28} 
    specific 6[1],{ 4} 
    generally 5[1],{ 18} 
    the 0[4],{ 4 12 16 19} 1[3],{ 4 12 18} 3[3],{ 2 5 10} 5[3],{ 0 6 10} 
    with 1[1],{ 17} 
    application 0[1],{ 6} 
    location 3[1],{ 3} 
    to 0[2],{ 10 15} 5[2],{ 15 23} 
    operation 5[1],{ 2} 
    applications 6[2],{ 13 16} 
    =========== 查询结果 ==========
    Inverted index comes from the actual application, it needs to find the record according to the value of the attribute.
    It is called inverted index
    Each item Each in the index table includes an attribute value and the address of each record with the attribute value

[Link 1]: http://blog.csdn.net/qq_18860653/article/details/78399983