Mmseg Analysis for Elasticsearch
The Mmseg Analysis plugin integrates Lucene mmseg4j-analyzer:http://code.google.com/p/mmseg4j/ into elasticsearch, support customized dictionary.
The plugin ships with analyzers: mmseg_maxword ,mmseg_complex ,mmseg_simple and tokenizers: mmseg_maxword ,mmseg_complex ,mmseg_simple and token_filter: cut_letter_digit .
Versions
| Mmseg ver | ES version | 
|---|---|
| master | 5.x -> master | 
| 5.5.2 | 5.5.2 | 
| 5.4.3 | 5.4.3 | 
| 5.3.2 | 5.3.2 | 
| 5.2.2 | 5.2.2 | 
| 5.1.2 | 5.1.2 | 
| 1.10.1 | 2.4.1 | 
| 1.9.5 | 2.3.5 | 
| 1.8.1 | 2.2.1 | 
| 1.7.0 | 2.1.1 | 
| 1.5.0 | 2.0.0 | 
| 1.4.0 | 1.7.0 | 
| 1.3.0 | 1.6.0 | 
| 1.2.1 | 0.90.2 | 
| 1.1.2 | 0.20.1 | 
Package
mvn package
Install
Unzip and place into elasticsearch's plugins folder, download plugin from here: https://github.com/medcl/elasticsearch-analysis-mmseg/releases
Install by command: ./bin/elasticsearch-plugin install https://github.com/medcl/elasticsearch-analysis-mmseg/releases/download/v5.5.2/elasticsearch-analysis-mmseg-5.5.2.zip
Mapping Configuration
Here is a quick example:
1.Create a index
curl -XPUT http://localhost:9200/index
2.Create a mapping
curl -XPOST http://localhost:9200/index/fulltext/_mapping -d'
{
        "properties": {
            "content": {
                "type": "text",
                "term_vector": "with_positions_offsets",
                "analyzer": "mmseg_maxword",
                "search_analyzer": "mmseg_maxword"
            }
        }
    
}'
3.Indexing some docs
curl -XPOST http://localhost:9200/index/fulltext/1 -d'
{"content":"美国留给伊拉克的是个烂摊子吗"}
'
curl -XPOST http://localhost:9200/index/fulltext/2 -d'
{"content":"公安部:各地校车将享最高路权"}
'
curl -XPOST http://localhost:9200/index/fulltext/3 -d'
{"content":"中韩渔警冲突调查:韩警平均每天扣1艘中国渔船"}
'
curl -XPOST http://localhost:9200/index/fulltext/4 -d'
{"content":"中国驻洛杉矶领事馆遭亚裔男子枪击 嫌犯已自首"}
'
4.Query with highlighting
curl -XPOST http://localhost:9200/index/fulltext/_search  -d'
{
    "query" : { "term" : { "content" : "中国" }},
    "highlight" : {
        "pre_tags" : ["<tag1>", "<tag2>"],
        "post_tags" : ["</tag1>", "</tag2>"],
        "fields" : {
            "content" : {}
        }
    }
}
'
Here is the query result
{
    "took": 14,
    "timed_out": false,
    "_shards": {
        "total": 5,
        "successful": 5,
        "failed": 0
    },
    "hits": {
        "total": 2,
        "max_score": 2,
        "hits": [
            {
                "_index": "index",
                "_type": "fulltext",
                "_id": "4",
                "_score": 2,
                "_source": {
                    "content": "中国驻洛杉矶领事馆遭亚裔男子枪击 嫌犯已自首"
                },
                "highlight": {
                    "content": [
                        "<tag1>中国</tag1>驻洛杉矶领事馆遭亚裔男子枪击 嫌犯已自首 "
                    ]
                }
            },
            {
                "_index": "index",
                "_type": "fulltext",
                "_id": "3",
                "_score": 2,
                "_source": {
                    "content": "中韩渔警冲突调查:韩警平均每天扣1艘中国渔船"
                },
                "highlight": {
                    "content": [
                        "均每天扣1艘<tag1>中国</tag1>渔船 "
                    ]
                }
            }
        ]
    }
}
Have fun.
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 JarCasting