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
5.2.2	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, you can checkout example from https://github.com/medcl/elasticsearch-rtf

Custom Analysis Configuration Example (elasticsearch.yml)

index:
  analysis:
    analyzer:
      my_mmseg_maxword:
        type: custom
        filter:
        - lowercase
        tokenizer: mmseg_maxword
      mmseg_maxword_with_cut_letter_digi:
        type: custom
        filter:
        - lowercase
        - cut_letter_digit
        tokenizer: mmseg_maxword    

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'
{
    "fulltext": {
             "_all": {
            "analyzer": "mmseg_maxword",
            "search_analyzer": "mmseg_maxword",
            "term_vector": "no",
            "store": "false"
        },
        "properties": {
            "content": {
                "type": "text",
                "store": "no",
                "term_vector": "with_positions_offsets",
                "analyzer": "mmseg_maxword",
                "search_analyzer": "mmseg_maxword",
                "include_in_all": "true",
                "boost": 8
            }
        }
    }
}'

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.