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https://github.com/lindera-morphology/lindera

A multilingual morphological analysis library.
https://github.com/lindera-morphology/lindera

analyzer library morphological multilingual tokenizer

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A multilingual morphological analysis library.

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README 

        
# Lindera



[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![Join the chat at https://gitter.im/lindera-morphology/lindera](https://badges.gitter.im/lindera-morphology/lindera.svg)](https://gitter.im/lindera-morphology/lindera?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [![Crates.io](https://img.shields.io/crates/v/lindera.svg)](https://crates.io/crates/lindera)



A morphological analysis library in Rust. This project fork from [kuromoji-rs](https://github.com/fulmicoton/kuromoji-rs).



Lindera aims to build a library which is easy to install and provides concise APIs for various Rust applications.



The following products are required to build:



- Rust >= 1.46.0



## Tokenizer Usage



### Basic tokenizer example



Put the following in Cargo.toml:



```toml

[dependencies]

lindera-tokenizer = { version = "0.31.0", features = ["ipadic"] }

```



This example covers the basic usage of Lindera.



It will:



- Create a tokenizer in normal mode

- Tokenize the input text

- Output the tokens



```rust

use lindera::{

    DictionaryConfig, DictionaryKind, LinderaResult, Mode, Tokenizer, TokenizerConfig,

};



fn main() -> LinderaResult<()> {

    let dictionary = DictionaryConfig {

        kind: Some(DictionaryKind::IPADIC),

        path: None,

    };



    let config = TokenizerConfig {

        dictionary,

        user_dictionary: None,

        mode: Mode::Normal,

    };



    // create tokenizer

    let tokenizer = Tokenizer::from_config(config)?;



    // tokenize the text

    let tokens = tokenizer.tokenize("関西国際空港限定トートバッグ")?;



    // output the tokens

    for token in tokens {

        println!("{}", token.text);

    }



    Ok(())

}

```



The above example can be run as follows:



```shell

% cargo run --features=ipadic --example=ipadic_basic_example

```



You can see the result as follows:



```text

関西国際空港

限定

トートバッグ

```



### User dictionary example



You can give user dictionary entries along with the default system dictionary. User dictionary should be a CSV with following format.



```csv

,,

```



Put the following in Cargo.toml:



```toml

[dependencies]

lindera-tokenizer = { version = "0.31.0", features = ["ipadic"] }

```



For example:



```shell

% cat ./resources/simple_userdic.csv

東京スカイツリー,カスタム名詞,トウキョウスカイツリー

東武スカイツリーライン,カスタム名詞,トウブスカイツリーライン

とうきょうスカイツリー駅,カスタム名詞,トウキョウスカイツリーエキ

```



With an user dictionary, `Tokenizer` will be created as follows:



```rust

use std::path::PathBuf;



use lindera::{

    DictionaryConfig, DictionaryKind, LinderaResult, Mode, Tokenizer, TokenizerConfig,

    UserDictionaryConfig,

};



fn main() -> LinderaResult<()> {

    let dictionary = DictionaryConfig {

        kind: Some(DictionaryKind::IPADIC),

        path: None,

    };



    let user_dictionary = Some(UserDictionaryConfig {

        kind: DictionaryKind::IPADIC,

        path: PathBuf::from("./resources/ipadic_simple_userdic.csv"),

    });



    let config = TokenizerConfig {

        dictionary,

        user_dictionary,

        mode: Mode::Normal,

    };



    let tokenizer = Tokenizer::from_config(config)?;



    // tokenize the text

    let tokens = tokenizer.tokenize("東京スカイツリーの最寄り駅はとうきょうスカイツリー駅です")?;



    // output the tokens

    for token in tokens {

        println!("{}", token.text);

    }



    Ok(())

}

```



The above example can be by `cargo run --example`:



```shell

% cargo run --features=ipadic --example=ipadic_userdic_example

東京スカイツリー

の

最寄り駅

は

とうきょうスカイツリー駅

です

```



## Anzalyzer Usage



### Basic analyzer example



Put the following in Cargo.toml:



```toml

[dependencies]

lindera-analyzer = { version = "0.31.0", features = ["ipadic", "filter"] }

```



This example covers the basic usage of Lindera Analysis Framework.



It will:



- Apply character filter for Unicode normalization (NFKC)

- Tokenize the input text with IPADIC

- Apply token filters for removing stop tags (Part-of-speech) and Japanese Katakana stem filter



```rust

use std::collections::HashSet;



use lindera::{

    Analyzer, BoxCharacterFilter, BoxTokenFilter, DictionaryConfig, DictionaryKind,

    JapaneseCompoundWordTokenFilter, JapaneseCompoundWordTokenFilterConfig,

    JapaneseIterationMarkCharacterFilter, JapaneseIterationMarkCharacterFilterConfig,

    JapaneseNumberTokenFilter, JapaneseNumberTokenFilterConfig,

    JapaneseStopTagsTokenFilter, JapaneseStopTagsTokenFilterConfig, LinderaResult, Mode,

    Tokenizer, TokenizerConfig, UnicodeNormalizeCharacterFilter,

    UnicodeNormalizeCharacterFilterConfig, UnicodeNormalizeKind,

};



fn main() -> LinderaResult<()> {

    let mut character_filters: Vec = Vec::new();



    let unicode_normalize_character_filter_config =

            UnicodeNormalizeCharacterFilterConfig::new(UnicodeNormalizeKind::NFKC);

    let unicode_normalize_character_filter =

        UnicodeNormalizeCharacterFilter::new(unicode_normalize_character_filter_config);

    character_filters.push(BoxCharacterFilter::from(unicode_normalize_character_filter));



    let japanese_iteration_mark_character_filter_config =

        JapaneseIterationMarkCharacterFilterConfig::new(true, true);

    let japanese_iteration_mark_character_filter = JapaneseIterationMarkCharacterFilter::new(

        japanese_iteration_mark_character_filter_config,

    );

    character_filters.push(BoxCharacterFilter::from(

        japanese_iteration_mark_character_filter,

    ));



    let dictionary = DictionaryConfig {

        kind: Some(DictionaryKind::IPADIC),

        path: None,

    };



    let config = TokenizerConfig {

        dictionary,

        user_dictionary: None,

        mode: Mode::Normal,

    };



    let tokenizer = Tokenizer::from_config(config).unwrap();



    let mut token_filters: Vec = Vec::new();



    let japanese_compound_word_token_filter_config =

        JapaneseCompoundWordTokenFilterConfig::new(

            DictionaryKind::IPADIC,

            HashSet::from_iter(vec!["名詞,数".to_string()]),

            Some("名詞,数".to_string()),

        )?;

    let japanese_compound_word_token_filter =

        JapaneseCompoundWordTokenFilter::new(japanese_compound_word_token_filter_config);

    token_filters.push(BoxTokenFilter::from(japanese_compound_word_token_filter));



    let japanese_number_token_filter_config =

        JapaneseNumberTokenFilterConfig::new(Some(HashSet::from_iter(vec![

            "名詞,数".to_string()

        ])));

    let japanese_number_token_filter =

        JapaneseNumberTokenFilter::new(japanese_number_token_filter_config);

    token_filters.push(BoxTokenFilter::from(japanese_number_token_filter));



    let japanese_stop_tags_token_filter_config =

        JapaneseStopTagsTokenFilterConfig::new(HashSet::from_iter(vec![

            "接続詞".to_string(),

            "助詞".to_string(),

            "助詞,格助詞".to_string(),

            "助詞,格助詞,一般".to_string(),

            "助詞,格助詞,引用".to_string(),

            "助詞,格助詞,連語".to_string(),

            "助詞,係助詞".to_string(),

            "助詞,副助詞".to_string(),

            "助詞,間投助詞".to_string(),

            "助詞,並立助詞".to_string(),

            "助詞,終助詞".to_string(),

            "助詞,副助詞／並立助詞／終助詞".to_string(),

            "助詞,連体化".to_string(),

            "助詞,副詞化".to_string(),

            "助詞,特殊".to_string(),

            "助動詞".to_string(),

            "記号".to_string(),

            "記号,一般".to_string(),

            "記号,読点".to_string(),

            "記号,句点".to_string(),

            "記号,空白".to_string(),

            "記号,括弧閉".to_string(),

            "その他,間投".to_string(),

            "フィラー".to_string(),

            "非言語音".to_string(),

        ]));

    let japanese_stop_tags_token_filter =

        JapaneseStopTagsTokenFilter::new(japanese_stop_tags_token_filter_config);

    token_filters.push(BoxTokenFilter::from(japanese_stop_tags_token_filter));



    let analyzer = Analyzer::new(character_filters, tokenizer, token_filters);



    let mut text =

        "Ｌｉｎｄｅｒａは形態素解析ｴﾝｼﾞﾝです。ユーザー辞書も利用可能です。".to_string();

    println!("text: {}", text);



    // tokenize the text

    let tokens = analyzer.analyze(&mut text)?;



    // output the tokens

    for token in tokens {

        println!(

            "token: {:?}, start: {:?}, end: {:?}, details: {:?}",

            token.text, token.byte_start, token.byte_end, token.details

        );

    }



    Ok(())

}

```



The above example can be run as follows:



```shell

% cargo run --features=ipadic,filter --example=analysis_example

```



You can see the result as follows:



```text

text: Ｌｉｎｄｅｒａは形態素解析ｴﾝｼﾞﾝです。ユーザー辞書も利用可能です。

token: Lindera, start: 0, end: 21, details: Some(["UNK"])

token: 形態素, start: 24, end: 33, details: Some(["名詞", "一般", "*", "*", "*", "*", "形態素", "ケイタイソ", "ケイタイソ"])

token: 解析, start: 33, end: 39, details: Some(["名詞", "サ変接続", "*", "*", "*", "*", "解析", "カイセキ", "カイセキ"])

token: エンジン, start: 39, end: 54, details: Some(["名詞", "一般", "*", "*", "*", "*", "エンジン", "エンジン", "エンジン"])

token: ユーザ, start: 0, end: 26, details: Some(["名詞", "一般", "*", "*", "*", "*", "ユーザー", "ユーザー", "ユーザー"])

token: 辞書, start: 26, end: 32, details: Some(["名詞", "一般", "*", "*", "*", "*", "辞書", "ジショ", "ジショ"])

token: 利用, start: 35, end: 41, details: Some(["名詞", "サ変接続", "*", "*", "*", "*", "利用", "リヨウ", "リヨー"])

token: 可能, start: 41, end: 47, details: Some(["名詞", "形容動詞語幹", "*", "*", "*", "*", "可能", "カノウ", "カノー"])

```



## API reference



The API reference is available. Please see following URL:



- [lindera](https://docs.rs/lindera)