elasticsearch-analysis-pinyin | Pinyin Analysis plugin is used to do conversion
kandi X-RAY | elasticsearch-analysis-pinyin Summary
kandi X-RAY | elasticsearch-analysis-pinyin Summary
elasticsearch-analysis-pinyin is a Java library. elasticsearch-analysis-pinyin has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub, Maven.
this pinyin analysis plugin is used to do conversion between chinese characters and pinyin, integrates nlp tools (the plugin includes analyzer: pinyin , tokenizer: pinyin and token-filter: pinyin. 1.create a index with custom pinyin analyzer put /medcl/ { "settings" : { "analysis" : { "analyzer" : { "pinyin_analyzer" : { "tokenizer" : "my_pinyin" } }, "tokenizer" : { "my_pinyin" : { "type" : "pinyin", "keep_separate_first_letter" : false, "keep_full_pinyin" : true, "keep_original" : true, "limit_first_letter_length" : 16, "lowercase" : true, "remove_duplicated_term" : true } } } } } . 2.test analyzer, analyzing a chinese name, such as 刘德华 get /medcl/_analyze { "text": ["刘德华"], "analyzer": "pinyin_analyzer" } { "tokens" : [ { "token" : "liu", "start_offset" : 0, "end_offset" : 1, "type" : "word", "position" : 0 }, { "token" : "de", "start_offset" : 1, "end_offset" : 2, "type" : "word", "position" : 1 }, { "token" : "hua", "start_offset" : 2, "end_offset" : 3, "type" : "word", "position" : 2 }, { "token" : "刘德华", "start_offset" : 0, "end_offset" : 3, "type" : "word", "position" : 3 }, { "token" : "ldh", "start_offset" : 0, "end_offset" : 3, "type" : "word", "position" : 4 } ] }
this pinyin analysis plugin is used to do conversion between chinese characters and pinyin, integrates nlp tools (the plugin includes analyzer: pinyin , tokenizer: pinyin and token-filter: pinyin. 1.create a index with custom pinyin analyzer put /medcl/ { "settings" : { "analysis" : { "analyzer" : { "pinyin_analyzer" : { "tokenizer" : "my_pinyin" } }, "tokenizer" : { "my_pinyin" : { "type" : "pinyin", "keep_separate_first_letter" : false, "keep_full_pinyin" : true, "keep_original" : true, "limit_first_letter_length" : 16, "lowercase" : true, "remove_duplicated_term" : true } } } } } . 2.test analyzer, analyzing a chinese name, such as 刘德华 get /medcl/_analyze { "text": ["刘德华"], "analyzer": "pinyin_analyzer" } { "tokens" : [ { "token" : "liu", "start_offset" : 0, "end_offset" : 1, "type" : "word", "position" : 0 }, { "token" : "de", "start_offset" : 1, "end_offset" : 2, "type" : "word", "position" : 1 }, { "token" : "hua", "start_offset" : 2, "end_offset" : 3, "type" : "word", "position" : 2 }, { "token" : "刘德华", "start_offset" : 0, "end_offset" : 3, "type" : "word", "position" : 3 }, { "token" : "ldh", "start_offset" : 0, "end_offset" : 3, "type" : "word", "position" : 4 } ] }
Support
Quality
Security
License
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Support
elasticsearch-analysis-pinyin has a medium active ecosystem.
It has 2567 star(s) with 520 fork(s). There are 111 watchers for this library.
It had no major release in the last 12 months.
There are 103 open issues and 157 have been closed. On average issues are closed in 55 days. There are 4 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of elasticsearch-analysis-pinyin is 5.2.2
Quality
elasticsearch-analysis-pinyin has 0 bugs and 0 code smells.
Security
elasticsearch-analysis-pinyin has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
elasticsearch-analysis-pinyin code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
elasticsearch-analysis-pinyin is licensed under the Apache-2.0 License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
Reuse
elasticsearch-analysis-pinyin releases are available to install and integrate.
Deployable package is available in Maven.
Build file is available. You can build the component from source.
Installation instructions are not available. Examples and code snippets are available.
Top functions reviewed by kandi - BETA
kandi has reviewed elasticsearch-analysis-pinyin and discovered the below as its top functions. This is intended to give you an instant insight into elasticsearch-analysis-pinyin implemented functionality, and help decide if they suit your requirements.
- Processes the current token
- Parse buffered text
- Add term to list
- Sets the term
- Increments the next token
- Returns a list with positive max length
- Reverse the pinyin text in the piny input string
- Read term
- Resets the iterator
- Provides a map of tokenizers to use
- Resets the writer
- Ends the offset
- Returns a map of token filters to use
- The analyzer
Get all kandi verified functions for this library.
elasticsearch-analysis-pinyin Key Features
No Key Features are available at this moment for elasticsearch-analysis-pinyin.
elasticsearch-analysis-pinyin Examples and Code Snippets
No Code Snippets are available at this moment for elasticsearch-analysis-pinyin.
Community Discussions
No Community Discussions are available at this moment for elasticsearch-analysis-pinyin.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install elasticsearch-analysis-pinyin
You can download it from GitHub, Maven.
You can use elasticsearch-analysis-pinyin like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the elasticsearch-analysis-pinyin component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
You can use elasticsearch-analysis-pinyin like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the elasticsearch-analysis-pinyin component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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