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elasticsearch-analysis-turkishstemmer | ElasticSearch analysis plugin providing Turkish stemming | Natural Language Processing library

 by   skroutz Java Version: 7.7.0.2 License: No License

 by   skroutz Java Version: 7.7.0.2 License: No License

kandi X-RAY | elasticsearch-analysis-turkishstemmer Summary

elasticsearch-analysis-turkishstemmer is a Java library typically used in Artificial Intelligence, Natural Language Processing applications. elasticsearch-analysis-turkishstemmer has no vulnerabilities, it has build file available and it has low support. However elasticsearch-analysis-turkishstemmer has 1 bugs. You can download it from GitHub, Maven.
Turkish is an agglutinative language and has a very rich morphological stucture. In Turkish, you can form many different words from a single stem by appending a sequence of suffixes. For example The word "doktoruymuşsunuz" means "You had been the doctor of him". The stem of the word is "doktor" and it takes three different suffixes -sU, -ymUş, and -sUnUz. Words are usually composed of a stem and of at least two or three affixes appended to it. We can analyze noun suffixes in Turkish in two groups. Noun suffixes (eg. "doktor-um" meaning "my doctor") and nominal verb suffixes (eg. "doktor-dur" meaning ‘is a doctor’). The words ending with nominal verb suffixes can be used as verbs in sentences. There are over thirty different suffixes classified in these two general groups of suffixes. In Turkish, the suffixes are affixed to the stem according to definite ordering rules.
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kandi-support Support

  • elasticsearch-analysis-turkishstemmer has a low active ecosystem.
  • It has 69 star(s) with 15 fork(s). There are 78 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 2 open issues and 4 have been closed. On average issues are closed in 6 days. There are no pull requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of elasticsearch-analysis-turkishstemmer is 7.7.0.2
This Library - Support
Best in #Natural Language Processing
Average in #Natural Language Processing
This Library - Support
Best in #Natural Language Processing
Average in #Natural Language Processing

quality kandi Quality

  • elasticsearch-analysis-turkishstemmer has 1 bugs (1 blocker, 0 critical, 0 major, 0 minor) and 77 code smells.
This Library - Quality
Best in #Natural Language Processing
Average in #Natural Language Processing
This Library - Quality
Best in #Natural Language Processing
Average in #Natural Language Processing

securitySecurity

  • elasticsearch-analysis-turkishstemmer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • elasticsearch-analysis-turkishstemmer code analysis shows 0 unresolved vulnerabilities.
  • There are 1 security hotspots that need review.
This Library - Security
Best in #Natural Language Processing
Average in #Natural Language Processing
This Library - Security
Best in #Natural Language Processing
Average in #Natural Language Processing

license License

  • elasticsearch-analysis-turkishstemmer does not have a standard license declared.
  • Check the repository for any license declaration and review the terms closely.
  • Without a license, all rights are reserved, and you cannot use the library in your applications.
This Library - License
Best in #Natural Language Processing
Average in #Natural Language Processing
This Library - License
Best in #Natural Language Processing
Average in #Natural Language Processing

buildReuse

  • elasticsearch-analysis-turkishstemmer releases are not available. You will need to build from source code and install.
  • Deployable package is available in Maven.
  • Build file is available. You can build the component from source.
  • Installation instructions, examples and code snippets are available.
  • It has 2050 lines of code, 138 functions and 26 files.
  • It has medium code complexity. Code complexity directly impacts maintainability of the code.
This Library - Reuse
Best in #Natural Language Processing
Average in #Natural Language Processing
This Library - Reuse
Best in #Natural Language Processing
Average in #Natural Language Processing
Top functions reviewed by kandi - BETA

kandi has reviewed elasticsearch-analysis-turkishstemmer and discovered the below as its top functions. This is intended to give you an instant insight into elasticsearch-analysis-turkishstemmer implemented functionality, and help decide if they suit your requirements.

  • Stores the word in a string .
    • SuffixStripper .
      • Parses the exceptions file .
        • Parse the vowel exceptions set .
          • Increments the current token .
            • Returns a list of similar transitions .
              • Returns a string representation of this state .
                • Gets the token filters .

                  Get all kandi verified functions for this library.

                  Get all kandi verified functions for this library.

                  elasticsearch-analysis-turkishstemmer Key Features

                  ElasticSearch analysis plugin providing Turkish stemming functionality

                  elasticsearch-analysis-turkishstemmer Examples and Code Snippets

                  See all related Code Snippets

                  Community Discussions

                  Trending Discussions on Natural Language Processing
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                  • Which model/technique to use for specific sentence extraction?
                  • Assigning True/False if a token is present in a data-frame
                  • How to calculate perplexity of a sentence using huggingface masked language models?
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                  Trending Discussions on Natural Language Processing

                  QUESTION

                  number of matches for keywords in specified categories

                  Asked 2022-Apr-14 at 13:32

                  For a large scale text analysis problem, I have a data frame containing words that fall into different categories, and a data frame containing a column with strings and (empty) counting columns for each category. I now want to take each individual string, check which of the defined words appear, and count them within the appropriate category.

                  As a simplified example, given the two data frames below, i want to count how many of each animal type appear in the text cell.

                  df_texts <- tibble(
                    text=c("the ape and the fox", "the tortoise and the hare", "the owl and the the 
                    grasshopper"),
                    mammals=NA,
                    reptiles=NA,
                    birds=NA,
                    insects=NA
                  )
                  
                  df_animals <- tibble(animals=c("ape", "fox", "tortoise", "hare", "owl", "grasshopper"),
                             type=c("mammal", "mammal", "reptile", "mammal", "bird", "insect"))
                  

                  So my desired result would be:

                  df_result <- tibble(
                    text=c("the ape and the fox", "the tortoise and the hare", "the owl and the the 
                    grasshopper"),
                    mammals=c(2,1,0),
                    reptiles=c(0,1,0),
                    birds=c(0,0,1),
                    insects=c(0,0,1)
                  )
                  

                  Is there a straightforward way to achieve this keyword-matching-and-counting that would be applicable to a much larger dataset?

                  Thanks in advance!

                  ANSWER

                  Answered 2022-Apr-14 at 13:32

                  Here's a way do to it in the tidyverse. First look at whether strings in df_texts$text contain animals, then count them and sum by text and type.

                  library(tidyverse)
                  
                  cbind(df_texts[, 1], sapply(df_animals$animals, grepl, df_texts$text)) %>% 
                    pivot_longer(-text, names_to = "animals") %>% 
                    left_join(df_animals) %>% 
                    group_by(text, type) %>% 
                    summarise(sum = sum(value)) %>% 
                    pivot_wider(id_cols = text, names_from = type, values_from = sum)
                  
                    text                                   bird insect mammal reptile
                    <chr>                                 <int>  <int>  <int>   <int>
                  1 "the ape and the fox"                     0      0      2       0
                  2 "the owl and the the \n  grasshopper"     1      0      0       0
                  3 "the tortoise and the hare"               0      0      1       1
                  

                  To account for the several occurrences per text:

                  cbind(df_texts[, 1], t(sapply(df_texts$text, str_count, df_animals$animals, USE.NAMES = F))) %>% 
                    setNames(c("text", df_animals$animals)) %>% 
                    pivot_longer(-text, names_to = "animals") %>% 
                    left_join(df_animals) %>% 
                    group_by(text, type) %>% 
                    summarise(sum = sum(value)) %>% 
                    pivot_wider(id_cols = text, names_from = type, values_from = sum)
                  

                  Source https://stackoverflow.com/questions/71871613

                  Community Discussions, Code Snippets contain sources that include Stack Exchange Network

                  Vulnerabilities

                  No vulnerabilities reported

                  Install elasticsearch-analysis-turkishstemmer

                  To list all plugins in current installation:.

                  Support

                  Fork it ( http://github.com/<my-github-username>/elasticsearch-analysis-turkishstemmer/fork )Create your feature branch (git checkout -b my-new-feature)Commit your changes (git commit -am 'Add some feature')Push to the branch (git push origin my-new-feature)Create new Pull Request

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                  Install
                  Clone
                  • https://github.com/skroutz/elasticsearch-analysis-turkishstemmer.git

                  • gh repo clone skroutz/elasticsearch-analysis-turkishstemmer

                  • git@github.com:skroutz/elasticsearch-analysis-turkishstemmer.git

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