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elasticsearch-skroutz-greekstemmer | Greek Stemmer for elasticsearch | Natural Language Processing library

 by   skroutz Java Version: 7.7.0.4 License: No License

 by   skroutz Java Version: 7.7.0.4 License: No License

kandi X-RAY | elasticsearch-skroutz-greekstemmer Summary

elasticsearch-skroutz-greekstemmer is a Java library typically used in Artificial Intelligence, Natural Language Processing applications. elasticsearch-skroutz-greekstemmer has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub, Maven.
This plugin is based on the GreekStemmer that is included in Apache Lucene. Lucene’s GreekStemmer is created according to Development of a Stemmer for the Greek Language of Georgios Ntaias. This thesis mentions that 166 suffixes are recognized in the Greek language. However, only 158 were captured by this stemmer, because the addition of the remainning suffixes would reduce the precision of the stemmer on the word-sets that were used for its evaluation.
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Support
Quality
Quality
Security
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kandi-support Support

  • elasticsearch-skroutz-greekstemmer has a low active ecosystem.
  • It has 64 star(s) with 31 fork(s). There are 68 watchers for this library.
  • There were 1 major release(s) in the last 12 months.
  • There are 7 open issues and 8 have been closed. On average issues are closed in 101 days. There are 3 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of elasticsearch-skroutz-greekstemmer is 7.7.0.4
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-skroutz-greekstemmer has 0 bugs and 46 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-skroutz-greekstemmer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • elasticsearch-skroutz-greekstemmer code analysis shows 0 unresolved vulnerabilities.
  • There are 0 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-skroutz-greekstemmer 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-skroutz-greekstemmer 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 1295 lines of code, 38 functions and 9 files.
  • It has high 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-skroutz-greekstemmer and discovered the below as its top functions. This is intended to give you an instant insight into elasticsearch-skroutz-greekstemmer implemented functionality, and help decide if they suit your requirements.

  • check the rule 2
    • get the position of the start of the specified string
      • find the first rule in a string
        • Increments the token .
          • Gets the token filters .
            • Creates a token stream from a token stream .

              Get all kandi verified functions for this library.

              Get all kandi verified functions for this library.

              elasticsearch-skroutz-greekstemmer Key Features

              Greek Stemmer for elasticsearch

              elasticsearch-skroutz-greekstemmer Examples and Code Snippets

              Community Discussions

              Trending Discussions on Natural Language Processing
              • number of matches for keywords in specified categories
              • Apple's Natural Language API returns unexpected results
              • Tokenize text but keep compund hyphenated words together
              • Create new boolean fields based on specific bigrams appearing in a tokenized pandas dataframe
              • ModuleNotFoundError: No module named 'milvus'
              • 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?
              • Mapping values from a dictionary's list to a string in Python
              • What are differences between AutoModelForSequenceClassification vs AutoModel
              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-skroutz-greekstemmer

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

              • gh repo clone skroutz/elasticsearch-skroutz-greekstemmer

              • git@github.com:skroutz/elasticsearch-skroutz-greekstemmer.git

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