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elasticsearch-analysis-decompound | Decompounding Plugin for Elasticsearch | Natural Language Processing library

 by   jprante Java Version: 6.3.2.0 License: GPL-2.0

 by   jprante Java Version: 6.3.2.0 License: GPL-2.0

kandi X-RAY | elasticsearch-analysis-decompound Summary

elasticsearch-analysis-decompound is a Java library typically used in Artificial Intelligence, Natural Language Processing applications. elasticsearch-analysis-decompound has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. However elasticsearch-analysis-decompound has 2 bugs. You can download it from GitHub, Maven.
Decompounding Plugin for Elasticsearch
Support
Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • elasticsearch-analysis-decompound has a low active ecosystem.
  • It has 88 star(s) with 34 fork(s). There are 17 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 16 open issues and 18 have been closed. On average issues are closed in 74 days. There are 2 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of elasticsearch-analysis-decompound is 6.3.2.0
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-decompound has 2 bugs (0 blocker, 1 critical, 1 major, 0 minor) and 42 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-decompound has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • elasticsearch-analysis-decompound 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-analysis-decompound is licensed under the GPL-2.0 License. This license is Strong Copyleft.
  • Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.
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-decompound 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 2401 lines of code, 131 functions and 16 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-analysis-decompound and discovered the below as its top functions. This is intended to give you an instant insight into elasticsearch-analysis-decompound implemented functionality, and help decide if they suit your requirements.

  • Decompose a word
    • get a node for a word
      • Build an object tree .
        • Increments the next token .
          • Reduce the word to the base form .
            • Creates a Decompounder from the given settings .
              • Returns true if this filter is equal to the given one .
                • Override this method to add extra token filters to the user .
                  • Creates a token stream .
                    • Set children of this node .

                      Get all kandi verified functions for this library.

                      Get all kandi verified functions for this library.

                      elasticsearch-analysis-decompound Key Features

                      Decompounding Plugin for Elasticsearch

                      elasticsearch-analysis-decompound Examples and Code Snippets

                      See all related 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-analysis-decompound

                      Do not forget to restart the node after installing.
                      Do not forget to restart the node after installing.

                      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/jprante/elasticsearch-analysis-decompound.git

                      • gh repo clone jprante/elasticsearch-analysis-decompound

                      • git@github.com:jprante/elasticsearch-analysis-decompound.git

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