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stanbol-freeling | Stanbol Freeling is an external HTTP | Natural Language Processing library

 by   insideout10 Java Version: 20141218 License: AGPL-3.0

 by   insideout10 Java Version: 20141218 License: AGPL-3.0

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kandi X-RAY | stanbol-freeling Summary

stanbol-freeling is a Java library typically used in Artificial Intelligence, Natural Language Processing applications. stanbol-freeling has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.
Apache Stanbol Freeling integration.
Support
Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • stanbol-freeling has a low active ecosystem.
  • It has 21 star(s) with 6 fork(s). There are 10 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 2 open issues and 3 have been closed. On average issues are closed in 2 days. There are 1 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of stanbol-freeling is 20141218
stanbol-freeling Support
Best in #Natural Language Processing
Average in #Natural Language Processing
stanbol-freeling Support
Best in #Natural Language Processing
Average in #Natural Language Processing

quality kandi Quality

  • stanbol-freeling has 0 bugs and 0 code smells.
stanbol-freeling Quality
Best in #Natural Language Processing
Average in #Natural Language Processing
stanbol-freeling Quality
Best in #Natural Language Processing
Average in #Natural Language Processing

securitySecurity

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

license License

  • stanbol-freeling is licensed under the AGPL-3.0 License. This license is Strong Copyleft.
  • Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.
stanbol-freeling License
Best in #Natural Language Processing
Average in #Natural Language Processing
stanbol-freeling License
Best in #Natural Language Processing
Average in #Natural Language Processing

buildReuse

  • stanbol-freeling releases are available to install and integrate.
  • Build file is available. You can build the component from source.
  • Installation instructions are not available. Examples and code snippets are available.
  • It has 4039 lines of code, 190 functions and 33 files.
  • It has high code complexity. Code complexity directly impacts maintainability of the code.
stanbol-freeling Reuse
Best in #Natural Language Processing
Average in #Natural Language Processing
stanbol-freeling Reuse
Best in #Natural Language Processing
Average in #Natural Language Processing
Top functions reviewed by kandi - BETA

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

  • Analyze a blob .
    • Create a freeling analyzer object .
      • Read properties .
        • Main entry point for the Freeling instance .
          • Checks whether the given type is acceptable .
            • Make sure that the native library exists .
              • Detects languages in the given text .
                • Add common punctuation tags .
                  • Build Language Identifier .
                    • Method to create a Language Identification resource .

                      Get all kandi verified functions for this library.

                      Get all kandi verified functions for this library.

                      stanbol-freeling Key Features

                      there might be issues according on which version of boost gets installed and its location (open an issue, we’ll try to help).

                      the install-sh file might not have the required permissions (change with chmod 755 install-sh)

                      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 stanbol-freeling

                      You can download it from GitHub.
                      You can use stanbol-freeling 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 stanbol-freeling 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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