topicmodeling | central repository for literature on and applications | Topic Modeling library

 by   RFJHaans JavaScript Version: Current License: No License

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kandi X-RAY | topicmodeling Summary

kandi X-RAY | topicmodeling Summary

topicmodeling is a JavaScript library typically used in Artificial Intelligence, Topic Modeling, Arduino, JavaFX applications. topicmodeling has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

This is the central repository for literature on and applications of the topic modeling methodology. This page was specifically designed for the professional development workshop (PDW) on topic modeling that have taken place at the 2017 and 2018 iterations of the annual Academy of Management Meeting, but is open to anyone interested.
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              topicmodeling has a low active ecosystem.
              It has 10 star(s) with 2 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              topicmodeling has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of topicmodeling is current.

            kandi-Quality Quality

              topicmodeling has no bugs reported.

            kandi-Security Security

              topicmodeling has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              topicmodeling does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              topicmodeling releases are not available. You will need to build from source code and install.
              Installation instructions are not available. Examples and code snippets are available.

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            topicmodeling Key Features

            No Key Features are available at this moment for topicmodeling.

            topicmodeling Examples and Code Snippets

            No Code Snippets are available at this moment for topicmodeling.

            Community Discussions

            Trending Discussions on topicmodeling

            comprehend.start_topics_detection_job Fails with Silent Error?
            Topic Modeling: graphical representation of words with the greatest differences between two topics
            Error: No tidy method for objects of class LDA_VEM§

            QUESTION

            comprehend.start_topics_detection_job Fails with Silent Error?
            Asked 2020-Apr-07 at 05:03

            I have Amazon sample code for running comprehend.start_topics_detection_job. Here is the code with the variables filled in for my job:

            ...

            ANSWER

            Answered 2019-May-01 at 08:07

            It turns out that there was nothing wrong with the call to comprehend.describe_topics_detection_job -- it was just returning, in describe_result, something that could not be json serialized, so json.dumps(describe_result)) was throwing an error.

            Source https://stackoverflow.com/questions/55854377

            QUESTION

            Topic Modeling: graphical representation of words with the greatest differences between two topics
            Asked 2020-Mar-02 at 21:36

            In Text Mining with R, methods for unsupervised classification of documents, such as blog posts or news articles, are introduced. This is work for topic modeling. I'm running the codes enclosed in this link, but I do not know how obtain Figure 6.3, "Words with the greatest difference in beta between topic 2 and topic 1".

            Any suggestions please?

            ...

            ANSWER

            Answered 2020-Mar-02 at 21:36

            This book has source available, you can just click the edit button and be taken to the GitHub project with the current page to edit. Just navigate to the chapter that you need (a Rmd file) and look for the text closest to the image.

            Thankfully this image was also made with R, so you can just check: here

            Posting for completeness:

            Source https://stackoverflow.com/questions/60496730

            QUESTION

            Error: No tidy method for objects of class LDA_VEM§
            Asked 2018-Dec-12 at 04:01

            I am literally following the steps as presented in chapter 6 of the "Text Mining in R: a Tidy Approach" book. See: https://www.tidytextmining.com/topicmodeling.html

            ...

            ANSWER

            Answered 2018-Dec-11 at 16:43

            You need to first tidy the AssociatedPress data. Like this:

            Source https://stackoverflow.com/questions/53728532

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

            Vulnerabilities

            No vulnerabilities reported

            Install topicmodeling

            You can download it from GitHub.

            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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