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Text Analysis of books using C++

A text analysis application that processes the text file of books gathered with XPDFREADER to do analysis on.
Explore the docs »

View Demo · Report Bug · Request Feature

Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgments

About The Project

Version one the application will take in a text file that is supplied in the inputs folder, from there it will execute the algorithm to scan and process the textfile using multithreading and output to an output folder as well as efficiency statistics. With the change in the number of threads you can get statistics on the efficiency of # of threads. https://machinelearningmastery.com/gentle-introduction-bag-words-model/ Model to implement

(back to top)

Built With

(back to top)

Getting Started

This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.

Prerequisites

  • C++17

Dependencies

  • Standard Library

Installation

  1. Upon Version 1's completion need to update installation guide. As of right now git clone and branch off to work on it!

(back to top)

Usage

Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.

For more examples, please refer to the Documentation

(back to top)

Roadmap

  • [] Basic Functionality
    • [] Optimize any potential algorithms(search/sort)
  • [] Documentation
    • Readme
    • [] Doxygen
    • [] Performance Monitoring(Google Benchmark)
  • [] User Interface
    • [] Interactibility with the application without programming selecting files
  • [] Report
    • Word Count/Frequency
    • [] Sentiment Analysis
    • [] General Stats
  • [] Automation
    • [] Ability to send multiple files for analysis(Batch Order)
    • [] Ability to analyze same file multiple configurations(single vs multi threading)
  • [] Futures
    • [] Analyze different file types
    • [] Analysis of none books such as tweets/articles

See the open issues for a full list of proposed features (and known issues).

(back to top)

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

(back to top)

License

Distributed under the MIT License. See license.md for more information.

(back to top)

Contact

John Parkhurst - jparkhurst120@gmail.com

Project Link: https://github.com/John4064/text-analysis

(back to top)

Acknowledgments

(back to top)

About

Using text analysis of pdfs converted to text using xpdf pdftotext

Resources

Readme
MIT license
Activity

Stars

3 stars

Watchers

1 watching

Forks

1 fork
Report repository

Releases

Packages

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all 
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})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
Repository files navigation
ContributorsForksStargazersIssuesMIT LicenseLinkedIn

Logo
Text Analysis of books using C++

A text analysis application that processes the text file of books gathered with XPDFREADER to do analysis on.

Explore the docs »

View Demo
·
Report Bug
·
Request Feature
Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgments
About The Project
Version one the application will take in a text file that is supplied in the inputs folder, from there it will execute the algorithm to scan and process the textfile using multithreading and output to an output folder as well as efficiency statistics. With the change in the number of threads you can get statistics on the efficiency of # of threads.
https://machinelearningmastery.com/gentle-introduction-bag-words-model/
Model to implement

(back to top)
Built With
(back to top)
Getting Started
This is an example of how you may give instructions on setting up your project locally.
To get a local copy up and running follow these simple example steps.
Prerequisites
  • C++17
Dependencies
  • Standard Library
Installation
  1. Upon Version 1's completion need to update installation guide. As of right now git clone and branch off to work on it!
(back to top)
Usage
Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.
For more examples, please refer to the Documentation
(back to top)
Roadmap
  • [] Basic Functionality

    • [] Optimize any potential algorithms(search/sort)
  • [] Documentation

    •  Readme
    • [] Doxygen
    • [] Performance Monitoring(Google Benchmark)
  • [] User Interface

    • [] Interactibility with the application without programming selecting files
  • [] Report

    •  Word Count/Frequency
    • [] Sentiment Analysis
    • [] General Stats
  • [] Automation

    • [] Ability to send multiple files for analysis(Batch Order)
    • [] Ability to analyze same file multiple configurations(single vs multi threading)
  • [] Futures

    • [] Analyze different file types
    • [] Analysis of none books such as tweets/articles
See the open issues for a full list of proposed features (and known issues).
(back to top)
Contributing
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!
  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request
(back to top)
License
Distributed under the MIT License. See license.md for more information.
(back to top)
Contact
John Parkhurst - jparkhurst120@gmail.com
Project Link: https://github.com/John4064/text-analysis
(back to top)
Acknowledgments
(back to top)
About
Using text analysis of pdfs converted to text using xpdf pdftotext
Resources
Readme
MIT license
Activity
Stars
3 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Force GitHub README to respect dark mode
(function() {
var style = document.createElement('style');
style.textContent = '
.markdown-body {
color-scheme: dark light;
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
ContributorsForksStargazersIssuesMIT LicenseLinkedIn

Logo
Text Analysis of books using C++

A text analysis application that processes the text file of books gathered with XPDFREADER to do analysis on.

Explore the docs »

View Demo
·
Report Bug
·
Request Feature
Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgments
About The Project
Version one the application will take in a text file that is supplied in the inputs folder, from there it will execute the algorithm to scan and process the textfile using multithreading and output to an output folder as well as efficiency statistics. With the change in the number of threads you can get statistics on the efficiency of # of threads.
https://machinelearningmastery.com/gentle-introduction-bag-words-model/
Model to implement

(back to top)
Built With
(back to top)
Getting Started
This is an example of how you may give instructions on setting up your project locally.
To get a local copy up and running follow these simple example steps.
Prerequisites
  • C++17
Dependencies
  • Standard Library
Installation
  1. Upon Version 1's completion need to update installation guide. As of right now git clone and branch off to work on it!
(back to top)
Usage
Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.
For more examples, please refer to the Documentation
(back to top)
Roadmap
  • [] Basic Functionality

    • [] Optimize any potential algorithms(search/sort)
  • [] Documentation

    •  Readme
    • [] Doxygen
    • [] Performance Monitoring(Google Benchmark)
  • [] User Interface

    • [] Interactibility with the application without programming selecting files
  • [] Report

    •  Word Count/Frequency
    • [] Sentiment Analysis
    • [] General Stats
  • [] Automation

    • [] Ability to send multiple files for analysis(Batch Order)
    • [] Ability to analyze same file multiple configurations(single vs multi threading)
  • [] Futures

    • [] Analyze different file types
    • [] Analysis of none books such as tweets/articles
See the open issues for a full list of proposed features (and known issues).
(back to top)
Contributing
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!
  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request
(back to top)
License
Distributed under the MIT License. See license.md for more information.
(back to top)
Contact
John Parkhurst - jparkhurst120@gmail.com
Project Link: https://github.com/John4064/text-analysis
(back to top)
Acknowledgments
(back to top)
About
Using text analysis of pdfs converted to text using xpdf pdftotext
Resources
Readme
MIT license
Activity
Stars
3 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
(function() {
var ref = document.referrer;
var terms = [];
if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {
var url = new URL(ref);
var q = url.searchParams.get('q') || url.searchParams.get('p');
if (q) {
terms = q.split(/\s+/).filter(function(t) { return t.length > 2; });
}
}
if (terms.length === 0) return;
var style = document.createElement('style');
style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';
document.head.appendChild(style);
function highlight(node) {
if (node.nodeType === 3) { // text node
var text = node.textContent;
var found = false;
terms.forEach(function(term) {
var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi');
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if (!skipTags.includes(node.tagName)) {
Array.from(node.childNodes).forEach(highlight);
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}
}
highlight(document.body);
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var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1 || node.nodeType === 3) highlight(node);
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
ContributorsForksStargazersIssuesMIT LicenseLinkedIn

Logo
Text Analysis of books using C++

A text analysis application that processes the text file of books gathered with XPDFREADER to do analysis on.

Explore the docs »

View Demo
·
Report Bug
·
Request Feature
Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgments
About The Project
Version one the application will take in a text file that is supplied in the inputs folder, from there it will execute the algorithm to scan and process the textfile using multithreading and output to an output folder as well as efficiency statistics. With the change in the number of threads you can get statistics on the efficiency of # of threads.
https://machinelearningmastery.com/gentle-introduction-bag-words-model/
Model to implement

(back to top)
Built With
(back to top)
Getting Started
This is an example of how you may give instructions on setting up your project locally.
To get a local copy up and running follow these simple example steps.
Prerequisites
  • C++17
Dependencies
  • Standard Library
Installation
  1. Upon Version 1's completion need to update installation guide. As of right now git clone and branch off to work on it!
(back to top)
Usage
Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.
For more examples, please refer to the Documentation
(back to top)
Roadmap
  • [] Basic Functionality

    • [] Optimize any potential algorithms(search/sort)
  • [] Documentation

    •  Readme
    • [] Doxygen
    • [] Performance Monitoring(Google Benchmark)
  • [] User Interface

    • [] Interactibility with the application without programming selecting files
  • [] Report

    •  Word Count/Frequency
    • [] Sentiment Analysis
    • [] General Stats
  • [] Automation

    • [] Ability to send multiple files for analysis(Batch Order)
    • [] Ability to analyze same file multiple configurations(single vs multi threading)
  • [] Futures

    • [] Analyze different file types
    • [] Analysis of none books such as tweets/articles
See the open issues for a full list of proposed features (and known issues).
(back to top)
Contributing
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!
  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request
(back to top)
License
Distributed under the MIT License. See license.md for more information.
(back to top)
Contact
John Parkhurst - jparkhurst120@gmail.com
Project Link: https://github.com/John4064/text-analysis
(back to top)
Acknowledgments
(back to top)
About
Using text analysis of pdfs converted to text using xpdf pdftotext
Resources
Readme
MIT license
Activity
Stars
3 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
(function() {
var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
u.searchParams.delete(p);
changed = true;
}
});
return changed ? u.toString() : url;
} catch (e) {
return url;
}
}
function cleanLinks() {
document.querySelectorAll('a[href]').forEach(function(a) {
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if (clean !== a.href) a.href = clean;
});
}
cleanLinks();
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1) {
if (node.tagName === 'A') cleanLinks();
node.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
ContributorsForksStargazersIssuesMIT LicenseLinkedIn

Logo
Text Analysis of books using C++

A text analysis application that processes the text file of books gathered with XPDFREADER to do analysis on.

Explore the docs »

View Demo
·
Report Bug
·
Request Feature
Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgments
About The Project
Version one the application will take in a text file that is supplied in the inputs folder, from there it will execute the algorithm to scan and process the textfile using multithreading and output to an output folder as well as efficiency statistics. With the change in the number of threads you can get statistics on the efficiency of # of threads.
https://machinelearningmastery.com/gentle-introduction-bag-words-model/
Model to implement

(back to top)
Built With
(back to top)
Getting Started
This is an example of how you may give instructions on setting up your project locally.
To get a local copy up and running follow these simple example steps.
Prerequisites
  • C++17
Dependencies
  • Standard Library
Installation
  1. Upon Version 1's completion need to update installation guide. As of right now git clone and branch off to work on it!
(back to top)
Usage
Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.
For more examples, please refer to the Documentation
(back to top)
Roadmap
  • [] Basic Functionality

    • [] Optimize any potential algorithms(search/sort)
  • [] Documentation

    •  Readme
    • [] Doxygen
    • [] Performance Monitoring(Google Benchmark)
  • [] User Interface

    • [] Interactibility with the application without programming selecting files
  • [] Report

    •  Word Count/Frequency
    • [] Sentiment Analysis
    • [] General Stats
  • [] Automation

    • [] Ability to send multiple files for analysis(Batch Order)
    • [] Ability to analyze same file multiple configurations(single vs multi threading)
  • [] Futures

    • [] Analyze different file types
    • [] Analysis of none books such as tweets/articles
See the open issues for a full list of proposed features (and known issues).
(back to top)
Contributing
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!
  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request
(back to top)
License
Distributed under the MIT License. See license.md for more information.
(back to top)
Contact
John Parkhurst - jparkhurst120@gmail.com
Project Link: https://github.com/John4064/text-analysis
(back to top)
Acknowledgments
(back to top)
About
Using text analysis of pdfs converted to text using xpdf pdftotext
Resources
Readme
MIT license
Activity
Stars
3 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
ContributorsForksStargazersIssuesMIT LicenseLinkedIn

Logo
Text Analysis of books using C++

A text analysis application that processes the text file of books gathered with XPDFREADER to do analysis on.

Explore the docs »

View Demo
·
Report Bug
·
Request Feature
Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgments
About The Project
Version one the application will take in a text file that is supplied in the inputs folder, from there it will execute the algorithm to scan and process the textfile using multithreading and output to an output folder as well as efficiency statistics. With the change in the number of threads you can get statistics on the efficiency of # of threads.
https://machinelearningmastery.com/gentle-introduction-bag-words-model/
Model to implement

(back to top)
Built With
(back to top)
Getting Started
This is an example of how you may give instructions on setting up your project locally.
To get a local copy up and running follow these simple example steps.
Prerequisites
  • C++17
Dependencies
  • Standard Library
Installation
  1. Upon Version 1's completion need to update installation guide. As of right now git clone and branch off to work on it!
(back to top)
Usage
Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.
For more examples, please refer to the Documentation
(back to top)
Roadmap
  • [] Basic Functionality

    • [] Optimize any potential algorithms(search/sort)
  • [] Documentation

    •  Readme
    • [] Doxygen
    • [] Performance Monitoring(Google Benchmark)
  • [] User Interface

    • [] Interactibility with the application without programming selecting files
  • [] Report

    •  Word Count/Frequency
    • [] Sentiment Analysis
    • [] General Stats
  • [] Automation

    • [] Ability to send multiple files for analysis(Batch Order)
    • [] Ability to analyze same file multiple configurations(single vs multi threading)
  • [] Futures

    • [] Analyze different file types
    • [] Analysis of none books such as tweets/articles
See the open issues for a full list of proposed features (and known issues).
(back to top)
Contributing
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!
  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request
(back to top)
License
Distributed under the MIT License. See license.md for more information.
(back to top)
Contact
John Parkhurst - jparkhurst120@gmail.com
Project Link: https://github.com/John4064/text-analysis
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Acknowledgments
(back to top)
About
Using text analysis of pdfs converted to text using xpdf pdftotext
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Readme
MIT license
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3 stars
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1 watching
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1 fork
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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Text Analysis of books using C++

A text analysis application that processes the text file of books gathered with XPDFREADER to do analysis on.

Explore the docs »

View Demo
·
Report Bug
·
Request Feature
Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgments
About The Project
Version one the application will take in a text file that is supplied in the inputs folder, from there it will execute the algorithm to scan and process the textfile using multithreading and output to an output folder as well as efficiency statistics. With the change in the number of threads you can get statistics on the efficiency of # of threads.
https://machinelearningmastery.com/gentle-introduction-bag-words-model/
Model to implement

(back to top)
Built With
(back to top)
Getting Started
This is an example of how you may give instructions on setting up your project locally.
To get a local copy up and running follow these simple example steps.
Prerequisites
  • C++17
Dependencies
  • Standard Library
Installation
  1. Upon Version 1's completion need to update installation guide. As of right now git clone and branch off to work on it!
(back to top)
Usage
Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.
For more examples, please refer to the Documentation
(back to top)
Roadmap
  • [] Basic Functionality

    • [] Optimize any potential algorithms(search/sort)
  • [] Documentation

    •  Readme
    • [] Doxygen
    • [] Performance Monitoring(Google Benchmark)
  • [] User Interface

    • [] Interactibility with the application without programming selecting files
  • [] Report

    •  Word Count/Frequency
    • [] Sentiment Analysis
    • [] General Stats
  • [] Automation

    • [] Ability to send multiple files for analysis(Batch Order)
    • [] Ability to analyze same file multiple configurations(single vs multi threading)
  • [] Futures

    • [] Analyze different file types
    • [] Analysis of none books such as tweets/articles
See the open issues for a full list of proposed features (and known issues).
(back to top)
Contributing
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!
  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request
(back to top)
License
Distributed under the MIT License. See license.md for more information.
(back to top)
Contact
John Parkhurst - jparkhurst120@gmail.com
Project Link: https://github.com/John4064/text-analysis
(back to top)
Acknowledgments
(back to top)
About
Using text analysis of pdfs converted to text using xpdf pdftotext
Resources
Readme
MIT license
Activity
Stars
3 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

Skip to content
BranchesTags
Repository files navigation
ContributorsForksStargazersIssuesMIT LicenseLinkedIn

Logo
Text Analysis of books using C++

A text analysis application that processes the text file of books gathered with XPDFREADER to do analysis on.

Explore the docs »

View Demo
·
Report Bug
·
Request Feature
Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgments
About The Project
Version one the application will take in a text file that is supplied in the inputs folder, from there it will execute the algorithm to scan and process the textfile using multithreading and output to an output folder as well as efficiency statistics. With the change in the number of threads you can get statistics on the efficiency of # of threads.
https://machinelearningmastery.com/gentle-introduction-bag-words-model/
Model to implement

(back to top)
Built With
(back to top)
Getting Started
This is an example of how you may give instructions on setting up your project locally.
To get a local copy up and running follow these simple example steps.
Prerequisites
  • C++17
Dependencies
  • Standard Library
Installation
  1. Upon Version 1's completion need to update installation guide. As of right now git clone and branch off to work on it!
(back to top)
Usage
Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.
For more examples, please refer to the Documentation
(back to top)
Roadmap
  • [] Basic Functionality

    • [] Optimize any potential algorithms(search/sort)
  • [] Documentation

    •  Readme
    • [] Doxygen
    • [] Performance Monitoring(Google Benchmark)
  • [] User Interface

    • [] Interactibility with the application without programming selecting files
  • [] Report

    •  Word Count/Frequency
    • [] Sentiment Analysis
    • [] General Stats
  • [] Automation

    • [] Ability to send multiple files for analysis(Batch Order)
    • [] Ability to analyze same file multiple configurations(single vs multi threading)
  • [] Futures

    • [] Analyze different file types
    • [] Analysis of none books such as tweets/articles
See the open issues for a full list of proposed features (and known issues).
(back to top)
Contributing
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!
  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request
(back to top)
License
Distributed under the MIT License. See license.md for more information.
(back to top)
Contact
John Parkhurst - jparkhurst120@gmail.com
Project Link: https://github.com/John4064/text-analysis
(back to top)
Acknowledgments
(back to top)
About
Using text analysis of pdfs converted to text using xpdf pdftotext
Resources
Readme
MIT license
Activity
Stars
3 stars
Watchers
1 watching
Forks
1 fork
Report repository
Releases
Packages
Used by
Contributors
Languages