https://github.com/philferriere/mscsshiny
Test/demo web app for R packages like {mscsweblm4r} and {mscstexta4r} that interface with Microsoft Cognitive Services REST APIs.
https://github.com/philferriere/mscsshiny
Last synced: 5 months ago
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Test/demo web app for R packages like {mscsweblm4r} and {mscstexta4r} that interface with Microsoft Cognitive Services REST APIs.
- Host: GitHub
- URL: https://github.com/philferriere/mscsshiny
- Owner: philferriere
- License: other
- Created: 2016-05-18T16:51:04.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2016-06-20T15:46:15.000Z (over 9 years ago)
- Last Synced: 2025-03-31T16:58:46.634Z (6 months ago)
- Language: R
- Homepage:
- Size: 2.08 MB
- Stars: 7
- Watchers: 2
- Forks: 7
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE
Awesome Lists containing this project
README
---
title: Welcome to MSCSShiny!
author: "Phil Ferriere"
date: "June 2016"
geometry: margin=0cm
output:
html_document:
self_contained: true
highlight: tango
keep_md: yes
theme: cerulean
toc: yes
toc_depth: 4
toc_float: yes
---
```{r echo=FALSE}
library("knitr")
knitr::opts_chunk$set(comment = "#>", collapse = TRUE)
```
**MSCSShiny** is a test/demo application for R packages like `{mscstexta4r}` and `{mscsweblm4r}` that interface with the Microsoft Cognitive Services REST APIs.
> Demo: Try it live on [shinyapps.io](https://philferriere.shinyapps.io/MSCSShiny)!
## Microsoft Cognitive Services? What's that about?
[Microsoft Cognitive Services](https://www.microsoft.com/cognitive-services/en-us/documentation)
-- formerly known as Project Oxford -- are a set of large, diverse, truly awesome APIs, SDKs and services that developers can use to add [AI](https://en.wikipedia.org/wiki/Artificial_intelligence) features to their apps. Those features include emotion and video detection; facial, speech and vision recognition; as well as speech and [NLP](https://en.wikipedia.org/wiki/Natural_language_processing).
## MSCS Language Services
Our interest, at this stage, is limited to the exploration and evaluation of the NLP features of MSCS:
[](https://www.microsoft.com/cognitive-services/en-us/documentation)
As should be clear from the above, this subset itself isn't exactly small...
## Text Analytics API
The `{mscstexta4r}` package is a wrapper around the MSCS [Text Analytics REST API](https://www.microsoft.com/cognitive-services/en-us/text-analytics/documentation). This API offers a suite of text analytics web services - built with Azure Machine Learning - that can be used to analyze unstructured text. The API supports the following operations:
* Sentiment analysis - Is a sentence or document generally positive or negative?
* Topic detection - What's being discussed across a list of documents/reviews/articles?
* Language detection - What language is a document written in?
* Key talking points extraction - What's being discussed in a single document?
For more information about the `{mscstexta4r}` package (on [CRAN](https://cran.r-project.org/package=mscstexta4r), or on [GitHub](https://github.com/philferriere/mscstexta4r)), please check out the **Text Analytics API** tab at the top of this page.
## Web Language Model API
The `{mscsweblm4r}` R package exposes bindings for the MSCS [Web Language Model REST API](https://www.microsoft.com/cognitive-services/en-us/web-language-model-api/documentation). Per Microsoft's website, this API uses smoothed backoff N-gram language models (supporting Markov order up to 5) that were trained on four web-scale American English corpora collected by Bing (web page body, title, anchor and query). The following operations are supported:
* Calculate the joint probability that a sequence of words will appear together.
* Compute the conditional probability that a specific word will follow an existing sequence of words.
* Get the list of words (completions) most likely to follow a given sequence of words.
* Insert spaces into a string of words adjoined together without any spaces (hashtags, URLs, etc.).
* Retrieve the list of supported language models.
For additional information on the `{mscsweblm4r}` package (on [CRAN](https://cran.r-project.org/package=mscsweblm4r), or on [GitHub](https://github.com/philferriere/mscsweblm4r)), please click the **Web Language Model API** tab at the top of this page.
## Text Analytics Screenshots
### Sentiment analysis
### Topic detection
### Language detection
### Key talking points extraction
## Web Language Model Screenshots
### Supported web language models
### Words most likely to follow a sequence of words
### Break concatenated words into individual words
### Conditional probability that a particular word follows a given sequence of words
### Joint probability that a particular sequence of words appears together
## Credits
All Microsoft Cognitive Services components are Copyright (c) Microsoft.
Customized progress bar style, courtesy of [\@jackolney](https://github.com/jackolney).
## Meta
Please report any MSCSShiny issues or bugs [here](https://github.com/philferriere/mscsshiny/issues).
License: MIT + [file](./LICENSE)
This project is released with a [Contributor Code of Conduct](./CONDUCT.md). By
participating in this project, you agree to abide by its terms.