How can you use MeaningCloud?

APIs

As we have mentioned before, APIs provide an incredible amount of flexibility. If your data is already included in a workflow or pipeline and you just want to add additional information to it in the form of insights extracted from it, this is the perfect option for you. Each one of our APIs provide a specific type of text analysis, so by combining several of them you can customize the information to extract.

• You can check all our available APIs in their dashboard.
• For each one of the APIs we provide three sections: extensive technical documentation, some developer tools and a test console.
  • In the technical documentation you will find all the information you may need about the parameters of the API, its response, as well as some examples. For instance, this is the technical documentation for the Sentiment Analysis API.
  • In the developer tools section, you will find simple examples of clients for that API in as many as 9 programming languages using different libraries. These are the clients for the Deep Categorization API.
  • The test console enables you to test quickly any text, URL or document you want with any combination of the input parameters of the API. It’s extremely useful when you are starting to work with MeaningCloud as you can see the response produced for any given input. This is the test console for the Topics Extraction API.
• For those of you looking to quickly integrate MeaningCloud into your application, we’ve published in our GitHub account SDKs in three of the most popular languages: Java, Python and PHP. This kits will allow you to add easily a framework to your application where you will be able to include MeaningCloud’s analysis.
• If you are already a RapidAPI user, you can use MeaningCloud from there too!

Integrations

Our integrations provide access to the MeaningCloud analyses from different platforms, making them more accessible and removing the need for coding. Your choice of integration may depend on your needs or the tools you are working on:

• Spreadsheets: one of the most common ways of working with data. There are two options:
  • Excel add-in: fast to install, easy to use and our most popular integration! With its variants for the Voice of the Customer and Voice of the Employee packs!
  • Google Spreadsheets add-on: for those of you that need to work on spreadsheets in an environment independent from the OS used.
• Structured data: our RapidMiner extension and our Dataiku plugin enable you to combine the text analytics results with the structured data you may have associated to it and all the powerful analysis both tools provide.
• Automation: the Zapier app enables you to integrate hundreds of apps together to automate your work. You can check some Zap templates that use MeaningCloud to illustrate only a fraction of what you can do.
• Research: integrate MeaningCloud’s analyses with our plugin for GATE, one of the classic open source solutions for text processing.
• Data analytics: if you are a Qlik user, there’s a connector for MeaningCloud’s Sentiment Analysis to include it in your data analytics.

Customization

We know how important it is to adapt text analytics to the specific scenario or domain you are working on, which is why we provide a myriad of possibilities to do this and reach the best results possible. For every API we provide predefined resources that let you analyze a number of generic scenarios, and all of them included in any of our plans (including the Free one!).

For those cases where you need something more specific, we’ve got you covered:

• Customization: each application is different than the next, and no one better than you knows the ins and outs of scenario you are apply text analytics to. For these reason we’ve implemented a powerful collection of customization consoles that allow you to define resources as specific as you need for your application. You can customize the following resources:
  • Text classification models, to define the categories and criteria you want for automatic Text Classification.
  • Sentiment models, to adapt the Sentiment Analysis to the quirks and twists of your own domain.
  • Deep categorization models, to categorize those scenarios where linguistic nuances are key using Deep Categorization.
  • Dictionaries, to add the terminology or aspects you want to detect to Topics Extraction or to define your own ontology and use it in Deep Categorization or Sentiment Analysis.
• Packs: part of the work we do at MeaningCloud involves creating resources for some of our clients. Some of these scenarios are common and useful enough that we decided to share them with all our clients. This is where our vertical and language packs come in.
  • Our vertical packs provide resources tailor-made for scenarios such as Voice of the Customer, Intention Analysis or Voice of the Employee.
  • Our language packs give access to text analytics in additional languages. You can check out the supported languages and the APIs each one of them applies to.

  All our packs are available to try out for free for a 30-day period. After that, they are available by subscribing to them.

Data, privacy and security

MeaningCloud by default is a Software as a Service application, that is, any processing is done in the servers we have set up for this purpose. This means that when you analyze any text (no matter if you are using one of the text consoles or any of the integrations available), it’s sent to our servers where the analysis requested is done. We are aware of how important data privacy is, so we don’t store the texts sent for processing and we are very careful on how our client’s information is treated. You can read all the details of our data protection policy here.

Some users have very strict data policies, to the point where said data cannot leave their premises. For these cases, MeaningCloud is available as an on-premises deployment, where you can install a server or servers in your environment and do there all your text analytics. This way you can take advantage of MeaningCloud and ensure the confidentiality of your data.

Information security is extremely important to us, which is why we recently achieved ISO 27001 certification, as well as adhered to the Privacy Shield Framework.