Author Archives: Blanca Galego

About Blanca Galego

MeaningCloud's Product Manager and NLP Consultant.

MeaningCloud Release: Sentiment + Nordic Pack

Not long ago we published the first of our Language Packs: the Nordic pack, which includes several text analytics tasks in Swedish, Danish, Norwegian and Finnish.

Among the text analytics tasks supported, there’s one that was missed by many of you: Sentiment Analysis API. Well, no more!

We are happy to announce that from now on you can also analyze sentiment in the four languages included in the Nordic pack. And what’s more, for those of you that are already subscribed to the pack, it has been automatically included and so you can start using it right away without any change in pricing.

MeaningCloud release

For those of you that are not subscribed to the Nordic pack, remember that you can test all our packs full functionality by requesting a 30 day period trial. It’s super easy!

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MeaningCloud Release: VoC vertical pack upgrade

In the latest MeaningCloud update, we have published a new upgrade for our Voice of the Customer vertical pack. This update has two significant changes:

  • We’ve added a new domain to the four we already supported: telecommunications. This domain is huge and has a vast amount of unstructured data available and ready to be analyzed. You can check out the categories for this new model in the documentation.
  • We’ve refactored the models we already provided. Most of this refactorization has been done under-the-hood, but there are some categories that have changed names, either to give a more intuitive idea of what they refer to or to narrow down the criteria.
MeaningCloud release

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Vertical packs: trial and subscription

We recently published our first two vertical packs: Voice of the Customer and Voice of the Employee, both with several Deep Categorization models in English and Spanish.

We are happy to announce that both packs are now available for automatic subscriptions. In the same way you can choose which plan you want to subscribe depending on the credits, rate limit and resources you need, all the public packs are now included in the upgrade process.

Select packs

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The Text Proofreading API moves to Stilus

Even since the very beginnings of MeaningCloud, we have offered a Text Proofreading API in Spanish which allow you to standardize and ensure the quality of your contents through spelling, grammar and style proofreading.

Stilus logo

On the 2nd of April, we will definitely move this API and its functionality to Stilus, an application where we take advantage of the functionality provided by the API and show everything you can do with it.

To those of you who currently use it, the migration process can be done in three easy steps:

  1. Register at Stilus.
  2. Contact us at support telling us about your volume requirements and which Stilus user would use the API. We will inform you of the conditions and tell you how to subscribe to the API.
  3. Once you have subscribed, you will only have to change the API endpoint and the key parameter value in your integration, and you will be all set to keep using the Text Proofreading API.

If you’d rather use directly the text proofreading functionality online or from Word, check out all the ways in which you can use Stilus!


Voice of the Customer in Excel: creating a dashboard

Excel spreadsheets are still one of the most extended ways of working with big collections of data, especially among non-technical users. Two of our Vertical Packs, Voice of the Customer and Voice of the Employee, are particularly useful for typically non-technical teams, which can now carry out their analyses easily with our last Excel integration.

In this tutorial, we are going to show you how to use the add-in provided in the Voice of the Customer Vertical Pack, how to carry out a VoC analysis, and how to work with its output by creating a dashboard like the one on the right. Working with the Voice of the Employee Pack would follow a similar pattern.

[This post was last updated in February 2019 to include the updated ontology.]

dashboard general

A practical case

Let us imagine we work for a market research department or agency interested in analyzing the Insurance industry. Customer comments in forums and social networks constitute an extremely valuable source of spontaneous information about their opinions about insurance providers.
We are going to focus specifically on auto insurance reviews extracted from ConsumerAffairs, a website that collects reviews from several domains.

The reviews we are going to use have been extracted from the top five companies in the Auto Insurance section: for each one of them we’ve picked ten items. You can download here the Excel spreadsheet we will be working on. It contains a single sheet where we have included two columns: one with the selected reviews, and another with the name of the company they refer to.

As we have mentioned, for this tutorial we are going to use our Vertical Pack for Voice of the Customer analysis. Vertical Packs are a combination of preconfigured models or dictionaries, powerful APIs and specific add-ins for Excel that enable you to adapt text analytics to your domain with only one click. Just by registering at MeaningCloud, you have a 30-day trial for all Vertical Packs available. The trial starts the moment you first analyze a text, so users that have been using MeaningCloud for a while will also be able to try it out.

To get started, you need to register at MeaningCloud (if you haven’t already), request access to the Voice of the Customer pack and download and install the VoC Excel add-in on your computer. Here you can read a detailed step by step guide to the process.

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MeaningCloud Release: new add-ins for Excel

In the last MeaningCloud release we presented our new Deep Categorization API, a new Premium API that gives us access to two of our new vertical packs: Voice of the Customer and Voice of the Employee.

We also know that many of the target users of these functionality may not be necessarily know how to code, so with that in mind, in this latest release we are publishing two new add-ins, one for each vertical pack:

Both add-ins provide an integration with the Deep Categorization API, but focus on giving a more user-friendly approach for the analysis each one of them provides.

MeaningCloud release

The add-ins are adapted so anyone can obtain the analysis they want with just a few clicks, without worrying about API parameters or leaving the environment where they have the data to analyze.

This release also contains minor security updates as well as bug fixes in our core engines.

If you have any questions or just want to talk to us, we are always available at support@meaningcloud.com!


MeaningCloud Release: new Deep Categorization API

This is what we’ve included in MeaningCloud’s latest release:

  • New Deep Categorization API: we are happy to present the first of our Premium APIs, Deep Categorization 1.0, which lets you carry out an in-depth categorization of your data. In this initial release, we’ve included predefined models for analyzing the Voice of the Customer in several domains and the Voice of the Employee.
  • Language Identification 1.1: we say goodbye to Language Identification 1.0, so if you are still using it, you will need to migrate to the newest version. If you are using it through the Excel add-in, we’ve done it for you, so you just have to update your Excel add-in to the latest version.
  • New language for Text Clustering: we’ve added Catalan to the languages supported in the Text Clustering API.
  • General usability improvements: mainly in the developer area of the website.
New NeaningCloud release

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MeaningCloud Release: new Language Identification API and more

As we recently advanced, during these last few months we have been working on new functionality. We are planning to start releasing it over the next few months.

In the latest release of MeaningCloud we have included some of this functionality:

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Text Analytics & MeaningCloud 101

One of the questions we get most often at our helpdesk is how to apply the text analytics functionalities that MeaningCloud provides to specific scenarios.

Users know they want to incorporate text analytics into their processes but are not sure how to translate their business requirements into something they can integrate into their pipeline.

If you add the fact that each provider has a different name for the products they offer to carry out specific text analytics tasks, it becomes difficult not just to get started, but even to know exactly what you need for your scenario.

homer-simpson-confused

In this post, we are going to explain what our different products are used for, the NLP (Natural Language Processing) tasks they are tied to, the added value they provide, and the requirements they fulfill.

[This post was last updated in October 2018 to include our new functionalities.]
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Text Classification in Excel: build your own model

Customized Text Classification for Excel

In the previous tutorial we published about Text Classification and MeaningCloud’s Excel add-in, we showed you step by step how to carry out an automatic text classification using an example spreadsheet.

In this tutorial, we are going a bit further: instead of just using one of the predefined classification models we provide, we are going to create our own model using the model customization console in order to classify according to whichever categories we want.

We are going to work with the same example as before: London restaurants reviews extracted from Yelp. We will use some data from the previous tutorial, but for this one we need more texts, so we’ve added some. You can download the spreadsheet here if you want to follow the tutorial along.

If you followed the previous tutorial, you might remember that we tried to use the IAB model (a predefined model for contextual advertisement) to classify the different restaurant reviews and find out what type of restaurants they were. We had limited success: we did obtain a restaurant type for some of them, but for the rest we just got a general category, “Food & Drink“, which didn’t tell us anything new.

This is where our customization tools come in. Our classification models customization console allows you to create a model with the categories you want and lets you define exactly the criteria to use in the classification.

So how do we create this user model?
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