Author Archives: David Muñoz

About David Muñoz

CTO at MeaningCloud

MeaningCloud participates in T3chFest 2019

This year MeaningCloud participates in T3chFest, the technology fair in University Carlos III de Madrid.

T3chFest was born as a show of the research works made in the Department of Informatics. Today, the event has become a reference in Spain’s technology scene. In the last edition 1600 people attended to more than 80 talks.

This year we have submitted a call titled “NLP for Small Data“, where we review the state of the art in the Natural Language Processing. We will also discuss the advances in Deep Learning and the usage of Linguistic Models.

The talk will be presented by two members of our Linguistics team: Concepción Polo, Director of Linguistics, and María José García, computational linguist. They are actively involved in every linguistic model in all our products, from the initial model sketch to its final fine tuning.

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Easy Text Analytics using MeaningCloud’s Zapier integration

We at MeaningCloud love Zapier. It lets us build workflows connecting email, Slack, etc. We wanted to contribute our bit to its ecosystem, so we created MeaningCloud’s Zapier integration. Thanks to it, we can perform Text Analytics in any Zapier workflow easily.

Many organizations use workflows to automate tasks. Chat rooms and bots are a common way of triggering events. For instance, the Slash commands in Slack or Hubot respond to well-formed commands with strict patterns to avoid ambiguity, which is something desirable under some circumstances.

Zapier logo

Where these approaches do not fit specially well is, precisely, one of the most exciting aspects of using Text Analytics in automatization: it can react to the outside world. A company can analyze all communications received from clients, measure reputation, detect weaknesses, or even analyze the employee satisfaction. And all that information can be injected in an automated process and react conveniently.

In this article, we will learn how to integrate MeaningCloud in any Zapier workflow. Continue reading

Dockerized text analytics with MeaningCloud On-Premises

One of the main challenges users face when adopting an on-premises solution is the ability to integrate it into their infrastructure. The days when EJBs and application servers ruled the world have gone, and organizations bet for virtualization. They offer convenient features like isolation and replication, but along with a critical drawback: performance. Docker has raised as a serious alternative to virtual machines, and dockerized applications are the new EJBs. It is not uncommon to find in a company’s infrastructure dockerized services and processes. In this sense, a question rises: what about dockerized text analytics?

The problem with virtual machines

By definition, a virtual machine runs a complete stack of virtualized hardware and operating system. It takes a powerful host machine to run a large amount of virtual machines seamlessly. Organizations often find themselves forced to invest in powerful servers to run solutions that are in fact not specially hardware-demanding.

In the last years, an alternative approach called containers has been widely adopted. In short, a container is an isolated file system, with its own processes, users, and network interfaces, but without any virtualized hardware.

Dockerized text analytics with MeaningCloud

MeaningCloud runs seamlessly in Docker containers, which makes it a convenient solution for deploying it in some infrastructures. It also takes advantage of some appealing aspects inherited from the Docker internal design.

Text analytics: docker makes it easy

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