Category Archives: MeaningCloud

This category groups the different aspects of MeaningCloud we talk about in the blog.

الصيحة! Text Analytics in Arabic

At MeaningCloud we aim to provide the most advanced text analytics product with the broadest language coverage in the market. That’s why before we finished 2019 we worked on launching several new language packs to increase the coverage given by our standard pack — English, Spanish, French, Italian, Portuguese and Catalan — and our Nordic pack — Swedish, Danish, Norwegian and Finnish.

The third pack we launched is the Arabic pack. Arabic, the fifth most spoken language in the world, is the official language in twenty countries and co-official in six others. It is the first language of 280 million speakers, and the second language of another 250 million. Moreover, for religious reasons, several million Muslims living in other countries have knowledge of Arabic.

Its most peculiar characteristic is that it uses its own writing system, from right to left, joining the letters together. In this way, each letter can have up to four forms. It is also interesting that, despite the fact that they were introduced in the 1920s, there are no capital letters in Arabic. Since sometimes common names can be confused with proper names, the latter are usually enclosed in parentheses or quotes.

MeaningCloud now provides coverage for Arabic for the following functionality:

Arabic

This coverage will be extended through the successive product releases depending on the market demand. Find detailed information on our new language coverage page.

So, what are these text analytics tasks and what are they used for?
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Text Analytics for the Contact Center of the Future

The contact center is a crucial component of the customer experience and increasingly incorporates more channels based on unstructured information. In this post we analyze how advanced semantic analysis can be used to get the most out of the contact center of the future.

The Rise of the New Contact Center

Interest in the contact center has multiplied by its greater role as an essential component of the customer experience. New interaction channels (bots, chats, social) add to the traditional email and telephone and enable innovative ways to connect with clients in both inbound and outbound contact centers, both internal to companies of all types and in those operated by BPO vendors to provide outsourced services.

In this way, the contact center (traditionally known as call center) has ceased to be a cost center to become a tool for proactively communicating with and understanding the market, for multichannel business development and for generating value for the company.
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Ура! Text Analytics in Russian

At MeaningCloud we aim to provide the most advanced text analytics product with the broadest language coverage in the market. That’s why before we finished 2019 we worked on launching several new language packs to increase the coverage given by our standard pack — English, Spanish, French, Italian, Portuguese and Catalan — and our Nordic pack — Swedish, Danish, Norwegian and Finnish.

The second pack we launched is the Russian pack. Russian is the official language of the Russian Federation, Belarus, Kazakhstan and Kyrgyzstan. It was the de facto language in the Soviet Union, so its use it’s also common in the Baltic States, the Caucasus and Central Asia. It’s the most common of the Slavic languages with almost 144 million speakers.

Russian is written using the Cyrillic alphabet, and although transliteration into the Latin alphabet has been common due to the technical restrictions and to the unavailability of Cyrillic keyboards abroad, it’s used less and less thanks to the Unicode extension that incorporates the Russian alphabet and the many free programs that leverage it.

MeaningCloud now provides coverage for Russian for the following functionality:

Russian pack

This coverage will be extended through the successive product releases depending on the market demand. Find detailed information on our new language coverage page.

So, what are these text analytics tasks and what are they used for?
Continue reading


好棒! Text Analytics in Chinese

At MeaningCloud we aim to provide the most advanced text analytics product with the broadest language coverage in the market. That’s why before we finish 2019 we have worked on launching several new language packs to increase the coverage given by our standard pack — English, Spanish, French, Italian, Portuguese and Catalan — and our Nordic pack — Swedish, Danish, Norwegian and Finnish.

The first pack we are launching is the Chinese pack. Chinese, the official language of the People’s Republic of China. It’s the language with the most native speakers, almost a 16% of the global population.

Chinese (in all its varieties) is a group of languages based on ideograms, traditionally arranged in vertical columns, read from top to bottom down a column and right to left across columns. The variety covered by MeaningCloud is simplified Chinese.

MeaningCloud now provides coverage for Chinese for the following functionality:

Chinese pack

This coverage will be extended through the successive product releases depending on the market demand. Find detailed information on our new language coverage page.

So, what are these text analytics tasks and what are they used for?
Continue reading


Performance Metrics for Text Categorization

One of the most common and extensively studied knowledge extraction task is text categorization. Frequently customers ask how we evaluate the quality of the output of our categorization models, especially in scenarios where each document may belong to several categories.

The idea is to be able to keep track of changes in the continuous improvement cycle of models and know if those changes have been for good or bad, to commit or reject them.

This post gives answer to this question describing the metrics that we commonly adopt for model quality assessment, depending on the categorization scenario that we are facing.

 

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NLP technologies: state of the art, trends and challenges

This post presents MeaningCloud’s vision on the state of Natural Language Processing technology by the end of 2019, based on our work with customers and research projects.

NLP technology has practically achieved human quality (or even better) in many different tasks, mainly based on advances in machine learning/deep learning techniques, which allow to make use of large sets of training data to build language models, but also due to the improvement in core text processing engines and the availability of semantic knowledge databases.

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Case Study: Text Analytics against Fake News

Everybody has heard about fake news. Fake news is a neologism that can be formally defined as a type of yellow journalism or propaganda that consists of deliberate disinformation or hoaxes spread via traditional print and broadcast news media or online social media. It is also commonly used to refer to fabricated or junk news, with no basis in fact, but presented as being factually accurate.

The reason for putting someone’s efforts in creating fake news is mainly to cause financial, political or reputational damage to people, companies or organizations, using sensationalist, dishonest, or outright fabricated headlines to increase readership and dissemination among readers using viralization. In addition, clickbait stories, a special type of fake news, earn direct advertising revenue from this activity.

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Use case: VoC program for retail

Voice of the Customer (VoC) programs have become an established path for retailers to deliver enhanced customer experiences.

Consumer behavior, nevertheless, is always changing. Retailers are rarely able to anticipate these behavioral changes or adapt quickly enough to preserve or grow their market share.

In 2018, a regional supermarket brand with over 800 hundred stores wanted to understand customer experience at every touchpoint in order to identify potential areas of customer frustration.

The company undertook a strategic Voice of the Customer (VoC) program with the aim of systematically and consistently capturing insights from the customer experience.

The program is still running. It comprises of around 23,000 surveys per month, completed by customers at various branches of the supermarket chain.

In retail, listening to the Voice of the Customer to identify the strengths and weaknesses of business is fundamental. Competition is fierce. Given that the scale of information to be analyzed is immense, the company decided to work with MeaningCloud to process the literal answers to the open-ended questions of the surveys, so they need not worry about the amount or the time needed to process them.
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Introducing the Demo for VoC Retail

Illustration showing a group of shops. Voc Retail

At MeaningCloud, we know how important unstructured data is for  Voice of the Customer Analysis; so we’ve defined a model that will allow you to characterize any feedback, focusing on the retail domain, in detail that you receive from your customers.

Our experience in Voice of the Customer Analysis has shown us that to obtain useful results when consolidating or reorienting a business strategy the detection of peculiarities of a specific domain is vital, as much in a linguistic way as a conceptual way, taking into account the identifying characteristics of the brand to be analyzed. For this reason, we have not only developed an analysis model focused on the retail trade, but we have also adapted analytical tools towards the sale of groceries, personal care and homecare in the retail sector.

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MeaningCloud achieves ISO/IEC 27001 certification

In MeaningCloud, we know how important it is to manage and ensure information security, even more so for a platform that processes all kinds of texts — including texts with sensitive information — to help you extract insightful information from them. For this reason, at the end of last year we prioritized confirming and improving our good practices by obtaining the ISO 27001 certification, which we achieved in our first attempt in February after following an extensive audit process carried out by RINA.

For those unfamiliar with it, ISO/IEC 27001 is an information security standard that specifies a management system that is intended to bring information security under management control and gives specific requirements.

Organizations that meet the requirements may be certified by an accredited certification body following successful completion of an audit. The standard is published by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) under a joint subcommittee.

ISO27001

The certification obtained applies to both MeaningCloud in its SaaS and its on-premises version, and includes all its stages: development, maintenance and deployment.