Category Archives: Webinars

Posts about MeaningCloud’s webinars.

Recorded webinar: Why You Need Deep Semantic Analytics

Last July 13th we delivered our webinar “Why You Need Deep Semantic Analytics”, where we explained how to achieve a deep, automatic understanding of complex documents. Thank you all for your interest.

During the session we covered these items:

  • Automatic understanding of unstructured documents.
  • What is Deep Semantic Analytics? Comparison with conventional text analytics.
  • Where it can be applied.
  • Case study: due diligence process.
  • Ideal features of a Deep Semantic Analytics solution.
  • MeaningCloud Roadmap in Deep Semantic Analytics.

IMPORTANT: you can find a more literary explanation of some of the items we covered, including the due diligence practical case, in this article.

Interested? Here you have the presentation and the recording of the webinar.

(También presentamos este webinar en español. Tenéis la grabación aquí.)
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Why you need Deep Semantic Analytics (webinar)

Achieve a deep, automated understanding of complex documents

Conventional Text Analytics enable a first level of automatic understanding of unstructured content, achieved through its ability to extract mentions of entities and concepts, assign general categories or identify the polarity of opinions and facts that appear in the text. However, these isolated information elements do not reflect the wealth of information provided by these documents and impose limitations when it comes to finding, relating or analyzing them automatically.

Deep Semantic Analytics represents a step beyond conventional text analytics by providing features such as snippet-level granular categorization, detection of complex patterns, and extraction of semantic relationships between information elements in the document.

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Recorded webinar: Integrate the most advanced text analytics into your predictive models

Last April 27th we delivered our webinar “Integrate the most advanced text analytics into your predictive models”, where we presented our new MeaningCloud Extension for RapidMiner. Thank you all for your interest.

During the session we covered these items:

  • Analytics platforms. Introduction to RapidMiner.
  • Text analytics. Introduction to MeaningCloud.
  • Combining text and data analytics. MeaningCloud Extension for RapidMiner.
  • Practical case demo.
  • Application scenarios.
  • How this Extension is different.
  • Product roadmap.

IMPORTANT: The data analyzed during the webinar can be found in this tutorial, along  with the applied RapidMiner workflows and models.

Interested? Here you have the presentation and the recording of the webinar.

(También presentamos este webinar en español. Tenéis la grabación aquí.)
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Recorded webinar: When to use the different Text Analytics tools?

Last February 9th we presented our webinar “Classification, topic extraction, clustering… When to use the different Text Analytics tools?”. Thank you all for your interest.

During the session we covered the following agenda:

  • An introduction to Text Analytics.
  • Which application scenarios can benefit most from Text Analytics? Conversation analysis, 360° vision, intelligent content, knowledge management, e-discovery, regulatory compliance… Benefits and challenges.
  • What are the different Text Analytics functions useful for? Information extraction, categorization, clustering, sentiment analysis, morphosyntactic analysis… Description, demonstration and applications.
  • What features should a Text Analytics tool have? Is it all a question of precision? How to enhance quality?
  • A look at MeaningCloud’s roadmap.

IMPORTANT: The data analyzed during the webinar can be found in this tutorial.

Interested? Here you have the presentation and the recording of the webinar.

(También presentamos este webinar en español. Tenéis la grabación aquí.)
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Classification, topic extraction, clustering… When to use the different Text Analytics tools? (webinar)

How to leverage Text Analytics technology for your business

Text AnalyticsMost valuable information for organizations is hidden in unstructured texts (documents, contact center interactions, social conversations, etc.). Text Analytics helps us to structure such data and turn it into useful information. But which text analytical tools are the most appropriate for each case? When should I use information extraction, categorization, or clustering? Which applications can benefit most from Text Analytics? What are the challenges?

Register for this MeaningCloud webinar on Wednesday, February 8th at 9:00 PDT and discover answers to these and other questions through practical examples.

UPDATE: this webinar has already taken place. See the recording here.

(Este webinar también se realizó en español, ver la grabación aquí.)


Learn to develop custom text classifiers (recorded webinar)

Last October 5th we presented our webinar “Learn to develop custom text classifiers with MeaningCloud”. Thank you all for your attendance.

We began by presenting how to do text classification with MeaningCloud and why it is necessary to develop models that are adapted to each specific application scenario. The bulk of the presentation consisted in using a practical case (analysis of restaurant reviews) to show how these models can be developed using our product.

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Learn to develop custom text classifiers with MeaningCloud (webinar)

Learn in this webinar how to use MeaningCloud’s tools to create classification models completely adapted to your scenario

Users frequently ask us through our support line how to perform text classification according to application-specific taxonomies. For example, somebody needing to analyzing a bank’s contact center calls and open survey responses might be interested in classifying such messages according to the institution’s different types of products and services (deposits, loans, mortgages, etc.) or the type of interaction (request for information, contracting, complaint, etc.).

Custom classification

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A tailored sentiment analysis (recorded webinar)

Last May 4th we presented our webinar “An entirely tailored sentiment analysis using MeaningCloud”. Thank you all for your attendance.

After a brief introduction to MeaningCloud and the operation of its add-in for Excel, we developed a practical example of sentiment analysis in a specific domain (restaurant reviews) and showed how MeaningCloud’s customization tools can be used to improve the accuracy of the analysis:

  • By including attributes that are relevant to the domain and focusing the analysis around them, through the creation of personal dictionaries of entities and concepts.
  • By specifying the polarity of expressions in the domain depending on the context, thanks to the definition of personal sentiment models.

Together, these tools enable our users to be greatly autonomous in the customization of MeaningCloud and put the highest-quality sentiment analysis at everybody’s fingertips.

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A sentiment analysis entirely tailored to your needs with our new customization tool

The adaptation to the domain is what makes the difference between a good sentiment analysis and an exceptional one. Until now, the possibilities of adapting MeaningCloud’s sentiment analysis to your domain relied on the use of personal dictionaries – to create new entities and concepts that the Sentiment Analysis API employed to carry out its aspect-based analysis – or you had to ask our Professional Services Department to develop a tailor-made sentiment model.

Sentiment Models buttonWith the release of Sentiment Analysis 2.1, we incorporated a new customization tool designed to facilitate the creation of personal sentiment models. This tool fully employs our Natural Language Processing technology to enable you to be autonomous and develop —without programming— powerful sentiment analysis engines tailored to your needs.

Other tools for customizing sentiment analysis available on the market, mostly permit to define “bags of words” with either positive or negative polarity. Our tools go far beyond and enable you to:

  • Define the role of a word as a polarity vector (container, negator, modifier), allowing to use lemmas to easily incorporate all the possible variants of each word
  • Specify particular cases of a word’s polarity, depending on the context in which it appears or its morphosyntactic function in each case
  • Define multiword expressions as priority elements in the evaluation of polarity
  • Manage how these custom polarity models complement or replace the general dictionaries of every language.

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Improve your Customer Experience Management with Text Analytics (recorded webinar)

Last June 10th we presented our webinar “Discover the WHY behind your Customer Scores – Improve your Customer Experience Management with Text Analytics”, featuring industry expert Seth Grimes.

The goal of the webinar was to ensure you are getting the most from your Customer Experience / Voice of the Customer initiatives, using text analytics to understand massive amounts of unsolicited, unstructured customer feedback in real time.

User Profiling and Segmentation

The agenda, with contributions from Seth and members of the MeaningCloud team, was:

  • Text analytics in Customer Experience (CX) management. Why is it important?
  • How text analytics complements/amplifies “traditional” CX? What specific benefits does it bring: understanding the reason behind the scores, extending to new, untapped feedback sources, analyzing CX in big data contexts … What new applications does it enable?
  • What text analytics techniques are applicable: text classification, information extraction, sentiment analysis, user profiling…
  • Analysis of some real scenarios/projects: survey analysis, contact center interaction, market research, social media analysis.
  • How to implement this easily with MeaningCloud: APIs, personalization tools, add-in for Excel.

For those of you interested, below you can find the webinar’s slides and recording.

And, if you want to give MeaningCloud a try and see how it can take your customer feedback analysis to the next level, register and use it for free here.

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