While reading the title, did you try to correct the misspelled words? If you did, you are relying on your in-built knowledge of the correct spellings you have learned over time. However, since a computer has no innate knowledge, we must provide it with some reference dictionaries to make these corrections. We can ask computers to do this for us, using Natural Language Processing, or NLP.
There are several ‘general’ dictionaries available that have been created and shared amongst the NLP community. A common one is Words Alpha.
Imagine the thousands of consumer-generated text data containing category-specific vocabulary that are either not corrected or replaced by the wrong word.
Let’s consider this sentence from a customer review:
And it matters - think about how people acquire subject-specific vocabulary, for example, doctors or plumbers. These professionals each work with their own set of vocabulary and phrases. So, if they are communicating, they would keep it at a high level; otherwise, they would not understand each other.
At the same time, building this type of subject-specific dictionary is not easy. If you plan to become a doctor, you must study and learn all about human anatomy and the associated medical terms.
The problem with general analytics providers is that they will not invest in building a comprehensive domain-specific dictionary for one industry – it’s too hard. As people, we acquire our vocabulary over time – through studying and reading different types of books. It's the same when trying to create category-specific dictionaries. It would help if you learned from other kinds of data.
Many general analytics providers put this important responsibility onto the shoulders of junior analysts, but the real value comes from subject matter experts working alongside data scientists.
If you’d like to learn more about how we go further, please read our article, “What's the sense in sentiment analysis?”.
The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.
A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!
Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.
Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.
