An introduction to Natural Language Processing (NLP)
6 januari 2020 | 5min read
Artificial intelligence or AI is changing the way we look at the world. We can find AI everywhere, from our phones to devices such as Google home. We live in a world that is surrounded by it.
This blog will explain more about something called natural language processing (NLP). It’s a form of artificial intelligence that focuses on analyzing the human language to create advertisements, help you text, draw insights and more.
You will read about the next topics in this blog:
- What is Natural Language Processing?
- What is NLP used for?
- Why is NLP important?
- NLP for real estate websites
What is Natural Language Processing?
Natural language processing or NLP is one of the hottest areas of AI today. NLP is focused on enabling computers to understand and process human languages, to get computers closer to a human-level understanding of language.
Computers are able to process data much faster than we, humans, can. Therefore, they are great at working with standardized and structured data like database tables and financial records.
The problem is that we, humans, don’t communicate in “structured data” nor do we speak binary. We speak and write using words, a form of unstructured data.
This is why our Macs and PCs don’t have the same intuitive understanding of natural language that humans do (not yet). They can’t really understand what the language is really trying to say.
With NLP algorithms, we can get our computers closer to that deeper human level of understanding language. Today, NLP enables us to build things like chat bots, language translators, and automated systems to recommend you the best Netflix TV shows.
“ Natural Language Processing or NLP is a field of Artificial Intelligence that gives the machines the ability to read, understand and derive meaning from human languages. “
What is NLP used for?
NLP is the driving force behind the following common applications:
- Language translation applications such as Google Translate
- Word Processors such as Microsoft
- Word and Grammarly that employ NLP to check grammatical accuracy of texts.
- Interactive Voice Response (IVR) applications used in call centers to respond to certain users’ requests.
- Personal assistant applications such as OK Google, Siri, Cortana, and Alexa.
Why is NLP important?
There is a large volume of textual data
Natural language processing helps computers communicate with humans in their own language. For example: NLP makes it possible for computers to read text, hear speech, interpret it, measure sentiment and determine which parts are important.
Today’s computers can already analyse more language-based data than humans. Without fatigue and in a consistent way.
The human language is extremely complex.
There are infinite ways to express ourselves, verbally and in writing. Not only are there hundreds of languages and dialect, but within each language is a unique set of grammar and syntax rules. This is not the only reason. When write, we often misspell or abbreviate words. When we speak, we have regional accents, and borrow terms from other languages.
While deep learning is now widely used for modeling human language, there’s also a need for syntactic and semantic understanding and domain expertise that are not necessarily present in these machine learning approaches.
NLP is important because it helps resolve ambiguity in language. Besides that it adds useful numeric structure to the data for many downstream applications, such as speech recognition or text analytics.
NLP for real estate websites
There is a lot of information available in the textual description of a listing. Usually they contain important real estate related keywords such as price, amount of bedrooms, specific objects in rooms and more.
Often the metadata is incomplete or incorrect. Therefore, a search does not take these features correctly into account. So, it is possible that a relevant property is not shown.
The AI engines of Co-libry are developed to process natural languages and to get valuable information out of the descriptions.
We do this in 3 ways:
- Keyword detection: Our AI engines can detect real estate related keywords such as terrace, kitchen, bath, garage, fireplace and more.
- Meta validation: We can use the keywords in the descriptions to to validate the metadata and correct the data if it’s wrong.
- Metadata completion: Our engines can use detected keywords to complete metadata so all relevant listings show up in search results.
Natural Language Processing plays a critical role in supporting machine-human interactions.
As more research is being carried in this field, we expect to see more breakthroughs that will make machines smarter at recognizing and understanding the human language.
For now, it is mainly used by bigger companies such as Netflix, Google and Amazon. But there is an upward trend for smaller companies and real estate websites.