English, Chinese, or Spanish, the inhabitants of the earth use thousands of different languages to communicate. On the other side, the communicative language in the world of machines consists of only two numbers: 0 and 1. So, how can we bring these unrelated languages together in a way that will benefit everyone? If you’re wondering about it, let's make an informative introduction to natural language processing.
Natural language processing is the process of understanding and analyzing human languages by computer languages and extracting useful information from nonsense data. It sounds a little confusing. Then remember the times you talk to Siri or those moments when the search engine guessed your thoughts after you hit just a few buttons. That's exactly what NLP is. A branch of artificial intelligence was developed to fill the gap between human language and computer understanding. It can analyze and process the words in the text utilizing its advanced grammar capabilities and algorithm, even if you make some mistakes.
Now that you know what it is, we can clear things up by getting into how does natural language processing work. There are two basic techniques in natural language processing: syntax and semantic analysis.
When modeling natural language, the machine first checks whether the syntax is a sentence. This regulatory process analyzes the words in the sentence and the relationships between the words. Measures sentence elements such as subject, verb, and object and their affixes according to the rules of the language.
Semantic analysis determines the possible meanings of sentences using data that has passed through the syntax stage. In doing so, it categorizes words according to their context and ignores meaningless results. In short, semantic analysis naturally interprets text data as humans interpret it.
Natural language processing techniques that work successfully offer the following services:
• Text Classification: As one of the most basic NLP techniques, text classification allows to divide data from different sources such as web pages, forums, e-mail, and social media into organized groups.
• Text Similarity: By comparing different texts, you can easily identify similarities and categorize similar texts. For example, you can quickly identify frequently asked questions to your institution, or you can eliminate the intensity of repeated questions in notifications to customer service.
• Intention Classification: The intent classification technique enables the creation of the right strategies by understanding the trends of the customers. The data obtained from the texts categorizes the customers according to their purchase, unsubscribe, purpose.
• Sentiment Analysis: It helps companies to develop new strategies and decision-making processes by analyzing the positive or negative emotions of the users hidden in the texts.
• Named Entity Recognition: This divides the data in the basic technical text into predetermined categories. By categorizing data such as date, location, institution, person, and organization name, you can develop analysis and action processes specific to the target entity you are interested in.
• Keyword Extraction: You can track the words you want to access in raw data stacks and make them meaningful for your organization and operations. By using this technique, you can set up efficient campaigns by highlighting the words your customers use the most.
• Language Recognition: This pre-process determines which language the written data from different sources belong to. It scans potential languages and directs customers to representatives speaking in their own language and provides automatic answers in the right language.
Natural language processing is highly important to both companies and their customers. If you're wondering why let’s look at where NLP is useful:
• Chatbots: Companies are now using advanced chatbots to communicate with their customers. These bots can understand the questions asked by customers and give answers from large databases. In this way, the customer can easily get the answer instead of scanning pages and documents, while businesses avoid hiring dozens of call center staff for this job.
• Email Classification: Email services use natural language processing methods to classify incoming emails to their users under titles such as spam, important or promotional. Likewise, businesses can develop classification algorithms customized for their services using similar methods.
• Smart Searches: Google or other search engines predict what they will search for, using data from different sources and the user's search history. Blogs and e-commerce sites also improve the user experience with similar smart search methods. Smart completions make it easier for users to find the right words, while algorithms analyze the query semantically. Thus, even if they do not contain the same words, it presents results with similar meanings to the user.
• Social Media Monitoring: Today, many companies use social media monitoring services with natural language processing software. If we look at the search results with the right keywords, companies can both analyze customer satisfaction and be informed about customer complaints easily. In addition, general opinions about the sector and customer tendencies can be analyzed.
Natural language processing has numerous benefits. The most important ones are:
• Easy correction of misspelling.
• Semi-automatic translation of written documents from one language to another.
• Ability to automatically create readable summary texts
• Producing sentences and text in natural language.
• Determining the thought maps of people by analyzing the correspondences that take place in environments such as social networks.
• Processing and grouping of texts.
• Financial and statistical reporting.
• Use of automated response systems in industries such as banking and customer service.
Every institution that wants to exist in the digital world needs to provide its customers with a personalized and exclusive experience in sales and customer service processes. Etiya AI Platform, Cognitus, increases the efficiency of operational processes with artificial intelligence-supported NLP solutions and services.
Thanks to its next-level natural language processing software, it offers premium services such as text classification, sentiment analysis, text similarity, and entity recognition, as well as malicious text identification and forum redirection. Discover forecasting and recommendation services and more with Cognitus.
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