Posted by AdminMar 23, 2021 10:05:28 AM
4 minutes to read
Technology is ever-evolving. Due to this fast growth, new data is being created by the megabyte every second. Every text message sent, query searched, video watched, package shipped, and call made is a form of data. And for data-driven businesses and organizations, it’s a goldmine of insights generated each day.
Unfortunately, it is impossible to make sense of the vast amount of available data without computerized intervention. This is where natural language processing (NLP) comes in.
Examples of Natural Language Processing in Everyday Life
Natural language processing (NLP) is known as the interaction between human language and computers. NLP can complete tasks associated with language, such as sentiment analysis and language detection. As a result, NLP enables our computer systems to interact with human language, opening the door to countless possibilities. Through NLP:
Businesses can translate customer data into insights that improve the customer experience.
Health organizations can use data to determine treatment outcomes for patients.
Government organizations can use data to pinpoint potential risks, thus protecting foreign and domestic assets.
These examples are only the beginning. And while they may sound futuristic, NLP is already changing the way we carry out mundane tasks in our everyday lives.
1. Question Answering
“Hey Siri, what does NLP mean?”
Smart assistants such as Siri and Alexa make it easy for us to get answers whenever we need them. Whether you need the definition of a word or a movie time, these assistants can help -- through NLP.
Smart assistants work by recognizing and analyzing speech patterns in data. They then assign meaning to the words spoken and provide the most valuable response. If the assistant fails to completely understand the meaning, you’ll receive an inaccurate response.
NLP solves the issue of meaning through methods such as part-of-speech tagging (identifying a part of speech for every word) and natural language generation (using databases to determine the intent of a word). It’s the technology that makes speech recognition a possibility.
2. Sentiment Analysis
NLP is also used to determine positive or negative connotations, known as sentiment analysis. For example, businesses often use sentiment analysis to understand customer feedback and social media interactions. This helps them make critical decisions that improve the customer experience.
It may seem easy to spot a negative review on a business website. However, when you must sift through thousands of reviews that may include sarcasm, emojis, and multiple languages, the task is impossible without NLP methods.
3. Image to Text Mapping
Images are another form of human communication that computers must learn to recognize and understand. NLP enables tech tools to map text to images for automatic image captioning.
For example, search engines use image-to-text mapping to provide image results from a search query. By entering a term in Google such as “dog”, the engine will generate images tied to that keyword.
You can also see NLP in action by visiting your favorite online retailer. E-commerce companies use NLP to automatically assign tags to their products, ensuring they show up in their relevant categories.
4. Machine Translation
Have you ever used Google Translate or another translation service? For proper translation, the application or tool must be able to identify the meaning, context and other nuances of each language to provide an accurate translation. This is only possible through NLP technology.
5. Name Entity Recognition
When reading or listening to a sentence, it’s easy for us to identify the entities involved. For example, in the sentence, “Washington DC is the capital of the United States”, we can identify two entities: Washington DC and the United States.
Through NLP, computers can do the same. Name entity recognition helps businesses and organizations with large datasets quickly discover critical insights.
For example, streaming apps often use entity recognition to make automatic recommendations based on what customers have enjoyed previously. As a result, the app becomes more engaging for the customer, which increases loyalty and revenue.
Rosoka: Multilingual & Customizable NLP Solutions
NLP’s uses go far beyond these everyday examples. In fact, NLP is changing the way organizations and businesses complete tasks involving security, intelligence, and other critical components.
Rosoka helps support these organizations through multilingual and customizable NLP solutions. Our software is the industry standard for applications for:
Military intelligence: Our military uses NLP to process data and provide field intelligence, review asset risk for military personnel, and manage assets. Our software is designed to integrate into any military solution seamlessly. Plus, we’re already embedded and approved with many military, law enforcement, and intelligence organizations.
Business intelligence: Customer data such as market reports and surveys can help businesses improve their reporting and analytics capabilities. As a result, stakeholders can make critical decisions that move the business forward.
Customer Relationship Management (CRM): Rosoka increases visibility when integrated into CRM systems designed to track and maintain customer relationships.
Risk management: Whether you work at a financial services company, governmental agency, or another high-risk organization, Rosoka helps you assess security risks through data.
Right out of the box, Rosoka software will get you 85% of the way to your goal. From there, our solutions are fully customizable to fit your requirements. There’s no need to purchase extra tools or add-ons for various languages or verticals.
Reach Out to Rosoka for Expert Entity & Relationship Extraction
Rosoka partners with companies and organizations within a wide range of industries to provide next-generation NLP. When accuracy and customization matter, trust the industry-standard. To learn more about Rosoka solutions, send us a message.