Natural language processing
With state-of-the-art natural language processing algorithms, your applications can understand and analyze human language.
Natural language processing aims at the identification and understanding of human language by machines. To do so, it combines artificial intelligence, machine learning, and linguistics. NLP is one of the most challenging branches of AI mainly because the human language is full of exceptions and ambiguities. We use irony and humor and often it is the context that plays a major role in understanding the meaning of the word. Moreover, there are many languages in the world that are subject to different rules and need to be analyzed differently.
Natural language processing applications may serve many purposes. Their primary aim is to facilitate company development thanks to process automation and freeing their employees from mundane tasks.
Sentiment analysis allows machines to identify emotions that stand behind the words used, if they are positive, negative, or neutral. It is eagerly adopted by applications of natural language processing that aim at measuring customer response to particular products and services, understanding users and more general trends concerning the brand. Sentiment analysis will help you prioritize issues that need your immediate reaction, for example in customer service. If a customer's intent is to give negative feedback online, you may react quickly and prevent it from happening. NLP consulting firms will advise you on the use of sentiment analysis in your particular case.
Instead of looking for the literal sense, semantic search based on NLP aims at understanding the intent of the user that is searching for information and the meaning of the results that the system is returning. To do so, the algorithms analyze not only words, but also relationships between words, sentences, and entire documents – and constantly learn to provide better-fitted results. We use semantic search in our learning management system Samelane to help people get the information they need in a heartbeat but also help to utilize similar algorithms in our client’s systems.
An incredible amount of text data is generated on a daily basis in every organization (documents, contracts, emails, presentations, notes, etc.). With natural language processing algorithms you can perform text mining to transform unstructured and sometimes chaotic documents and databases. In result, you get organized data that can be easily processed and examined further – to draw meaningful conclusions and help in everyday work.
With NLP you can perform text categorization (also referred to as text classification or tagging) instantly and effectively. The main aim of the process is to sort entire documents or pieces of information into organized categories. NLP algorithms can do it precisely and most importantly automatically. Segregated documents allow for better searchability and organization, which without NLP would have to be done manually.
NLP applications can help you with everyday and time-consuming tasks in your company. They can read invoices and other similar documents to extract key data from the text. Supported data types include everything that might be crucial to your business, in the case of invoices it will be an invoice number, date, seller, and buyer. Extracted data can be subject to further analysis.
NLP applications can take over repetitive tasks that have to be done by either humans or machines. One example is digitization – the process of converting documents into digital format. It applies to all kinds of information: invoices, handwritten notes, reports, and all documents that are kept in paper version only or never had an electronic form. This way they’re easier to store, access, share, and become easily searchable. Most importantly, your employees don't have to rewrite them and sort them manually anymore.Document digitization
Quick access to information is crucial in a variety of industries. NLP will help you improve search functionality within your products. Instead of focusing solely on keywords, advanced search uses context analysis, pattern recognition, understands a deeper meaning, and can identify whenever a mistake was made unintentionally. We use natural language processing in our Samelane platform. It allows learners to search for particular topics and get best-fitted results from text documents, photos, video, and audio. This is done not by simple keyword search but foremost by context analysis.
With NLP you can build outstanding and innovative products that offer extraordinary value to your customers. Chatbots and voicebots can give more accurate answers and feel more natural, human-like. Voice systems or personal assistants essentially take advantage of speech recognition and NLP to understand voice commands. Many apps use sentiment analysis to provide their services, such as media monitoring apps, chatbots, and reputation management apps.
Answer pertinent questions
Your clients don’t want to wait to get answers, and the longer they have to wait, the more irritated they get. Automated question answering systems based on natural language processing can provide round-the-clock service to your customers. They can get immediate answers to their questions, accurate advice, and quality support, whenever they need it, be it in the middle of the night. It is possible thanks to chatbots and voicebots that understand not only sentences but also customer intent.
Our natural language processing services consist of three stages that let our clients minimize the risk and costs of their NLP projects.
Our NLP practitioners define your challenge, conduct a workshop session, and propose a preliminary solution.
We propose a long-term, end-to-end solution and plan.
We divide your NLP project into smaller pieces that can be achieved within 1-2 sprints – and develop the first one.