Natural Language Processing
Deciphering human language is the goal of Natural Language Processing. Our NLP solutions are capable of analyzing, understanding and extracting relevant information from natural language texts.
More than 80 percent of the information we need is in natural language form. We save our work in text documents. We exchange emails with our employees or suppliers. Our clients write their opinions in forums and social networks. Given such volume and variety of unstructured texts, Natural Language Processing solutions become indispensable allies.
The complexity of human language was, until relatively recently, an unattainable challenge for technology. The same word may have different meanings, figures of speech modify the natural structure of sentences, irony can be difficult to understand ... Sophisticated machine learning
algorithms have made it possible to deal with the inherent ambiguity of natural language.
Our Natural Language Processing systems are capable of:
- Named entity recognition (NER): Our systems can recognize and classify personal names, trademarks, places, dates, addresses, numbers, percentages, books, movies, etc.
- Semantic analysis: Our solutions are designed to understand the meaning expressed in a text. Advanced NLP systems take into account the context of every linguistic unit. In this way, they are capable of solving the ambiguities caused by phenomena such as polysemy (a word that has different meanings) or homonymy (different words that are written alike).
- Multi-word expressions recognition: NLP systems are able to identify multi-word expressions (lexical units larger than a word that can bear both idiomatic and compositional meanings).
- Morphological analysis: Our NLP solutions are capable of recognizing the grammatical category of each word of a sentence.
- Syntactic analysis: These solutions can also identify the syntactic functions of the different elements of a text.
- Hierarchy: Natural Language Processing involves the extraction of the hierarchical relations between the different parts of a text.
- Pattern extraction: NLP can be used to identify repeating patterns from texts.
- Concepts recognition: Natural Language Processing systems are able to recognize the main themes or the general meaning of a text.
Benefits of Natural Language Processing
Natural Language Processing saves time and money. NLP solutions are capable of handling large volumes of information at an unattainable speed for a human being.
NLP can be used for many different purposes. Among its most common applications, it is worth mentioning the following:
- Sentiment analysis: NLP allows us to discover the positive, negative or neutral connotations of a text. It is used, for example, to monitor the opinions expressed about a product on social networks.
- Retrieving information: Thanks to Natural Language Processing, it is possible to discover relevant unstructured information that remained hidden.
- Translation: NLP is a key element in automatic translation systems. The goal is to avoid literal translation and to convey the meaning of the original text.
- Correction: The application of Natural Language Processing improves text correction systems. These systems are not only able to correct misspelled words, but also to check grammar, syntax or style.
- Recommendations: Thanks to the recognition of the main concepts expressed in a text, it is possible to recommend similar or complementary information.
All processes that include a significant amount of text can take advantage of Natural Language Processing. At 3.14 we are committed to developing tailor-made solutions that maximize these benefits.