Natural Language Processing - The key for value generation from unstructured (text) data
Language is omnipresent and can be encountered in many different facets in our everyday lives as well as in our professional environment – it is written, spoken and communicated in different languages by humans, but also gets analyzed, processed and synthesized by machines. With Natural Language Processing (NLP), computers are able to automatically process and generate natural language and act as an interface between humans and machines.
As an application area of Artificial Intelligence (AI), NLP is always used when monotonous processes or frequently recurring tasks in text processing are to be automated, subsequently optimized and integrated into a higher-level framework. In this way, errors can be minimized in various areas, processes can be (partially) automated, and savings can be achieved (through reduced personnel costs).
In many companies, there is an increasing shift towards digitization and automation. In the process, enormous amounts of unstructured data are continuously accumulating, the scope and complexity of which deter the stakeholders concerned from evaluating it, or the potential in the existing data is often not even recognized in the first place.
Regardless of whether fault messages in manufacturing processes are to be analyzed, doctor’s letters are to be filed in a structured manner, or products are to be suggested automatically, NLP offers a broad spectrum of industry-specific and cross-industry application possibilities.
Together with our customers we would like to take advantage of these opportunities – by using AnnaLyTE, our area of expertise for creating value from your text data.
AnnaLyTE - Natural Language Processing Solutions
RISC Software GmbH supports its customers with its many years of practical experience when it comes to developing individually tailored, AI-supported solutions. Innovative NLP technologies are used and based on four fundamental components:
- Analysis methods specifically selected for the problem
- Strong integration of domain know-how
- Tailored infrastructure solutions
- Comprehensive management of (big) data
We support our customers not only in the development of specific solutions, but also in going through the entire digital process chain. This already starts with the conceptual design of the overall architecture and the selection of tools. Moreover, this also includes both the connection to data sources as well as the preparation of data to enable a secure application of analysis methods from the NLP environment. The continuous integration of domain experts is of crucial importance in order to be able to correctly map all characteristics and peculiarities of a domain in the development. Depending on the requirements, the possible development stages range from prototypes and MVP’s to the development of stand-alone software or the integration of solutions into an existing system.
Together we design the applications of tomorrow
NLP is a core functionality in a multitude of applications. NLP is so versatile and broadly applicable as there are a wide variety of use cases in a large number of domains. Therefore we have summarized a selection of classic use cases of text and document analysis:
Searching for Keywords
Text documents contain a lot of information, but not all of it is relevant. Selectively extracting particularly important information from texts and storing it in a structured way can help to gain a better understanding of the text and enables further (automated) processing steps of the data, such as document classification.
Bypass Elaborate Manual Sorting
Manual sorting of documents can be very time-consuming and labor-intensive. By automating the classification process, documents can be automatically sorted into the categories you have previously selected. After the system does the work for you mostly independently with a high hit rate, this frees up resources for quality control and other important tasks that can be performed exclusively by domain experts.
How emotions become tangible
Keeping track of the current mood of your customers is often a difficult task. With the help of sentiment analysis, positive and negative feedback in texts (e.g. customer reviews) can be recognized and help to shorten response times to inquiries and to respond quickly and more specifically to the needs of customers.
Further fields of application of NL