Last time we had a look at the task of text normalization as a way of simplifying matching and searching for certain words. I mentioned that for the more complex normalization techniques one needs additional information: Since nouns, verbs, and
Liebe Freunde und Freundinnen, liebe Partner*innen von Qualicen, es ist soweit: die zweite Ausgabe unseres Snapshots - die erste im Jahr 2021 - ist fertig. Wir sind im Dezember 2020 mit diesem neuen Format gestartet und möchten uns zuerst noch einmal ganz
In my last article I talked about the benefits of tokenization regarding text processing: Essentially when we want to make processing text less awkward by separating tokens / words from the whitespace. In this article we continue cleaning up after
Previously we started our journey into the world of Natural Language Processing by learning the basics of Regular Expressions (RegEx) and fuzzy matching. While RegEx is certainly a powerful tool, it has its problems. As I wrote, Regular Expressions have a
NearLy Perfect In my last article I started with a dive into the wonderfull world of Regular Expressions. We’ve seen how RegEx are really useful for search tasks. However… They are not perfect and today we will look at one particular
Into the Fire - A
no less somewhat less nonsense introduction to NLP
Natural Language Processing? - What is NLP?
Language is messy. In our attempts to convey meaning, and emotions to each other, we have come up with some extraordinarily complex structures that need years of learning to grasp. There are countless rules and even more exceptions to those rules but somehow we manage to communicate with each other. The name, scientists have come up with for mess is natural language.
And then there are computers, machines that require a lot of structure to work. NLP is the attempt to make those two worlds meet, to have computers parse, process, and understand the language we use in our daily (natural) lifes. In the coming articles we will have a look at tools, techniques, and methods that help us deal with the chaotic complexity of natural language. We will see the many ways in which NLP will make dealing with language easier, one method at the time. Today we will start with the first:
Liebe Freund*innen und Partner*nnen von Qualicen, Langsam schaffen wir es nicht mehr uns mit allen Kontakten regelmäßig persönlich auszutauschen. Und manche/r scheut vielleicht die Hürde uns einfach mal auf die neuesten Entwicklungen anzusprechen. Und auch nicht jede/r hat die Zeit unseren Updates
User stories and acceptance criterias are the backbone of agile development. Everyone knows badly written user stories provide little value. In extreme cases, they even do more harm than good. Therefore, many best practices and templates exist guiding us to
There is a plethora of NLP libraries out there. For almost every NLP task, be it from rather trivial things like stop word removal, to more complex operations like relation extraction, there are libraries. This yields enormous power for modern
Anomaly Detection Anomaly Detection refers to the problem of finding anomalies in (usually) large datasets. Often, we are dealing with time-dependent or at least sequential data, originating, for example, from logs of a software or sensor values of a machine or