Natural Language Processing

Natural Language Processing  

The goal of natural language processing (NLP) is to design and build computer systems that are able to analyze natural languages like German or English, and that generate their outputs in a natural language, too. Typical applications of NLP are information retrieval, language understanding, and text classification. The development of statistical approaches for these applications is one of the research activities at the Lehrstuhl für Informatik VI.

Information retrieval (IR) deals with the representation, storage, organization of, and access to information items. Given a query the goal is to extract a subset of documents from a large data collection that satisfies a user's information need. Besides written texts the database may also contain multimedia documents, e.g. audio and video data.

In natural language understanding, the objective is to extract the meaning of an input sentence or an input text. Usually, the meaning is represented in a suitable formal representation language so that it can be processed by a computer.

The goal in text classification is to assign a text document to one out of several text classes. For newspaper articles, such classes are sports reports, finances, and politics.

  • Information Retrieval
  • Natural Language Understanding
  • Spoken Dialogue Systems
  • Text Classification and Clustering

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