Improving Search with Text Analysis
Adding adequate text analysis to your search application is just the beginning to creating a great search experience. Using advanced techniques can greatly increase the quality of search results and turn a good search engine into a great one. This course starts with an introduction about different analysis techniques, and how to apply them to different business needs.
Note: This course is a module of the Elasticsearch Advanced Search specialization.
You will learn how to configure analyzers to deal with different languages, how to search in compound words, and how to deal with fuzzy and phrase searches without using expensive queries. You’ll also learn the difference between stemming and lemmatization, as well as the different characteristics of some of the stemming algorithms. After completing this course, you will be prepared to use N-grams, edge N-grams, shingles, and some other specialized analyzers, tokenizers, and token filters in your Elasticsearch solution.
- Introduction to text analysis
- Text to words to tokens
- Language-specific analysis
- Fuzziness, partial matches, and misspellings
- N-grams and edge N-grams
Software Developers, Software Engineers, Data Architects, DevOps
We recommend taking the following foundational courses (or having equivalent knowledge):
- Stable internet connection
- Mac, Linux, or Windows
- Latest version of Chrome or Firefox (other browsers not supported)
- Disable any ad blockers and restart your browser before class
This course is a module of the Elasticsearch Advanced Search specialization. Find out how our focused Training Specializations can help you with your use case.
General Training Information