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 instructor-led course starts with an introduction about different analysis techniques, and how to apply them to different business needs. You will learn how to configure analyzers to deal with morphological variations, 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 module, you will be prepared to use ngrams, edge-ngrams, shingles, and some other specialized analyzers, tokenizers and token filters in your Elasticsearch solution.
- Introduction to Text Analysis
- Text to Words to Tokens
- Morphological Variations
- Handling Fuzziness, Partial Matches, and Misspellings
- N-Grams and Edge N-Grams
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.
Software Developers and Engineers, Data Architects, DevOps
Virtual Classroom - 1 Day | 2-3 hours
We recommend you have taken Elasticsearch Engineer I and Elasticsearch Engineer II or possess equivalent knowledge. Engineer I and Engineer II teach the concepts that are the foundation upon which all specializations are built.
- Stable internet connection
- Mac, Linux, or Windows
- Latest version of Chrome or Firefox (Safari is not 100% supported)
Upcoming Classes — Improving Search with Text Analysis
It was awesome. Both instructors are great speakers. They have a wide and deep knowledge about the topic, and they know how to pass it on. They are infecting with their enthusiasm.