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Identifying Wordsedit
A word in English is relatively simple to spot: words are separated by whitespace or (some) punctuation. Even in English, though, there can be controversy: is you’re one word or two? What about o’clock, cooperate, half-baked, or eyewitness?
Languages like German or Dutch combine individual words to create longer
compound words like Weißkopfseeadler (white-headed sea eagle), but in order
to be able to return Weißkopfseeadler
as a result for the query Adler
(eagle), we need to understand how to break up compound words into their
constituent parts.
Asian languages are even more complex: some have no whitespace between words, sentences, or even paragraphs. Some words can be represented by a single character, but the same single character, when placed next to other characters, can form just one part of a longer word with a quite different meaning.
It should be obvious that there is no silver-bullet analyzer that will miraculously deal with all human languages. Elasticsearch ships with dedicated analyzers for many languages, and more language-specific analyzers are available as plug-ins.
However, not all languages have dedicated analyzers, and sometimes you won’t even be sure which language(s) you are dealing with. For these situations, we need good standard tools that do a reasonable job regardless of language.
- Elasticsearch - The Definitive Guide:
- Foreword
- Preface
- Getting Started
- You Know, for Search…
- Installing and Running Elasticsearch
- Talking to Elasticsearch
- Document Oriented
- Finding Your Feet
- Indexing Employee Documents
- Retrieving a Document
- Search Lite
- Search with Query DSL
- More-Complicated Searches
- Full-Text Search
- Phrase Search
- Highlighting Our Searches
- Analytics
- Tutorial Conclusion
- Distributed Nature
- Next Steps
- Life Inside a Cluster
- Data In, Data Out
- What Is a Document?
- Document Metadata
- Indexing a Document
- Retrieving a Document
- Checking Whether a Document Exists
- Updating a Whole Document
- Creating a New Document
- Deleting a Document
- Dealing with Conflicts
- Optimistic Concurrency Control
- Partial Updates to Documents
- Retrieving Multiple Documents
- Cheaper in Bulk
- Distributed Document Store
- Searching—The Basic Tools
- Mapping and Analysis
- Full-Body Search
- Sorting and Relevance
- Distributed Search Execution
- Index Management
- Inside a Shard
- You Know, for Search…
- Search in Depth
- Structured Search
- Full-Text Search
- Multifield Search
- Proximity Matching
- Partial Matching
- Controlling Relevance
- Theory Behind Relevance Scoring
- Lucene’s Practical Scoring Function
- Query-Time Boosting
- Manipulating Relevance with Query Structure
- Not Quite Not
- Ignoring TF/IDF
- function_score Query
- Boosting by Popularity
- Boosting Filtered Subsets
- Random Scoring
- The Closer, The Better
- Understanding the price Clause
- Scoring with Scripts
- Pluggable Similarity Algorithms
- Changing Similarities
- Relevance Tuning Is the Last 10%
- Dealing with Human Language
- Aggregations
- Geolocation
- Modeling Your Data
- Administration, Monitoring, and Deployment