Hybrid Search

Traditional keyword-based search often fails to capture the context and intent behind user queries, leading to irrelevant or incomplete results. Vectara's Hybrid Search combines semantic search with traditional keyword-based approaches to offer a powerful and flexible solution for text retrieval.

We combine partial, exact, and Boolean text matching with neural models which blend traditional, keyword-based search with semantic search in what is called a "hybrid" retrieval model. This enables users to discover information based on a combination of keywords and the contextual meaning and relevance of their queries.

For example, you can use this in Vectara to:

• Include exact keyword matches for occasions where a search term was absent from Vectara's training data (e.g. product SKUs)
• Disable neural retrieval entirely, and instead use exact term matching
• Incorporate typical keyword modifiers like a NOT function, exact phrase matching, and wildcard prefixes of terms

Enable hybrid search

Enable hybrid search by specifying lexical_interpolation value at query time, specifically in the search object. This value can range from 0.0 to 1.0 (inclusive).

note

Setting lexical_interpolation to 1.0 is equivalent to the original BM25.

As you ingest data and run queries, adjust the lexical_interpolation value to achieve the perfect balance in answer quality.

{
  "query": "What is the meaning of life?",
  "search": {
    "corpora": [
      {
        "corpus_key": "my-corpus"
      }
    ],
    "offset": 0,
    "limit": 10,
    "lexical_interpolation": 0.025
  }
}

tip

For more information about queries such as additional search and summarization parameters, see the Query API Definition section and our interactive API Reference.

Experiment with different lexical interpolation values

The default value of lexical_interpolation is 0, which disables exact and Boolean text matching. A value of 1 would disable neural retrieval instead, relying only on Boolean and exact text matching. Experimenting with the lexical_interpolation value is useful if you're trying to evaluate how a keyword system like one based on Elasticsearch or Solr may compare to Vectara.

tip

💡 You can test queries with different lexical_interpolation values in our API Reference and in the Vectara Console.

Vectara supports in-between values as well, which tells Vectara to try to consider both neural and Boolean and exact text matching and then to blend the scores of the results of the two different scoring models. Users often see best results by setting this lambda value somewhere between 0.01 and 0.1, and we typically recommend users start experimentation with a lexical_interpolation value of 0.025.

Syntax interpretation

When interpreting query strings, Vectara treats the following syntax specially.

• Words that are quoted must match exactly in that order. For example, the query blue shoes must match the word blue followed immediately by shoes.

• A word fragment suffixed with an asterisk * is treated as a prefix match, meaning that it matches any word of which it is a prefix. For example, Miss* matches Mississippi.

• Words prefixed with a minus - sign are excluded from the results. To extend on the previous example, -Mississippi would exclude results referencing the Magnolia State. Using -Miss* would exclude references to both Mississippi and Missouri.