Relevant Search

List of Tables

Chapter 2. Search—under the hood

Table 2.1. Important pieces of data associated with the inverted index

Chapter 3. Debugging your first relevance problem

Table 3.1. Scoring love matches in Sleepless in Seattle versus lego in The Lego Movie. lego is rare and is mentioned only in The Lego Movie, thus yielding a higher score than the love match.

Table 3.2. Term frequency and document frequencies dampened with default formulas (IDF calculated for 1,000 documents)

Chapter 4. Taming tokens

Table 4.1. Semantic expansion at index time

Table 4.2. Tokens used to represent numerical values and ranges

Chapter 5. Basic multifield search

Table 5.1. Primitives working with TMDB and Elasticsearch

Chapter 6. Term-centric search

Table 6.1. ...