---
categories: [blog, "book review"]
title: "[Book review] Relevant Search"
date: 2021-05-02T21:35:08+07:00
tags: [book, review, search, programming, algorithm]
draft: true
---

So I decided to review books as I write. As people say, you would understand
things better when you share it with each other.

Each review will contain:

- metadata: book name, author(s), ISBN, genres, language (please tell if there
    are some more helpful information)
- summary: wrap up the content of the book; it should not no more than 5
    subsections of 150 words each
- comments: my thoughts on the book -- what I like and don't like about it

# Metadata

| Book | Relevant Search: With applications for Solr and Elasticsearch |
|---------|------------------------------|
| Authors | Doug Turnbull, John Berryman |
| ISBN    | 9781617292774                |
| Genres  | Programming                  |
| Language| English                      |

# Summary
## The search relevance problem

Given an increasingly large amount of information, it is infeasible for users
to retrieve what they needed.  Relevance scoring is therefore essential for
search engines.

In general, the relevance engineers have to identify the most important
features describing the content, the user, or the search query, transfer those
features to the search engine, then measure what's relevant to the search by
crafting signals and finally balance the weights of the signals to rank the
results.

Unfortunately, it is a challenging problem.  Each search application
serves a different type of content and thus has different expectation for
relevance.  Consequently, there is no silver bullet to solve this problem.
Even the academic field that thoroughly study this problem, information
retrieval is not a one-size-fit all solution.  Relevance is strongly tied with
the field and the application purpose.

## Tackling the problem

The book approaches the problem first by a top-down analysis of how a typical
search engine works.

## Taming token
## Multifield search
## Term-centric search
## Shaping relevance function
## Providing relevance feedback
## Designing a relevance-focused search application
## The relevance-centered enterprise
## Semantic and personalized search
# Comments