Books about full text search?

“Relevant search” by Doug Turnbull and John Berryman, published by Manning, is THE best book to get started with tuning search engines.

I’be been a search engineer for >10 years and this is always the first book I recommend.

https://www.manning.com/books/relevant-search

Three reference textbooks are available openly:

* Introduction to Information Retrieval, http://informationretrieval.org/

* Information Retrieval in Practice, http://www.search-engines-book.com/

* Entity-Oriented Search, https://eos-book.org/

Modern Information Retrieval is also a classic reference. Not openly available but some contents are (were?) available online. Their site seems to be down but the Internet Archive has a copy.

Additional resources here:

* https://nlp.stanford.edu/IR-book/information-retrieval.html http://web.archive.org/web/20220708135205/http://grupoweb.up...

At a general audience level, "Index" is on my list to read. It covers the invention of the index up to digital search engines. https://www.nytimes.com/2022/02/09/books/review-index-histor...

"Introduction to Information Retrieval" is a textbook which is available online https://nlp.stanford.edu/IR-book/ Here's a review: http://glinden.blogspot.com/2009/02/book-review-introduction...

Another textbook which IMHO is a bit lower level is "Information Retrieval: Implementing and Evaluating Search Engines". The book website is down for me right now, but you can find it on Amazon here: https://www.amazon.com/Information-Retrieval-Implementing-Ev...

Another commenter linked to "Relevant Search", which is great if you want to learn how to effectively use a search engine to improve relevance (as opposed to how to implement a search engine). It's old, but another book in that vein that was really helpful for me earlier in my career is Lucene in Action: https://www.amazon.com/Lucene-Action-Second-Covers-Apache/dp...

Managing Gigabytes

https://books.google.co.uk/books/about/Managing_Gigabytes.ht...

Old but good!

Not a book, but this paper from 2019 covers a lot of ground and reviews the different topics extensively: https://tonellotto.github.io/publication/fntir/fntir_main.pd...

Take a look at my post “Lucene: The Good Parts”—

https://blog.parse.ly/lucene/

The book mentioned there is Lucene in Action.

And then this YouTube presentation by a Lucene/Elasticsearch committer will give you a nice overview of some related algorithms—

https://youtu.be/eQ-rXP-D80U

Not a book but Hellerstein’s CS186 from 2015 starting with Lecture 17 gave me a basic understanding (I think).

Playlist https://youtube.com/playlist?list=PLhMnuBfGeCDPtyC9kUf_hG_Qw...

Also from that lecture series, the low level is always IO. One disk read tends to dwarf n^2 in-memory algorithms.

And IO is all about tuning caches and hardware for the specific structural relationships in the data, the way in which it is accessed, and the hardware everything runs on.

Good luck.

Hotz... Is that you... Trying to learn to improve Twitter search? ;)

https://www.manning.com/books/relevant-search

Also "taming text"

Lucene in Action, good introduction to Lucene, which can be helpful to learn ElasticSearch (most used FTS these days)

Check the literature of open courses on Text Retrieval. E.g. https://stanford.edu/class/cs276/

series of tutorials and comparisons that aim to teach a foundations about vector search:

https://vectorsearch.dev/

It's all in the Nim programming language, but if you prefer reading code or running diffs then you might get a vague sense of (some) low level nuts & bolts from: https://github.com/c-blake/nimsearch

Is there some better alternative to Knuth-Morris-Pratt or Boyer-Moore? Both can easily be adapted to regular expression matching and as far as I know there’s no faster algorithm that doesn’t do preprocessing.

Stanford's NLP course:

https://www.youtube.com/playlist?list=PLoROMvodv4rOSH4v6133s...

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Just use Postgres fulltext Search, its good enough http://rachbelaid.com/postgres-full-text-search-is-good-enou...