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You're reading from  Vector Search for Practitioners with Elastic

Product typeBook
Published inNov 2023
PublisherPackt
ISBN-139781805121022
Edition1st Edition
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Authors (2):
Bahaaldine Azarmi
Bahaaldine Azarmi
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Bahaaldine Azarmi

Bahaaldine Azarmi, Global VP Customer Engineering at Elastic, guides companies as they leverage data architecture, distributed systems, machine learning, and generative AI. He leads the customer engineering team, focusing on cloud consumption, and is passionate about sharing knowledge to build and inspire a community skilled in AI.
Read more about Bahaaldine Azarmi

Jeff Vestal
Jeff Vestal
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Jeff Vestal

Jeff Vestal has a rich background spanning over a decade in financial trading firms and extensive experience with Elasticsearch. He offers a unique blend of operational acumen, engineering skills, and machine learning expertise. As a Principal Customer Enterprise Architect, he excels at crafting innovative solutions, leveraging Elasticsearch's advanced search capabilities, machine learning features, and generative AI integrations, adeptly guiding users to transform complex data challenges into actionable insights.
Read more about Jeff Vestal

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Evolution of search experience

We are now going to see how users’ demand for a better search experience requires us to consider other techniques than just keyword-based search. In this section, we will approach the limitations of keyword-based search, understand what vector representation entails, and how the meta representation HNSW emerged to facilitate information retrieval with vector.

The limits of keyword-based search

For those of you who are comparatively new to the subject matter, before we talk about vector representation, we need to understand why the industry and keyword-based search experience have reached their limits, failing to fully meet end-user requirements.

Keyword-based search relies on exact matches between the user query and the terms contained in documents, which could lead to missed relevant results if the search system is not refined enough with synonyms, abbreviations, alternative phrasings, and so on. Therefore, it is important for the search...

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Vector Search for Practitioners with Elastic
Published in: Nov 2023Publisher: PacktISBN-13: 9781805121022

Authors (2)

author image
Bahaaldine Azarmi

Bahaaldine Azarmi, Global VP Customer Engineering at Elastic, guides companies as they leverage data architecture, distributed systems, machine learning, and generative AI. He leads the customer engineering team, focusing on cloud consumption, and is passionate about sharing knowledge to build and inspire a community skilled in AI.
Read more about Bahaaldine Azarmi

author image
Jeff Vestal

Jeff Vestal has a rich background spanning over a decade in financial trading firms and extensive experience with Elasticsearch. He offers a unique blend of operational acumen, engineering skills, and machine learning expertise. As a Principal Customer Enterprise Architect, he excels at crafting innovative solutions, leveraging Elasticsearch's advanced search capabilities, machine learning features, and generative AI integrations, adeptly guiding users to transform complex data challenges into actionable insights.
Read more about Jeff Vestal