DiceTechJobs/VectorsInSearch

Dice.com repo to accompany the dice.com 'Vectors in Search' talk by Simon Hughes, from the Activate 2018 search conference, and the 'Searching with Vectors' talk from Haystack 2019 (US). Builds upon my conceptual search and semantic search work from 2015

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This project helps search engineers and data scientists build extremely fast and relevant search experiences using advanced vector search techniques. It takes high-dimensional data, often representing concepts or items, and processes it to enable rapid, 'conceptual' matches. The output is a highly optimized search system capable of returning the most semantically similar results quickly, even with massive datasets.

No commits in the last 6 months.

Use this if you need to build a search system that can find conceptually similar items or documents extremely fast, even when dealing with large volumes of complex data points like job descriptions or product features.

Not ideal if your search needs are limited to basic keyword matching or if you are not working with vector-based data representations.

semantic-search information-retrieval search-relevance data-matching search-optimization
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 17 / 25

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Stars

86

Forks

15

Language

Python

License

Apache-2.0

Last pushed

May 12, 2021

Commits (30d)

0

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