Alessandro Benedetti

Following his passion he entered the Apache Lucene and Solr world in 2010 becoming an active member of the community and Apache Lucene/Solr Committer and PMC member.
Experience with a great variety of clients has taught him to be a proficient and professional consultant.
Recently Alessandro has contributed Neural Search to Apache Solr and worked on integrating Apache Solr’s Learning To Rank in various company ecosystems with the aim of improving search result relevancy.
Prior to that he designed and developed an enterprise semantic search engine known as Sensefy using approaches such as Named Entity Recognition at indexing time, advanced autocompletion, and document similarity metrics.


Company/Organisation

Sease


Sessions

06-19
14:00
40min
Introducing Multi-valued Vector Fields in Apache Lucene
Alessandro Benedetti

Multiple vectors in a field dedicated to K-nearest-neighbors search has been a fundamental problem for Apache Lucene for long.
This talk describes how this has been finally designed and implemented.

Kesselhaus