In particular, the advent of Deep Learning introduced the use of deep neural networks to solve complex problems that were very challenging for classic algorithms.įor the sake of this blog post, it suffices to know that Deep Learning can be used to produce a vector representation of both the query and the documents in a corpus of information.
#Apache lucene solr software#
With the strong and steady advance of computer power in the recent past, AI has seen a resurgence and it is now used in many domains, including software engineering and Information Retrieval (the science that regulates Search Engines and similar systems).
When we talk about AI we are referring to a set of techniques that enable machines to learn and show intelligence similar to humans. More and more frequently, we hear about how Artificial Intelligence (AI from now on) permeates many aspects of our lives. Neural Search is an industry derivation from the academic field of Neural information Retrieval, and it focuses on improving any of these areas with neural network based techniques.Īrtificial Intelligence, Deep Learning and Vector Representations assign a score to each matched document in order to establish a meaningful document ranking by relevance in the results.
It relies on the Apache Lucene implementation for K-nearest neighbor search. The first milestone for Neural Search in Apache Solr has been contributed to the open source community by Sease with the work of Alessandro Benedetti(Apache Lucene/Solr PMC member and committer) and Elia Porciani(Sease R&D software engineer).
0 kommentar(er)
