15 Jun 2018
Working as a search engineer myself I decided to develop a framework for finding optimal query weights for search engines like Elasticsearch or Solr. It is based on a machine learning branch called genetic programming, inspired by the process of natural selection. In this post I’ll describe it and briefly discuss how the good process of building the quality of search should look like. Let’s start!
27 Aug 2017
Although Solr comes with standard tokenizer implementation, which is well prepared to tokenize most of the texts, there are cases when it is helpless. Imagine a document with many numbers, of which many are followed by percentage sign. In a certain contexts it is expected to distinguish queries that refer to those percentages & plain numbers. How to achieve that? We need a custom tokenizer.
30 Mar 2017
Algorithms for extracting entities from text are ones of the most crucial aspects of text analysis. They lead to better understanding of the content, enable additional operations like filtering or grouping and - most importantly - allow to process data automatically. In the previous post I announced combination of text indexing & such extraction and in order to keep my promise I created a fork of Solr Text Tagger.
19 Feb 2017
The process of indexing in Solr in an advanced topic covered by many publications. On the most basic level it can be described as putting data into previously prepared containers. But what if user wants to perform additional data processing depending on documents that already are in the index?
31 Oct 2016
Recently, going through the Spring MVC documentation, I found a feature I haven’t previously used - asynchronous request processing. It is an addition of Servlet 3 API and a part of Java EE since its sixth edition from 2009; Spring started support it three years later. As it looks interesting (and as async is a popular word in developer’s journey since at least early Web 2.0 days) I decided to go deeper into details of it.