Smart research using Elasticsearch
More, Please

Websites often offer readers links to articles about similar topics. Using Elasticsearch, the free search engine, is one way to find related documents instantly and automatically.
When people rummage around on the StackOverflow website looking for advice on programming questions, they can find list of links to related topics in the Related section (Figure 1). This helps users if the first search result didn't show what they expected or the located resource is insufficient. According to Gormley and Tong [1], Elasticsearch [2] [3], the free search engine, generates these links on the website in real time from the growing and very impressive collection of 10 million StackOverflow contributions.

Artificial Brain
This isn't actual intelligence at work, because computers still find it difficult to understand the content of a document, meaning they can't find documents with related content. In fact, the algorithm used is based on simple nitpicking – it combines values for word frequency and derives a score from those values.
Elasticsearch uses an inverted index for this task; this index is a complete list of individual words that appear in any of the documents that have been added to the search engine so far. It remembers which document each word has been found in and can therefore instantly output a list of documents for a search term.
For example, if a user is looking for the term perl, Elasticsearch will immediately find the doc-1 document in the inverted index from Figure 2 and present this (one hopes) accurate search result.

When searching for two words (e.g., linux and cpan), two documents come into consideration, but because doc-2 only contains one term, whereas doc-3 contains both, the algorithm gives doc-3 a higher relevance score. In a match list sorted by descending score, doc-3 is then at the very top and is more likely to match the user's expectations.
What Is Relevant?
Not all words are equally important. For example, the word file understandably comes up in quite a large number of documents on computer topics. If the user searches for file linux cpan, doc-2 and doc-3 provide two matches each, but because linux is more significant for one document than file, the algorithm rates linux cpan higher than cpan file and gives doc-3 preference.
The Tf-idf score [4] determines how important a word is within a document. It gives a high value to those words that are prevalent in one document but do not occur too frequently in other documents competing for a high score (i.e., words that underpin the uniqueness of the document). A word's relevance value increases with the number of times the word appears in the document (this is known as term frequency, TF) and decreases if the word also appears in many other documents in the collection (IDF, inverse document frequency).
Searching for the Same
To find documents in the database that are similar to document x, Elasticsearch first extracts all relevant words from x, then forms a search query using these words and returns the results. Elasticsearch performs this search for similar documents using the more_like_this
query [5] command with very little programming required. However, all the relevant documents must be added to the index beforehand. I'll be using the official Perl client Search::Elasticsearch from CPAN for this.
Listing 3 (described later) wades through a directory of text files. These are stories from my Usarundbrief.com blog that I extracted from the home-grown content management system via another Perl script. Each text file corresponds to a blog entry – 877 messages accumulated over almost 20 years, which is why the directory contains 877 files. Listing 1 shows the shell output [6].
Listing 1
Feed Data
$ ls idx | wc -l 877 $ mlt-index Added 10-cents-for-a-grocery-bag.txt Added a-job-for-angelika.txt Added absurd-and-funny-american-tv-shows.txt ...
Buy this article as PDF
(incl. VAT)
Buy Linux Magazine
Direct Download
Read full article as PDF:
Price $2.95
Subscribe to our Linux Newsletters
Find Linux and Open Source Jobs
Subscribe to our ADMIN Newsletters
Find SysAdmin Jobs
News
-
MNT Seeks Financial Backing for New Seven-Inch Linux Laptop
MNT Pocket Reform is a tiny laptop that is modular, upgradable, recyclable, reusable, and ships with Debian Linux.
-
Ubuntu Flatpak Remix Adds Flatpak Support Preinstalled
If you're looking for a version of Ubuntu that includes Flatpak support out of the box, there's one clear option.
-
Gnome 44 Release Candidate Now Available
The Gnome 44 release candidate has officially arrived and adds a few changes into the mix.
-
Flathub Vying to Become the Standard Linux App Store
If the Flathub team has any say in the matter, their product will become the default tool for installing Linux apps in 2023.
-
Debian 12 to Ship with KDE Plasma 5.27
The Debian development team has shifted to the latest version of KDE for their testing branch.
-
Planet Computers Launches ARM-based Linux Desktop PCs
The firm that originally released a line of mobile keyboards has taken a different direction and has developed a new line of out-of-the-box mini Linux desktop computers.
-
Ubuntu No Longer Shipping with Flatpak
In a move that probably won’t come as a shock to many, Ubuntu and all of its official spins will no longer ship with Flatpak installed.
-
openSUSE Leap 15.5 Beta Now Available
The final version of the Leap 15 series of openSUSE is available for beta testing and offers only new software versions.
-
Linux Kernel 6.2 Released with New Hardware Support
Find out what's new in the most recent release from Linus Torvalds and the Linux kernel team.
-
Kubuntu Focus Team Releases New Mini Desktop
The team behind Kubuntu Focus has released a new NX GEN 2 mini desktop PC powered by Linux.