Clustering Algorithms and Classification Techniques for More Precise Results

How machine learning algorithms can give your employees and customers a better search experience.

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When do you use clustering algorithms?

When do you use classification techniques?

Here’s our quick video that explains the difference between the two and when you might use each.

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For Digital Commerce

“By 2022, at least 5% of digital commerce orders will be predicted and initiated by AI.” (Gartner)

Shoppers don’t always use the “right” words to find what they want. Clustering and classification delivers an optimal shopping experience to every customer showing them the right items at the right time – and predicting what they might buy next.

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For the Digital Workplace

“More than half of global information workers are interrupted from their work a few times or more per month to spend time looking for or trying to get access to information, insights, and answers.” (Forrester)

Clustering and classification gives employees the exact data and documents they’re looking for – faster and with higher precision.

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Amazon reports 35% of their sales come from their recommendations system.


What Are Clustering and Classification?

Clustering and classification are machine learning methods for finding the similarities – and differences – in a set of data or documents. These methods can be used for such tasks as grouping products in a product catalog, finding cohorts of similar customers, or aggregating sets of documents by topic, team, or office.

Supervised vs Unsupervised Learning

Classifications take a set of data that you’ve already manually analyzed and labeled and uses that to train a learning model to then examine a set of new data. This is called supervised learning.

Clustering on the other hand, doesn’t require an existing data set that’s been labeled by humans but still tries to find the groupings and differences in the data. This is called unsupervised learning.

The Crisis of Unlabeled Data

Without clustering algorithms and classification techniques, search results become watered down and non-specific. Business users and admins have to spend too much time manually adjusting relevancy and precision. Let machine learning do the work so you can focus your time and resources where they matter most.

Clustering and Classification in Ecommerce

Clustering and classification are important tools to provide a satisfying shopping experience for every customer. Learn more with this in-depth blog post exploring the retailers and ecommerce.

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Fusion Makes Clustering and Classification Easy

Lucidworks Fusion ships with clustering and classification algorithms that are pre-tuned by our data scientists drawing on our expertise with customers around the world. These machine learning methods include popular algorithms and approaches like:





K MeansClustering

K-Means Clustering

K NearestNeighbors

K-Nearest Neighbors


Decision Trees


Logistic Regression


Naive Bayes Modeling

Fusion’s AI capabilities give you full insight and control to test, configure, and deploy these methods to your applications to give every user more precise search results.

Elements of AI-Powered Search

Augmented Intelligence

There’s nothing artificial about intelligence. Augmented intelligence is when AI extends human judgement instead of replacing it.

Machine Learning

Learn how machine learning and search engines are a incredible combination for creating powerful experiences for customers and employees.

Clustering & Classification

How clustering and classification algorithms can improve the search experience for your employees and customers.

Query Analysis

Underperforming queries aggravate everyone. Head/tail analysis stops it.

Signal Capture & User Behavior

Users are constantly telling you what they like and what they don’t. Are you listening?


Some users know exactly what they’re looking for – almost. With every query, facets give every user a more precise set of results.


The best search applications index all of a company’s data so users have one unified search experience.


Personalization is about addressing people by name. Hyper-personalization is figuring out what they really want.

Build AI-Powered Apps With Fusion

Ready to create amazing search and data discovery apps? Contact us today to learn how Fusion can help you and our team put the power of AI, machine learning, and deep learning to work to  dazzle your customers and empower your employees.

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