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Home/ Questions/Q 942275
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Editorial Team
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Editorial Team
Asked: May 15, 20262026-05-15T22:14:47+00:00 2026-05-15T22:14:47+00:00

In an app that i’m creating, I want to add functionality that groups news

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In an app that i’m creating, I want to add functionality that groups news stories together. I want to group news stories about the same topic from different sources into the same group. For example, an article on XYZ from CNN and MSNBC would be in the same group. I am guessing its some sort of fuzzy logic comparison. How would I go about doing this from a technical standpoint? What are my options? We haven’t even started the app yet, so we aren’t limited in the technologies we can use.

Thanks, in advance for the help!

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  1. Editorial Team
    Editorial Team
    2026-05-15T22:14:48+00:00Added an answer on May 15, 2026 at 10:14 pm

    This problem breaks down into a few subproblems from a machine learning standpoint.

    First, you are going to want to figure out what properties of the news stories you want to group based on. A common technique is to use ‘word bags’: just a list of the words that appear in the body of the story or in the title. You can do some additional processing such as removing common English “stop words” that provide no meaning, such as “the”, “because”. You can even do porter stemming to remove redundancies with plural words and word endings such as “-ion”. This list of words is the feature vector of each document and will be used to measure similarity. You may have to do some preprocessing to remove html markup.

    Second, you have to define a similarity metric: similar stories score high in similarity. Going along with the bag of words approach, two stories are similar if they have similar words in them (I’m being vague here, because there are tons of things you can try, and you’ll have to see which works best).

    Finally, you can use a classic clustering algorithm, such as k-means clustering, which groups the stories together, based on the similarity metric.

    In summary: convert news story into a feature vector -> define a similarity metric based on this feature vector -> unsupervised clustering.

    Check out Google scholar, there probably have been some papers on this specific topic in the recent literature. A lot of these things that I just discussed are implemented in natural language processing and machine learning modules for most major languages.

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