Chemistry Journals Miner


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Chemistry Journals is a new Minerazzi miner, available now at

This one allows users to search chemistry journals for science, technology, and interdisciplinary research. They can search by topic, title, or site.

A great tool for researchers, teachers, students, and professional chemists/chemical engineers.

Chemical Databases


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Chemical Databases is a new Minerazzi miner, where you can find chemical databases, search engines, encyclopedias, dictionaries, glossaries, and more. Search by topic, title, or site.

This miner is available at A great tool for students, teachers, researchers, chemists, and chemical engineers.

The US Army Miner


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The US Army Miner is now available at

Mine Army divisions, units, battalions, breaking news, military social media, and more. Build US Army specific collections. Search by military resource or location.

PS. Amazing news obtained through the News Center of this miner
Imagine controlling things or communicating to each others through our brain waves! Coming soon?

Expanding the News Miner: Find newspapers from around the World

We have expanded and reindexed the News miner, available at

Use this miner to find newspapers and news services from around the World, particularly North America and the Caribbean. Search by newspaper, news service, or location.

If you are a data miner or collection curator, use its extraction tools to find urls, links, images, emails, etc from targeted news stories, newspapers, or news organizations.

Google: Turning users into content curators


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Google turns users into content curators

As we said many times before at, these are the days of turning searchers into data miners.

The days of just one-way searching for the heck of searching or staring at a list of search results ended like about 15 years ago with the last century.

It took so much money, effort, and time for commercial search engines to realize that?! These are the days of two-way searching. Socials simply makes this so obvious.

Glad to see that Google is catching up with our thesis of turning searchers into data miners!!!

This makes even more easy for users to deploy Minerazzi as a collection curator for their Google accounts!

More Grant and Scholarship Resources


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We have reindexed and expanded the grants and scholarships miner available at

As usual, users can scrape search results to find zillion of urls, links, images, scripts, etc, to build curated collections or gather intelligence, without spending any budget in web scrapping services.

More educational miners will be available soon.

World Search Engines and Directories


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A new Minerazzi miner: World Search Engines and Directories (

Find all top generic and specialty search engines and directories from around the World. Search them all by region, country, name, industry, or topic.

Once you find a result, either mine its URL or visit it to keep searching.

Query Examples

Try the following queries with this miner:

[ africa search engine], [ Australia ], [ Yahoo ], [ travel], [ news ], etc


A Cosine Similarity Tool and Companion Tutorial


On Cosine Similarity

Cosine similarity is commonly used in data mining and information retrieval as a measure of the resemblance between data sets; i.e. how similar or alike these are. It is an important concept used in Vector Space Theory and affine models.

While there are many tools and tutorials on the subject out there, quite often what is missed from these is a clear explanation of the underlying meaning and nature of the variables involved.

Did you know that centering data sets by subtracting the corresponding variable means can and will impact the angle between them, and therefore, the corresponding cosine similarity? Did you know that said change can be used to assess whether the variables are orthogonal, uncorrelated, or both/neither? Do you know what a cosine similarity of zero actually mean?

All these and similar questions are addressed with our cosine similarity tool and companion tutorial. Access them now at



To use the tool simply enter two data sets and select how these are delimited. Then check whether you want to compute their cosine similarity by using them as given (raw mode) or by subtracting their mean (centered mode). To interpret the results from either mode, read the companion tutorial.