categorization   799

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Robin: “How we organize GitHub issues: A simple styleguide for tagging”
“For people who make software, the internet has no shortage of best practice for workflow organization like Git Flow, release versioning, GitHub, etc. When you get to the topic of issue management, the reading material plummets.

At Robin, GitHub issues are the core of just about every action the team takes. Over the past year, we’ve worked out an internal tagging system that keeps engineering and product efforts organized across repositories on Github. We’re sharing the current iteration (and it will keep changing) in case your team is looking for some workflow inspiration.”
via:sam-richard  tagging  ontology  organization  categorization  github  zenhub 
5 weeks ago by BillHiggins
Johnny.Decimal home · J•D
Step 1: Divide everything in to ten things
Take everything you need to organise and sort it in to, at most, ten large buckets.
Make sure the buckets are unambiguously different.
Put a label on each bucket.
This forces you to group things quite broadly, but that’s the point.

We call these buckets your areas. An area might be Finance.

Step 2: In each area, divide in ten again
Go through each bucket and repeat the process. This creates your categories.

A category within the Finance area might be Tax Returns.

Now we have ten areas which contain ten categories each. That’s a hundred categories at the very most. It’s very unlikely you will end up with a hundred categories.

Categories are the key
What’s a category? It’s just a collection of stuff. Book drafts. Travel itineraries. Lease agreements. Test reports. Contracts. Any type of work you do can become a category.

The point is that you’ve defined these categories, each of which is contained within a broader area. You do this when you set up your system, which we’ll get to shortly.
notes  productivity  curation  categorization  archive 
january 2019 by euler
Safe Web Search and Secure Browsing | WOT (Web of Trust)
Web of Trust (MyWOT) offers free tools for safe search and web browsing. Ratings are based on a community of over 140M users and machine learning algorithms.
text  analysis  mediashift  classification  categorization  content 
december 2018 by kpieper876
Natural Language Understanding - IBM Cloud API Docs
API Docs lists the documentation of the APIs supported on IBM Cloud.
text  analysis  mediashift  classification  categorization  content 
december 2018 by kpieper876
inCompass | your OEM partner in web filtering and security
inCompass®, the Most Comprehensive Web Categorization and Filtering Technology Used by Mobile Operators, Service Providers, Gateway Appliance Vendors, UTM vendors, AV/Spam/Phishing, Advertising and Publishing Platforms, Content IAB Tier 1 IAB Tier 2 IAB Content Rating IAB Non-Standard Content IAB Marketing Knowledge Solutions, Big Data Analytics …
text  analysis  mediashift  classification  categorization  content 
december 2018 by kpieper876
GumGum | Applied Computer Vision
GumGum is a leading computer vision company on a mission to unlock the value of every online image and video for marketers using patented image-recognition technology.
computer  vision  image  video  analysis  categorization  mediashift 
december 2018 by kpieper876

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