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Show HN: A bookmark manager that uses TF-IDF vectors to group similar bookmarks

8 points by devinhn 6y ago

devinhn 6y ago
Hello!, Everyone I know has a bookmark graveyard of bits of interesting information we wanted to come back to later but added into a general folder that ends up being a mess. So I did what any good ML student would do and built a simple ML system (using TF-IDF vectors) that will recommend you similar bookmarks. I use Obsidian.md as my second brain but needed a space to put the interesting links without spending the time to create a new note incorporate it into my organizational system. I think lxi.ai does a good job of being the middle ground for holding the interesting links for me to come back to when I really want to wrestle with the ideas. Hope some people like it too! website: https://lxi.ai/ https://lxi.ai/ chrome extension: https://chrome.google.com/webstore/detail/lxiai/dkhfhajlhegdenbhkejkbagnlkgjnpcl?hl=en https://chrome.google.com/webstore/detail/lxiai/dkhfhajlhegd... firefox addon: https://addons.mozilla.org/addon/lxi-ai/ https://addons.mozilla.org/addon/lxi-ai/
shaggy8871 6y ago
That’s pretty cool, going to give it a try.
rasulkireev 6y ago
Looks very good, will certainly give it a try. I am assuming you built this with Python, right? Any chance you can share the approach? Would love to try building something for the web with the use of Tensorflow.
- devinhn 6y ago
  Hey thanks for giving it a try! And yes, built it with python - specifically I'm using a modified version of gensim's TF-IDF model implementation. If you haven't heard of TF-IDF before give http://www.tfidf.com/ http://www.tfidf.com/ a read through. It might be overkill to use tensorflow for TF-IDF, but go for it! With lxi.ai, I use the top 10 most important keywords for the actual comparison along with some other tricks to make sure the model can scale. Might be worth a blog post or something.
  - rasulkireev 6y ago
    Thanks. Found a small bug. I've added a few bookmarks and when I press the Random Bookmark link I get an Internal Server Error at this url (https://lxi.ai/bookmarks/achieve https://lxi.ai/bookmarks/achieve): ``` The server encountered an internal error and was unable to complete your request. Either the server is overloaded or there is an error in the application. ```
    - devinhn 6y ago
      Ah yes that makes sense - it'll be fixed within the hour.
  - rasulkireev 6y ago
    - How did build the graph view, looks very good? - Did you use Python to build the Chrome addon, too? If so, do you mind sharing a resource where I can see how to do that, cause when I was looking, did not find anything. Thanks a ton in advance.
    - devinhn 6y ago
      The graph is built with D3.js and some minor JS/CSS changes to create the hover effects. The extensions are built with simple html/js/css - they're basically mini webpages with special permissions. For example, I use an activeTab api provided by the browser to read the page text when the user clicks a button. I recommend google's getting started docs: https://developer.chrome.com/docs/extensions/mv3/getstarted/ https://developer.chrome.com/docs/extensions/mv3/getstarted/ Or find a youtube video and follow along!

8 points by devinhn 6y ago

Hello!, Everyone I know has a bookmark graveyard of bits of interesting information we wanted to come back to later but added into a general folder that ends up being a mess. So I did what any good ML student would do and built a simple ML system (using TF-IDF vectors) that will recommend you similar bookmarks. I use Obsidian.md as my second brain but needed a space to put the interesting links without spending the time to create a new note incorporate it into my organizational system. I think lxi.ai does a good job of being the middle ground for holding the interesting links for me to come back to when I really want to wrestle with the ideas. Hope some people like it too! website: https://lxi.ai/ https://lxi.ai/ chrome extension: https://chrome.google.com/webstore/detail/lxiai/dkhfhajlhegdenbhkejkbagnlkgjnpcl?hl=en https://chrome.google.com/webstore/detail/lxiai/dkhfhajlhegd... firefox addon: https://addons.mozilla.org/addon/lxi-ai/ https://addons.mozilla.org/addon/lxi-ai/

shaggy8871 6y ago

That’s pretty cool, going to give it a try.

rasulkireev 6y ago

Looks very good, will certainly give it a try. I am assuming you built this with Python, right? Any chance you can share the approach? Would love to try building something for the web with the use of Tensorflow.

devinhn 6y ago
Hey thanks for giving it a try! And yes, built it with python - specifically I'm using a modified version of gensim's TF-IDF model implementation. If you haven't heard of TF-IDF before give http://www.tfidf.com/ http://www.tfidf.com/ a read through. It might be overkill to use tensorflow for TF-IDF, but go for it! With lxi.ai, I use the top 10 most important keywords for the actual comparison along with some other tricks to make sure the model can scale. Might be worth a blog post or something.
- rasulkireev 6y ago
  Thanks. Found a small bug. I've added a few bookmarks and when I press the Random Bookmark link I get an Internal Server Error at this url (https://lxi.ai/bookmarks/achieve https://lxi.ai/bookmarks/achieve): ``` The server encountered an internal error and was unable to complete your request. Either the server is overloaded or there is an error in the application. ```
  - devinhn 6y ago
    Ah yes that makes sense - it'll be fixed within the hour.
- rasulkireev 6y ago
  - How did build the graph view, looks very good? - Did you use Python to build the Chrome addon, too? If so, do you mind sharing a resource where I can see how to do that, cause when I was looking, did not find anything. Thanks a ton in advance.
  - devinhn 6y ago
    The graph is built with D3.js and some minor JS/CSS changes to create the hover effects. The extensions are built with simple html/js/css - they're basically mini webpages with special permissions. For example, I use an activeTab api provided by the browser to read the page text when the user clicks a button. I recommend google's getting started docs: https://developer.chrome.com/docs/extensions/mv3/getstarted/ https://developer.chrome.com/docs/extensions/mv3/getstarted/ Or find a youtube video and follow along!