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Cool, but for each of these properties that knwl.js finds there are done extensive research and none of them are easy to do well. Sure, in the demo you find som

Cool, but for each of these properties that knwl.js finds there are done extensive research and none of them are easy to do well. Sure, in the demo you find some interesting properties, but it's content was chosen by the author. E.g. in the emotion-detection instead of using a data set such as http://sentiwordnet.isti.cnr.it/ http://sentiwordnet.isti.cnr.it/ the author defines the following data structures: this.emotion.negativeWords = ['terrible','horrible','evil','die','dick','bitch','fucked','stupid','idiot','dumb','noob','shit','vain','n00b','dickhead','cocksucker','disgusting','slut']; this.emotion.negativeWordsB = ['fuck','shit','kill','rape','hate','hating']; this.emotion.positiveWords = ['happy','good','great','amazing','awesome','wonderful','brilliant','smart']; this.emotion.positiveWordsB = ['love','like','want',"<3",'kiss']; Which perhaps functions well, but in a very limited domain. The same can be said for detection of spam, phone numbers (only find American numbers in a certain format atm) etc.

guptaneil 13y ago
As with most projects that deal with parsing natural language, it works best when optimized for your use case. For example, I created a natural language date parsing library [https://github.com/Tabule/Sherlock https://github.com/Tabule/Sherlock] that is great at parsing events for entering into a calendar, but would fail if tested against an entire news article. The cool thing about knwl is that it is open-source and the code is very clean, meaning you can easily optimize it for your use case. Knwl lays the ground work for somebody to build a smarter parser into their app.
- c16 13y ago
  + 1. I fully agree here, parsing for events data, parsing a news article or parsing tweets are all very different tasks and each one requires different optimizations. An interesting project regardless, I'll likely be using this in the near future.
- rdgiii 13y ago
  This is what I immediately thought of. They've built a nice small library that can be used as a framework for something more detailed and involved, which is fantastic.

guptaneil 13y ago

As with most projects that deal with parsing natural language, it works best when optimized for your use case. For example, I created a natural language date parsing library [https://github.com/Tabule/Sherlock https://github.com/Tabule/Sherlock] that is great at parsing events for entering into a calendar, but would fail if tested against an entire news article. The cool thing about knwl is that it is open-source and the code is very clean, meaning you can easily optimize it for your use case. Knwl lays the ground work for somebody to build a smarter parser into their app.

c16 13y ago
+ 1. I fully agree here, parsing for events data, parsing a news article or parsing tweets are all very different tasks and each one requires different optimizations. An interesting project regardless, I'll likely be using this in the near future.
rdgiii 13y ago
This is what I immediately thought of. They've built a nice small library that can be used as a framework for something more detailed and involved, which is fantastic.