I've been working on a completely data-driven spinner, accessible as an API, and I'm currently looking for testers.
How is this spinner different from existing ones? It doesn't use a thesaurus. Instead, similarities in word meaning, rules of grammar, and probabilities of words occurring in a given context are all estimated using state-of-the-art NLP approaches paired with (gigabytes of) training data, currently coming from a variety of free sources, including Wikipedia, product reviews, and PLR articles. This has its ups and downs... but by far the biggest advantage is scalability: improving the average quality is often as simple as throwing more data in.
This means that the quality of results depends on expanding and balancing out the training data - and that's where you come in. I need some field testers to evaluate how well the spinner handles different kinds of content so I can balance out the data it's trained on, as well as get general feedback on quality, usability, and errors.
Who I'm looking for
What I want you to do
Feedback I'm looking for
Interactive demo (with sample articles, just to show off general quality & current customization):
http://jespersen.pythonanywhere.com/vectordemo
Contact (for actually testing the API):
E-mail: [email protected]
Or just leave a reply here or send me a PM if you're interested.
I'm looking for around 10 people, first come first served as long as you think you qualify and you're willing to give serious feedback and respond to updates.
How is this spinner different from existing ones? It doesn't use a thesaurus. Instead, similarities in word meaning, rules of grammar, and probabilities of words occurring in a given context are all estimated using state-of-the-art NLP approaches paired with (gigabytes of) training data, currently coming from a variety of free sources, including Wikipedia, product reviews, and PLR articles. This has its ups and downs... but by far the biggest advantage is scalability: improving the average quality is often as simple as throwing more data in.
This means that the quality of results depends on expanding and balancing out the training data - and that's where you come in. I need some field testers to evaluate how well the spinner handles different kinds of content so I can balance out the data it's trained on, as well as get general feedback on quality, usability, and errors.
Who I'm looking for
- members who regularly use spin, preferably if you use existing commercial spinners
- members who have experience with API endpoints/sending out automated requests
What I want you to do
- test out the current (very basic) spinner API (I'll PM/e-mail you the details with the instructions for accessing the API)
Feedback I'm looking for
- reports on any bugs, crashes, and errors
- thoughts on performance: do you find it tolerable, or would you prioritize improving it over other things
- missing vocabulary & niches: notify me of any topics where the vocabulary either isn't spun, or gets replaced with unrelated words (e.g. if vocabulary related to tattoos in your content gets replaced with nonsense or unrelated stuff)
- also: point out any systematic nonsense which gets thrown in (e.g. references to petroleum or Spiderman in articles about fitness)
- general feedback on how the spinner compares with what you're currently using, how well it fares against Copyscape for your type of content, thoughts on the current settings, feature requests, etc.
Interactive demo (with sample articles, just to show off general quality & current customization):
http://jespersen.pythonanywhere.com/vectordemo
Contact (for actually testing the API):
E-mail: [email protected]
Or just leave a reply here or send me a PM if you're interested.
I'm looking for around 10 people, first come first served as long as you think you qualify and you're willing to give serious feedback and respond to updates.