Discovering patterns from chaotic datasets, albeit via Graph Theory techniques (instead of ML) for populating a knowledge graph. e.g., find commonalities among documents, such as a single occurrence of a common phrase in each that connects otherwise obscure papers.
This technique is well suited for datasets with insufficient features for machine learning...
Initial tech focus was on finding commonalities within a set of documents, such as by crawling all links on first 10 pages of Google search via their CSE API. Next search optionally increases the pool.
Initial business focus was for marketers, who not only know their pain but are willing to pay to make that pain go away.
Nothing unique about the market... but with Lean Interviews and with 100% hit rate for interest among the 40 highly qualified leads, it seemed like a simple matter of assembling various bits that we had each previously built.
Lessons learned:
Even if a long-time friend commits to joining, has the financial means to contribute several months, owes you the personal favour to do so, etc., etc.-- Don't bank on that.
Like a perfect storm, I had multiple friends who previously committed to assisting, then each suddenly experienced extenuating circumstances preventing them from joining. One would have been our NLP lead-- ouch!
More mundane lessons learned captured in articles:
This technique is well suited for datasets with insufficient features for machine learning...
Initial tech focus was on finding commonalities within a set of documents, such as by crawling all links on first 10 pages of Google search via their CSE API. Next search optionally increases the pool.
Initial business focus was for marketers, who not only know their pain but are willing to pay to make that pain go away.
Nothing unique about the market... but with Lean Interviews and with 100% hit rate for interest among the 40 highly qualified leads, it seemed like a simple matter of assembling various bits that we had each previously built.
Lessons learned:
Even if a long-time friend commits to joining, has the financial means to contribute several months, owes you the personal favour to do so, etc., etc.-- Don't bank on that.
Like a perfect storm, I had multiple friends who previously committed to assisting, then each suddenly experienced extenuating circumstances preventing them from joining. One would have been our NLP lead-- ouch!
More mundane lessons learned captured in articles:
https://play.org/articles/new-entrepreneur-checklist
https://play.org/articles/introduction-to-natural-language-p... (i.e., unlearning misconceptions about "synonyms" to fully deployed with spaCy.io)