Automatic Entrepreneur: Difference between revisions

From Computer Laboratory Group Design Projects
Jump to navigationJump to search
No edit summary
No edit summary
Line 1: Line 1:
Client (t.b.c.): Daniel Organisciak, Luminance <daniel.organisciak@luminance.com>
Client: �aniel Organisciak, Luminance <daniel.organisciak@luminance.com>
 
Current draft (t.b.c.) as follows ...


The skill of a business entrepreneur is turning a few key terms, and some names of people and places, together with some financial figures, into a compelling narrative. Until now, it has been time consuming to manually extract relevant names and figures from reports filed at Companies House. It requires hard thought and creativity to write about the business opportunity. Your project has two parts. The first is automatic extraction of pertinent information from company filings, using methods such as syntactic parsers or named entity recognition. The second part is to use a combination of visual design and generative language models to create web pages that pitch the business to new investors, or perhaps provide the template for a competing start-up.
The skill of a business entrepreneur is turning a few key terms, and some names of people and places, together with some financial figures, into a compelling narrative. Until now, it has been time consuming to manually extract relevant names and figures from reports filed at Companies House. It requires hard thought and creativity to write about the business opportunity. Your project has two parts. The first is automatic extraction of pertinent information from company filings, using methods such as syntactic parsers or named entity recognition. The second part is to use a combination of visual design and generative language models to create web pages that pitch the business to new investors, or perhaps provide the template for a competing start-up.

Revision as of 14:58, 28 October 2022

Client: �aniel Organisciak, Luminance <daniel.organisciak@luminance.com>

The skill of a business entrepreneur is turning a few key terms, and some names of people and places, together with some financial figures, into a compelling narrative. Until now, it has been time consuming to manually extract relevant names and figures from reports filed at Companies House. It requires hard thought and creativity to write about the business opportunity. Your project has two parts. The first is automatic extraction of pertinent information from company filings, using methods such as syntactic parsers or named entity recognition. The second part is to use a combination of visual design and generative language models to create web pages that pitch the business to new investors, or perhaps provide the template for a competing start-up.