Conservation Evidence Synthesis: Difference between revisions
From Computer Laboratory Group Design Projects
Jump to navigationJump to search
(Created page with "Client: Thomas White <tbw27@cam.ac.uk> Many published descriptions of conservation projects contain information about the actions that were taken, what they cost, and how eff...") |
No edit summary |
||
| (One intermediate revision by the same user not shown) | |||
| Line 1: | Line 1: | ||
Client: Thomas White <tbw27@cam.ac.uk> | Client: Thomas White, [[BioRISC]] <tbw27@cam.ac.uk> | ||
Many published descriptions of conservation projects contain information about the actions that were taken, what they cost, and how effective the results were. However, it’s impossible for one person to find and digest the corresponding pieces of evidence when the relevant publications can be so varied in format and length. Your task is to use natural language processing methods to assemble the most important quantitative and qualitative data, and generate short and approachable texts communicating the essentials of each publication. | Many published descriptions of conservation projects contain information about the actions that were taken, what they cost, and how effective the results were. However, it’s impossible for one person to find and digest the corresponding pieces of evidence when the relevant publications can be so varied in format and length. Your task is to use natural language processing methods to assemble the most important quantitative and qualitative data, and generate short and approachable texts communicating the essentials of each publication. | ||
Latest revision as of 11:37, 18 October 2021
Client: Thomas White, BioRISC <tbw27@cam.ac.uk>
Many published descriptions of conservation projects contain information about the actions that were taken, what they cost, and how effective the results were. However, it’s impossible for one person to find and digest the corresponding pieces of evidence when the relevant publications can be so varied in format and length. Your task is to use natural language processing methods to assemble the most important quantitative and qualitative data, and generate short and approachable texts communicating the essentials of each publication.
