Half a croissant, on a plate, with a sign in front of it saying '50c'
h a l f b a k e r y
Naturally, seismology provides the answer.

idea: add, search, annotate, link, view, overview, recent, by name, random

meta: news, help, about, links, report a problem

account: browse anonymously, or get an account and write.

user:
pass:
register,


         

job matchmaking

It's not what you know, it's who you know.
  (+12, -1)(+12, -1)
(+12, -1)
  [vote for,
against]

While there are many job databases geared towards matching acronyms in my resume with those in an employer's ads, there don't seem to be any that keep track of my single most important factor in a choice of job - who already works there.

In my fictitious database, users sign up, get an ID, and submit (and keep updated) four things:

(a) A resume.
(b) A selection from a set list of keywords that describes the person's expertise.
(c) A list of people they never want to work with again.
(d) A list of people they would enjoy working with.

Based on this information, scientists can begin collaborations if they like each other's work, without having to go through the usual courtship of conferences. If they like each other, they're told; if they're not told, it may be because of one of them not being in the system, rather than of outright dislike, so there's no direct rejection.

Based on this information, employers can find stable groups of people, not just single people, that work well together, or are interested in each other. Answering a request like "I'd like a four-person research department with a tendency towards AI and Human Interfaces" becomes solveable by a simple matchmaking algorithm.

(Problem: the data in such a database would be so precious that I'm not sure anyone would trust a company with it; realistic opinions about how desirable a co-worker an employee is would be used to evaluate employees, not just find matches.)

jutta, Mar 10 2001

Instant Background Checks for All http://www.halfbake...0Checks_20For_20All
A different kind of personal rating service. [egnor, Mar 10 2001]


Please log in.
If you're not logged in, you can see what this page looks like, but you will not be able to add anything.



Annotation:







       I could imagine collaborative-filtering systems which would make recommendations. "You don't actually know anyone at this company, but based on what you think of the people you do know (and a complex flow graph algorithm), you're likely to (like|dislike) the people working there." Of course, this could generalize to more than co-workers.
egnor, Mar 10 2001, last modified Mar 11 2001
  

       [egnor] - I rather like the idea of 'collaborative-flirting systems' that would recommend people I'd like... Oh, wait. Misread it. Nuts.
Chance, Jun 21 2002
  

       Cool. Get it set up and I'll be able to use it when I'm old enough to go looking for proper jobs
kaz, Jun 22 2002
  


 

back: main index

business  computer  culture  fashion  food  halfbakery  home  other  product  public  science  sport  vehicle