Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Encoding reputation
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > CRM > Encoding reputation
CRM

Encoding reputation

Editor SDC
Editor SDC
4 Min Read
SHARE

Go Big Always – Enterprise Data Portability needs a Reputation Standard

Sam Lawrence on ways of encoding reputation, and why that might be a good thing.

I’ve speculated about this before — in fact, I think it would be a killer attribute for SOA, and is therefore much more broadly interesting than Sam suggests. To wit:

One of the under represented aspects of the natural needs of a service oriented environment is credibility. In the ideal SOA world, your component goes out, “into the wild”, searching for a service implementation that matches a specific interface and provides certain information. What does your component do if it finds multiple implementations, each of which meets all of your other selection criteria, such as performance, cost, completeness, whatever. Under such circumstances, you’d need to make a judgement based on something quite similar (if not identical) to credibility in human relationships — what is the reputation of service X compared to service Y? Who do you believe?

So let’s play the scenario out — how would our theoretical agent/component, in some futuristic SOA environment, deal with such fuzzy choices? I think one possible valid solution would be …

More Read

Transforming 100 Blog Posts into 1 Wordle
Identity Mixer: better online identity management?
Twitter gains salesforce.com support, anticipating the next great thing?
Join the Social CRM Pioneers!
Social Media vs Social CRM vs Social Business vs Enterprise 2.0

Go Big Always – Enterprise Data Portability needs a Reputation Standard

Sam Lawrence on ways of encoding reputation, and why that might be a good thing.

I’ve speculated about this before — in fact, I think it would be a killer attribute for SOA, and is therefore much more broadly interesting than Sam suggests. To wit:

One of the under represented aspects of the natural needs of a service oriented environment is credibility. In the ideal SOA world, your component goes out, “into the wild”, searching for a service implementation that matches a specific interface and provides certain information. What does your component do if it finds multiple implementations, each of which meets all of your other selection criteria, such as performance, cost, completeness, whatever. Under such circumstances, you’d need to make a judgement based on something quite similar (if not identical) to credibility in human relationships — what is the reputation of service X compared to service Y? Who do you believe?

So let’s play the scenario out — how would our theoretical agent/component, in some futuristic SOA environment, deal with such fuzzy choices? I think one possible valid solution would be to provide a mechanism to “change our minds”. By that, I mean the agent would need to be able to do something along the lines of the following:

  • Evaluate the various offerings from the various available services
  • After filtering on the “objective” criteria (method signature, QOS promises, etc), if there are still multiple choices, apply “subjective” criteria, such as reputation, degree of satisfaction with past performance, and so on.
  • If there is still no distinct choice at this point, decide at random, AND (and here is the critical bit) “remember” the alternatives in some persistent way
  • If, at some later point in time, we become dissatisfied with the answer we received from the service we selected, we would invoke a kind of exception handling/rollback sort of mechanism, and “change our mind” — we switch to the alternative service.

Note that, to really model halfway human behaviour here, we’d need some sort of polling mechanism as well, in that last step — we’d need a way to “keep an eye on” the alternatives, as one possible motivation for “changing our mind” might be as simple as one of the alternatives suddenly offering a superior solution.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

power supplies for ATX for data scientists
Why Data Scientists Should Care About SFX Power Supplies
Big Data Exclusive
AI for website optimization
Free Tools to Test Website Accessibility
Artificial Intelligence Exclusive
Generative AI models
Thinking Machines At Work: How Generative AI Models Are Redefining Business Intelligence
Artificial Intelligence Business Intelligence Exclusive Infographic Machine Learning
image fx (2)
Monitoring Data Without Turning into Big Brother
Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

The Butterfly Effect and Data Quality

4 Min Read

Interview With Fellow UCONN Alumni and Successful Entrepreneur, Ted Hsu

7 Min Read

Come to the Enterprise Decision Management Summit in 2009

3 Min Read

Scenario Testing, Stress Testing and Decision Management

3 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?