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
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
    cybersecurity efforts
    How Behavioral Analytics and AI Are Redefining Cybersecurity for Boca Raton Businesses
    14 Min Read
    data driven risk management in heatlhcare
    How Data Analytics Is Changing Healthcare Risk Management
    17 Min Read
    big data and customer service outsourcing
    How Data Analytics Improves Customer Service Outsourcing
    18 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

2009 Annual Marketing Trends Study
Expert Panel on Challenges and Solutions
Wil Wheaton is Just Some Guy, You Know?
Data May Require Unique Data Quality Processes
Enterprise 2.0 Best Practices

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

chatgpt image jul 18, 2026, 05 09 14 pm
When Data-Driven Businesses Must Recover Data from USB Drives
Big Data Exclusive
chatgpt image jul 15, 2026, 03 28 38 pm
How Cloud Technology Helps IT Asset Recovery Services
Cloud Computing Exclusive IT Security
chatgpt image jul 13, 2026, 04 23 45 pm
How Data Analytics Helps Companies Improve User Engagement
Analytics Big Data Exclusive
chatgpt image jul 13, 2026, 04 19 58 pm
Can AI Help Companies Improve PPC Fulfilment?
Artificial Intelligence Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

IBM and ILOG for a smarter planet

5 Min Read
CRM business intelligence
Best PracticesBig DataBusiness IntelligenceCRMCulture/LeadershipData ManagementInside CompaniesMarketing

Convergence 2013: CMOs Ain’t Rich, MSDynCRM is Getting There

8 Min Read

Enterprise 2.x == Web science, or why “engineering” is a dead end for information system design

7 Min Read

An Interview With Tom De Ruyck of BAQMAR

1 Min Read

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

giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?