Archive for the ‘Decision Making’ Category

Topic Maps in Lake Wobegon

Wednesday, May 15th, 2013

Jim Harris writes in The Decision Wobegon Effect:

In his book The Most Human Human, Brian Christian discussed what Baba Shiv of the Stanford Graduate School of Business called the decision dilemma, “where there is no objectively best choice, where there are simply a number of subjective variables with trade-offs between them. The nature of the situation is such that additional information probably won’t even help. In these cases – consider the parable of the donkey that, halfway between two bales of hay and unable to decide which way to walk, starves to death – what we want, more than to be correct, is to be satisfied with our choice (and out of the dilemma).”

(…)

Jim describes the Wobegon effect, an effect that blinds decision makers to alternative bales of hay.

Topic maps are composed of a mass of decisions, both large and small.

Is the Wobegon effect affecting your topic map authoring?

Check Jim’s post and think about your topic map authoring practices.

Posted in Authoring Topic Maps, Decision Making, Topic Maps | No Comments »

Advances in Neural Information Processing Systems (NIPS)

Sunday, April 7th, 2013

Advances in Neural Information Processing Systems (NIPS)

From the homepage:

The Neural Information Processing Systems (NIPS) Foundation is a non-profit corporation whose purpose is to foster the exchange of research on neural information processing systems in their biological, technological, mathematical, and theoretical aspects. Neural information processing is a field which benefits from a combined view of biological, physical, mathematical, and computational sciences.

Links to videos from NIPS 2012 meetings are featured on the homepage. The topics are as wide ranging as the foundation’s description.

A tweet from Chris Diehl, wondering what to do with “old hardbound NIPS proceedings (NIPS 11)” led me to: Advances in Neural Information Processing Systems (NIPS) [Online Papers], which has the papers from 1987 to 2012 by volume and a search interface to the same.

Quite a remarkable collection just from a casual skim of some of the volumes.

Unless you need to fill book shelf space, suggest you bookmark the NIPS Online Papers.

Posted in Decision Making, Inference, Machine Learning, Neural Networks, Neuroinformatics | No Comments »

Fast Data Gets A Jump On Big Data

Tuesday, March 12th, 2013

Fast Data Gets A Jump On Big Data by Hasan Rizvi.

The title reminded me of a post by Sam Hunting that asked: “How come we’ve got Big Data and not Good Data?”

Now “big data” is to give way to “fast data.”

From the post:

Today, both IT and business users alike are facing business scenarios where they need better information to differentiate, innovate, and radically transform their business.

In many cases, that transformation is being enabled by a move to “Big Data.” Organizations are increasingly collecting vast quantities of real-time data from a variety of sources, from online social media data to highly-granular transactional data to data from embedded sensors. Once collected, users or businesses are mining the data for meaningful patterns that can be used to drive business decisions or actions.

Big Data uses specialized technologies (like Hadoop and NoSQL) to process vast amounts of information in bulk. But most of the focus on Big Data so far has been on situations where the data being managed is basically fixed—it’s already been collected and stored in a Big Data database.

This is where Fast Data comes in. Fast Data is a complimentary approach to Big Data for managing large quantities of “in-flight” data that helps organizations get a jump on those business-critical decisions. Fast Data is the continuous access and processing of events and data in real-time for the purposes of gaining instant awareness and instant action. Fast Data can leverage Big Data sources, but it also adds a real-time component of being able to take action on events and information before they even enter a Big Data system.

Sorry Sam, “good data” misses out again.

Data isn’t the deciding factor in human decision making, instant or otherwise, see Thinking, Fast and Slow by Daniel Kahnman.

Supplying decision makers with good data and sufficient time to consider it, is the route to better decision making.

Of course, that leaves time to discover the poor quality of data provided by fast/big data delivery mechanisms.

Posted in BigData, Decision Making, Intelligence | No Comments »

The #NIPS2012 Videos are out

Monday, January 21st, 2013

The #NIPS2012 Videos are out by Igor Carron.

From the post:

Videolectures came through earlier than last year. woohoo! Presentations relevant to Nuit Blanche were featured earlier here. Videos for the presentations for the Posner Lectures, Invited Talks and Oral Sessions of the conference are here. Videos for the presentations for the different Workshops are here. Some videos are not available because the presenters have not given their permission to the good folks at Videolectures. If you know any of them, let them know the world is waiting.

Just in case Netflix is down. ;-)

Posted in Decision Making, Inference, Machine Learning | No Comments »

Documenting decisions separately from use cases

Thursday, March 15th, 2012

Documenting decisions separately from use cases by James Taylor.

From the post:

I do propose making decisions visible. By visible, I mean a separate and explicit step for each decision being made. These steps help the developer identify where possible alternate and exception paths may be placed. These decision points occur when an actor’s input drives the scenario down various paths.

I could not have put this better myself. I am a strong believer in this kind of separation, and of documenting how the decision is made independently of the use case so it can be reused. The only thing I would add is that these decisions need to be decomposed and analyzed, not simply documented. Many of these decisions are non-trivial and decomposing them to find the information, know-how and decisions on which they depend can be tremendously helpful.

James describes development and documentation of use cases and decisions in a context broader than software development. His point on decomposition of decisions is particularly important for systems designed to integrate information.

He describes decomposition of decisions as leading to discovery of “information, know-how and decisions on which they depend….”

Compare and contrast that with simple mapping decisions that map one column in a table to another. Can you say on what basis that mapping was made? Or with more complex systems, what “know-how” is required or on what other decisions that mapping may depend?

If your integration software/practice/system doesn’t encourage or allow such decomposition of decisions, you may need another system.

James also cover’s some other decision management materials that you may find useful in designing, authoring, evaluating information systems. (I started to say “semantic information systems” but all information systems have semantics, so that would be prepending an unnecessary noise word.)

Posted in Decision Making, Documentation, Information Integration, Use Cases | No Comments »

JT on EDM

Tuesday, September 6th, 2011

JT on EDM – James Taylor on Everything Decision Management

From the about page:

James Taylor is a leading expert in Decision Management and an independent consultant specializing in helping companies automate and improve critical decisions. Previously James was a Vice President at Fair Isaac Corporation where he developed and refined the concept of enterprise decision management or EDM. Widely credited with the invention of the term and the best known proponent of the approach, James helped create the Decision Management market and is its most passionate advocate.

James has 20 years experience in all aspects of the design, development, marketing and use of advanced technology including CASE tools, project planning and methodology tools as well as platform development in PeopleSoft’s R&D team and consulting with Ernst and Young. He has consistently worked to develop approaches, tools and platforms that others can use to build more effective information systems.

Another mainstream IT/data site that you would do well to read.

Posted in Data Mining, Decision Making | No Comments »

Multiple Criteria Decision Aid Bibliography

Wednesday, July 6th, 2011

Multiple Criteria Decision Aid Bibliography

I stumbled over this site while looking for a free copy of Amos Tversky’s “Features of Similarity” paper to cite for my readers. (I never was able to find a copy that wasn’t behind a pay-per-view wall. Sorry.)

It is maintained by the LAMSADE laboratory as materials on decision making, which identification of a subject certainly falls into that category.

The LAMSADE laboratory has been established in 1974 as a joint laboratory of the Université Paris-Dauphine and the CNRS. Its central research activity lies at the interface of two fundamental scientific areas: Computer Science and Decision Making (and, more generally, Operations Research).

LAMSADE’s research themes are both theoretical and applied and cover decision making, decision theory, social choice, operations research, combinatorial optimization, computational complexity, mathematical programming, interactions between decision and artificial intelligence, massive data computation, and information systems.

And yes, it is no mistake, the first entry in the bibliography is from 1736.

Enjoy!

Posted in Bibliography, Decision Making | No Comments »