Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

December 14, 2012

Structure and Dynamics of Information Pathways in Online Media

Filed under: Information Flow,Information Theory,Networks,News,Social Networks — Patrick Durusau @ 6:16 am

Structure and Dynamics of Information Pathways in Online Media by Manuel Gomez Rodriguez, Jure Leskovec, Bernhard Schölkopf.

Abstract:

Diffusion of information, spread of rumors and infectious diseases are all instances of stochastic processes that occur over the edges of an underlying network. Many times networks over which contagions spread are unobserved, and such networks are often dynamic and change over time. In this paper, we investigate the problem of inferring dynamic networks based on information diffusion data. We assume there is an unobserved dynamic network that changes over time, while we observe the results of a dynamic process spreading over the edges of the network. The task then is to infer the edges and the dynamics of the underlying network.

We develop an on-line algorithm that relies on stochastic convex optimization to efficiently solve the dynamic network inference problem. We apply our algorithm to information diffusion among 3.3 million mainstream media and blog sites and experiment with more than 179 million different pieces of information spreading over the network in a one year period. We study the evolution of information pathways in the online media space and find interesting insights. Information pathways for general recurrent topics are more stable across time than for on-going news events. Clusters of news media sites and blogs often emerge and vanish in matter of days for on-going news events. Major social movements and events involving civil population, such as the Libyan’s civil war or Syria’s uprise, lead to an increased amount of information pathways among blogs as well as in the overall increase in the network centrality of blogs and social media sites.

A close reading of this paper will have to wait for the holidays but it will be very near the top of the stack!

Transient subjects anyone?

January 7, 2012

The feedback economy

Filed under: Information Flow,Information Theory — Patrick Durusau @ 3:55 pm

The feedback economy Companies that employ data feedback loops are poised to dominate their industries. by Alistair Croll.

From the post:

Military strategist John Boyd spent a lot of time understanding how to win battles. Building on his experience as a fighter pilot, he broke down the process of observing and reacting into something called an Observe, Orient, Decide, and Act (OODA) loop. Combat, he realized, consisted of observing your circumstances, orienting yourself to your enemy’s way of thinking and your environment, deciding on a course of action, and then acting on it.

[graphic omitted, but it is interesting. Go to Croll’s post to see it.]

The most important part of this loop isn’t included in the OODA acronym, however. It’s the fact that it’s a loop. The results of earlier actions feed back into later, hopefully wiser, ones. Over time, the fighter “gets inside” their opponent’s loop, outsmarting and outmaneuvering them. The system learns.

Boyd’s genius was to realize that winning requires two things: being able to collect and analyze information better, and being able to act on that information faster, incorporating what’s learned into the next iteration. Today, what Boyd learned in a cockpit applies to nearly everything we do.

Information is important but so is the use of information in the form of feedback.

But all systems, even information systems generate feedback.

The question is: Does your system (read topic map) hear feedback? Perhaps more importantly, does it adapt based upon feedback it hears?

October 19, 2011

The Kepler Project

Filed under: Bioinformatics,Data Analysis,ELN Integration,Information Flow,Workflow — Patrick Durusau @ 3:16 pm

The Kepler Project

From the website:

The Kepler Project is dedicated to furthering and supporting the capabilities, use, and awareness of the free and open source, scientific workflow application, Kepler. Kepler is designed to help scien­tists, analysts, and computer programmers create, execute, and share models and analyses across a broad range of scientific and engineering disciplines. Kepler can operate on data stored in a variety of formats, locally and over the internet, and is an effective environment for integrating disparate software components, such as merging “R” scripts with compiled “C” code, or facilitating remote, distributed execution of models. Using Kepler’s graphical user interface, users simply select and then connect pertinent analytical components and data sources to create a “scientific workflow”—an executable representation of the steps required to generate results. The Kepler software helps users share and reuse data, workflows, and compo­nents developed by the scientific community to address common needs.

The Kepler software is developed and maintained by the cross-project Kepler collaboration, which is led by a team consisting of several of the key institutions that originated the project: UC Davis, UC Santa Barbara, and UC San Diego. Primary responsibility for achieving the goals of the Kepler Project reside with the Leadership Team, which works to assure the long-term technical and financial viability of Kepler by making strategic decisions on behalf of the Kepler user community, as well as providing an official and durable point-of-contact to articulate and represent the interests of the Kepler Project and the Kepler software application. Details about how to get more involved with the Kepler Project can be found in the developer section of this website.

Kepler is a java-based application that is maintained for the Windows, OSX, and Linux operating systems. The Kepler Project supports the official code-base for Kepler development, as well as provides materials and mechanisms for learning how to use Kepler, sharing experiences with other workflow developers, reporting bugs, suggesting enhancements, etc.

I found this from an announcement of an NSF grant for a bioKepler project.

Questions:

  1. Review the Kepler project and prepare a short summary of it. (3 – 5 pages)
  2. Workflow by its very nature involves subjects moving from one process or user to another. How is that handled by Kepler in general?
  3. Can you use intersect the workflow of Kepler with other workflow management software? If not, why not? (research project)

December 3, 2010

Dynamic Indexes?

Filed under: Authoring Topic Maps,Graphic Processors,Indexing,Information Flow,Information Retrieval — Patrick Durusau @ 5:23 pm

I was writing the post about the New York Times graphics presentation when it occurred to me how close we are to dynamic indexes.

After all, gaming consoles are export restricted.

What we now consider to be “runs,” static indexes and the like are computational artifacts.

They follow how we created indexes when they were done by hand.

What happens when the properties of what is being indexed, its identifications and merging rules can change on the fly and re-present itself to the user for further manipulation?

I don’t think the fundamental issues of index construction get any easier with dynamic indexes but how we answer them will determine how quickly we can make effective use of such indexes.

Whether crossing the line first to dynamic indexes will be a competitive advantage, only time will tell.

I would like for some VC to be interested in finding out.

Caveat to VCs. If someone pitches this as making indexes more quickly, that isn’t the point. “Quick” and “dynamic” aren’t the same thing. Related but different. Keep both hands on your wallet.

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