Environment as a mechanism for Context Learning

Journalism is dying, they say. I do agree. And while the argue continues, many interested on the issue are now debating what really is the reason. The question is…, there is no reason at all, there are many. Intricate ones. Do ponder on this: while newspapers are facing the immense omnipresent and real-time competition from TV channels, TV on itself is dying also (while unexpectedly, … Radio is surging). On many broadcasted programs, TV anchors are now more important than the invited people who, on that subject (supposedly) worked hardly over years to provide that precise innovative content. As in large supermarkets and great malls, package by these means have turned more important than the content in itself. This related business editorial pressure for news quickness have become so intensive and aggressive, that contents are replaced every second without judge and once in the air hardly described, discussed,  opposed or dessicated. So at large,  TV CEO’s producers think that people are no longer waiting for a new interesting content to appear, they are instead waiting for the anchor which passes them down as they were peanuts. Peanuts are good, but in excess – we all agree – are damn awful. And many do so,  as an old passive addiction. Which means that in the long run, nothing remains (fact for both sides); … And if they give me no opportunity at all to check content carefully, if I happen to be on the mood to, … So, I move on. Buy this precise simple way, media cannibalizes itself.

We all know that attention spam is getting narrower these days, and, e.g., yes… greater literature classics are no longer read. So, Media CEO’s say – “they have no time“. But, really … do mind that gap. Think twice. If the whole environment suddenly recognizes (being this one of the major questions – see below) that they are getting enough of peanuts (and they really are), they will urge for beef-steaks. In fact, eating 1000 void peanuts takes more time to consume than one large good beef! And there is a difference, … the beef remains on our body for several hours, not seconds.

It’s promptly becoming a paradox, since Media CEO’s on their blindness competition refuge on saying that they – us readers – have no time (when in mediocrity no solution is found, easiest way is to repeat a mantra), and we (mostly of us) keep zapping news as never before. However, they never realized that we keep zapping it, because no news – by these means –  are of interest. They really all have become the same. And once they appear all the same, they all soon disappear from our minds. … We all in some aspects all wonder, what  really happened to  research journalism, stories about new complex issues, strong content, explained in detail but still provided in simple eloquent ways? Come on, this long-tailed huge market niche, once yours, is now void!

Newspapers do have this wonderful singularity. They still have journalists (at least some, if they had enough vision to nourish them). They could provide insightful detailed backup stories, open questions, or debating new ones as no one can in public space. Moreover, they have time from their consumers. That, at least, is what I am feed-backing to Guardian every Sunday when I put my money over the news bench in change for this newspaper, along others like The Economist. But in face of these overall great news-without-sense turmoil cascade, probably one of these days, people will instead desire silence… or listening to their grandfathers knowledge, good-sense, and long-lived emotion (which keeps increasing believe me). They will relate to him, as never before.  Not newspapers. At least, he do provides content.

But once the media is set (and in some way, not all the way, medium is the message, as postulated by Marshall McLuhan), the great gold-run will be on, … guess what, … content. And on relationships among content! Journalism will be no longer under atomization. Or crystallized.

Fig. – Spatial distribution of 931 items (words taken from an article at ABC Spanish newspaper) on a 61 x 61 non-parametric toroidal grid, at t=106. 91 ants used type 2 probability response functions, with k1=0.1 and k2=0.3. Some independent clusters examples are: (A) anunció, bilbao, embargo, titulos, entre, hacer, necesídad, tras, vida, lider, cualquier, derechos, medida.(B) dirigentes, prensa, ciu. (C) discos, amigos, grandes. (D) hechos, piloto, miedo, tipo, cd, informes. (E) dificil, gobierno, justicia, crisis, voluntad, creó, elección, horas, frente, técnica, unas, tarde, familia, sargento, necesídad, red, obra … (among other word semantic clusters; check paper article below).

For long, media decided to do nothing, while new media including social media was coming in to the plateu, stronger as never before. Let me give you one example. In order to understand how relations between item news could enhnace newspaper reading and social awareness, back in 2002 I decided to make an experiment. Together with a colleague, we took one article of the Spanish ABC magazine (photo above). The article was about spanish political parties and corruption. It contained 931words (snapshot above). In order to extract semantic meaning from it as a pre-processing computer analysis, we started by applying Latent Semantic Analysis (LSA). Then, Swarm Intelligent algorithms were developed in order to have a glimpse on the relations among all those words on the newspaper article. Guess what? Some words like “big”, friends” and “music discs” were segmented from the rest of the political related article (segregated it on a remote semantic “island”), that is, not only a whole conceptual semantic atlas of that entire news section was possible, as well as finding unrelated issues (which were uncorrelated semantic “islands”). Now, just imagine if this happens within a newspaper social network, live, 24 hours a day, while people grab for strong co-related content and discuss it as it happens. One strong journal article, could in facto, evolve to social collective knowledge and awareness as never before. That, in reality is something that classic journalism could use as and edge for their (nowadays awful) market approach. Providing not only good content, but along with it, an extra service not available anyware (which is in some way, priceless): The chance to provide co-related real-time meta-content. Not one view, but many aggregated views.  Edited real-world real-time good quality journalism which has the potential of an “endless” price, namely these days. On the other hand, what we now see is that news CEO’s along with some editors still keep their minds on 19th century journalism.  For worse, due to their legitimic panic. However, meanwhile, the world has indeed evolved.

[] Vitorino Ramos, Juan J. Merelo, Self-Organized Stigmergic Document Maps: Environment as a Mechanism for Context Learning, in AEB´2002 – 1st Spanish Conference on Evolutionary and Bio-Inspired Algorithms, E. Alba, F. Herrera, J.J. Merelo et al. (Eds.), pp. 284-293, Centro Univ. de Mérida, Mérida, Spain, 6-8 Feb. 2002.

Social insect societies and more specifically ant colonies, are distributed systems that, in spite of the simplicity of their individuals, present a highly structured social organization. As a result of this organization, ant colonies can accomplish complex tasks that in some cases exceed the individual capabilities of a single ant. The study of ant colonies behavior and of their self-organizing capabilities is of interest to knowledge retrieval/management and decision support systems sciences, because it provides models of distributed adaptive organization which are useful to solve difficult optimization, classification, and distributed control problems, among others. In the present work we overview some models derived from the observation of real ants, emphasizing the role played by stigmergy as distributed communication paradigm, and we present a novel strategy to tackle unsupervised clustering as well as data retrieval problems. The present ant clustering system (ACLUSTER) avoids not only short-term memory based strategies, as well as the use of several artificial ant types (using different speeds), present in some recent approaches. Moreover and according to our knowledge, this is also the first application of ant systems into textual document clustering.

(to obtain the respective PDF file follow link above or visit chemoton.org)

Self-Organized Data and Image Retrieval as a Consequence of Stigmergic Activities in Artificial Ant Colonies

Figure – A sequential clustering task of corpses performed by a real ant colony. In here 1500 corpses are randomly located in a circular arena with radius = 25 cm, where Messor Sancta workers are present. The figure shows the initial state (above), 2 hours, 6 hours and 26 hours (below) after the beginning of the experiment (from: Bonabeau E., M. Dorigo, G. Théraulaz. Swarm Intelligence: From Natural to Artificial Systems. Santa Fe Institute in the Sciences of the Complexity, Oxford University Press, New York, Oxford, 1999).

The following research paper exploits precisely this phenomena into digital data.

[] Vitorino Ramos, Fernando Muge, Pedro Pina, Self-Organized Data and Image Retrieval as a Consequence of Inter-Dynamic Synergistic Relationships in Artificial Ant Colonies, in Javier Ruiz-del-Solar, Ajith Abraham and Mario Köppen (Eds.), Frontiers in Artificial Intelligence and Applications, Soft Computing Systems – Design, Management and Applications, 2nd Int. Conf. on Hybrid Intelligent Systems, IOS Press, Vol. 87, ISBN 1 5860 32976, pp. 500-509, Santiago, Chile, Dec. 2002.

Social insects provide us with a powerful metaphor to create decentralized systems of simple interacting, and often mobile, agents. The emergent collective intelligence of social insects “swarm intelligence” resides not in complex individual abilities but rather in networks of interactions that exist among individuals and between individuals and their environment. The study of ant colonies behavior and of their self-organizing capabilities is of interest to knowledge retrieval/ management and decision support systems sciences, because it provides models of distributed adaptive organization which are useful to solve difficult optimization, classification, and distributed control problems, among others. In the present work we overview some models derived from the observation of real ants, emphasizing the role played by stigmergy as distributed communication paradigm, and we present a novel strategy (ACLUSTER) to tackle unsupervised data exploratory analysis as well as data retrieval problems. Moreover and according to our knowledge, this is also the first application of ant systems into digital image retrieval problems. Nevertheless, the present algorithm could be applied to any type of numeric data.

(to obtain the respective PDF file follow link above or visit chemoton.org)