15 results back to index
Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms: Proceedings of the Agi Workshop 2006 by Ben Goertzel, Pei Wang
AI winter, artificial general intelligence, bioinformatics, brain emulation, combinatorial explosion, complexity theory, computer vision, conceptual framework, correlation coefficient, epigenetics, friendly AI, G4S, information retrieval, Isaac Newton, John Conway, Loebner Prize, Menlo Park, natural language processing, Occam's razor, p-value, pattern recognition, performance metric, Ray Kurzweil, Rodney Brooks, semantic web, statistical model, strong AI, theory of mind, traveling salesman, Turing machine, Turing test, Von Neumann architecture, Y2K
Humans can construct powerful mental programs for many domains never seen before. We address the questions of how this occurs, and how it could possibly be accomplished in software. Section one surveys a theory of natural understanding, as follows. One understands a domain when one has mental programs that can be executed to solve problems arising in the domain. Evolution created compact programs understanding domains posed by nature. According to an extrapolation of Occam's razor, a compact enough program solving enough problems drawn from a distribution can only be found if there is simple structure underlying the distribution and the program exploits this structure, in which case the program will generalize by solving most new problems drawn from the distribution. This picture has several important ramifications for attempts to develop Artificial General Intelligence (AGI), suggesting for example, that human intelligence is not in fact general, and that weak methods may not suffice to reproduce human abilities.
Introduction A striking phenomenon of human intelligence is that we understand problems, and can construct powerful solutions for problems we have never seen before. Section one surveys a theory under which one understands a problem when one has mental programs that can solve it and many naturally occurring variations. Such programs are suggested to arise through discovering a sufficiently concise program that works on a sufficiently large sample of naturally presented problems. By a proposed extrapolation of Occam's razor, such a concise effective program would only exist if the world posing the problems had an underlying structure that the program exploits to solve the problems, and in that case it will generalize to solve many new problems generated by the same world. It is further argued that the concise Occam program leading to human and natural understanding is largely embodied in the genome, which programs development of a modular program in the brain.
Turing's thesis gives us a precise language which we can use to discuss and model thought, the language of computer programs. This thesis, however, left us with some puzzles. A first important one is: what about this particular code causes it to understand? A second important one is: given that complexity theory has indicated that many computations are inherently time consuming, how does the mind work so amazingly fast? Computational learning theory has explained generalization as arising from Occam's razor. The most studied context is concept learning, where one sees a series of classified examples, and desires to learn a function that will predict correctly whether new examples are examples of the concept or not. Roughly speaking, one can show that if one presents examples drawn from some process, and finds a simple enough E. Baum / A Working Hypothesis for General Intelligence 57 function classifying most examples in a large data set, it will also correctly classify most new examples drawn from the process on which it hadn't been been specifically trained, it will generalize.
The End of Traffic and the Future of Transport: Second Edition by David Levinson, Kevin Krizek
2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, American Society of Civil Engineers: Report Card, autonomous vehicles, barriers to entry, Bay Area Rapid Transit, big-box store, Chris Urmson, collaborative consumption, commoditize, crowdsourcing, DARPA: Urban Challenge, dematerialisation, Elon Musk, en.wikipedia.org, Google Hangouts, Induced demand, intermodal, invention of the printing press, jitney, John Markoff, labor-force participation, lifelogging, Lyft, means of production, megacity, Menlo Park, Network effects, Occam's razor, oil shock, place-making, post-work, Ray Kurzweil, rent-seeking, ride hailing / ride sharing, Robert Gordon, self-driving car, sharing economy, Silicon Valley, Skype, smart cities, technological singularity, Tesla Model S, the built environment, Thomas Kuhn: the structure of scientific revolutions, transaction costs, transportation-network company, Uber and Lyft, Uber for X, uber lyft, urban renewal, women in the workforce, working-age population, Yom Kippur War, zero-sum game, Zipcar
Safety Science 59: pp. 154-162 101 Hughes, Jonathan, Christopher Knittel, Daniel Sperling (2006) Evidence of a shift in the short-run price elasticity of gasoline demand. NBER Working Paper No 12530. Sept. 2006. http://www.nber.org/papers/w12530 102 Figure 3.9 Source: Schoner, Jessica, Greg Lindsey, and David Levinson (2015) Travel Behavior Over Time. MnDOT Report. 103 Occam's Razor, named for William of Ockham (1287-1347) says "among competing hypotheses, the one with the fewest assumptions should be selected." https://en.wikipedia.org/wiki/Occam's_razor 104 This is discussed in more detail in Garrison, W. L., & Levinson, D. M. (2014). The Transportation Experience: Policy, Planning, and Deployment. Oxford University Press. 105 Figure 3.10 Source: Historian, US Postal Service (2015-03) Pieces of Mail Handled, Number of Post Offices, Income, and Expenses Since 1789. https://about.usps.com/who-we-are/postal-history/pieces-of-mail-since-1789.pdf 106 Kurzweil, Ray (2005) The Singularity is Near: When Human Transcend Biology.
Some of that is due to changing preferences, some to the economy as discussed in earlier sections. School buses are likely due to changes in schools (which are bigger and farther apart) and increased movement away from the neighborhood school. Illustrative data for the Twin Cities is shown in Figure 3.9.102 Discussion It is hard to say which, if any, of these explanations have the fewest assumptions, thereby satisfying Occam's Razor.103 Instead, like Agatha Christie's novel, the guilt is spread over many shoulders. None of these explanations can be single-handedly responsible. As matters unfold over the upcoming years, more characters will be added and the specific role of any one culprit might become more pronounced. But for the time being, traffic is suffering a slow death by a thousand cuts. Interestingly, almost none of them can be attributed to conscious public policy aimed at traffic reduction.
Bulletproof Problem Solving by Charles Conn, Robert McLean
active transport: walking or cycling, Airbnb, Amazon Mechanical Turk, asset allocation, availability heuristic, Bayesian statistics, Black Swan, blockchain, business process, call centre, carbon footprint, cloud computing, correlation does not imply causation, Credit Default Swap, crowdsourcing, David Brooks, Donald Trump, Elon Musk, endowment effect, future of work, Hyperloop, Innovator's Dilemma, inventory management, iterative process, loss aversion, meta analysis, meta-analysis, Nate Silver, nudge unit, Occam's razor, pattern recognition, pets.com, prediction markets, principal–agent problem, RAND corporation, randomized controlled trial, risk tolerance, Silicon Valley, smart contracts, stem cell, the rule of 72, the scientific method, The Signal and the Noise by Nate Silver, time value of money, transfer pricing, Vilfredo Pareto, walkable city, WikiLeaks
We didn't invent them, we just make good use of them and so can you. EXHIBIT 5.1 The oldest of these is definitely Occam's Razor—favor the simplest solution that fits the facts—which originated in the fourteenth century. It tells us to select the hypothesis that has the fewest assumptions. One way of seeing why this make sense is a simple math example: If you have four assumptions that are independent of each other, with an 80% separate chance of being correct, the probability that all four will be correct is just over 40%. With two assumptions and the same probabilities, it is 64%. For many problems the fewer the assumptions you have the better. Practically speaking, this means avoiding complex, indirect, or inferential explanations, at least as our starting point. Related to Occam's Razor are one‐reason decision heuristics, including reasoning by elimination and a fortiori reasoning, where you eliminate alternatives that are less attractive.2 The important reminder is not to get committed to a simple answer with few assumptions when the facts and evidence are pointing to a more nuanced or complex answer (remember the availability and substitution biases from Chapter 4).
See Net present value Nursing outcomes, improvement, 67e Nussbaumer Knaflic, Cole, 182, 190 O Obesity analysis, 238–239 call to action, 239–243 case study, 143–146 high‐leverage problems, support, 242 incentives, 241 interventions, UK cost curve, 239e McKinsey Global Institute (MGI) study, 143, 236–239 policy variables, income/education (impact), 240 prevalence, measurement, 144, 144e problem, cleaving/definition, 237–238 rates, increase, 240 regulatory interventions, 237 social networks, impact, 241–242 walkability/active transport, 242–243 wicked problem, 236–237 Observations/complications, usage, 95 Occam's Razor, 114 Ohno, Taichi, 128 One‐day answers, 95–97, 184–185 example, 96 structuring, 95 Options, value, 216 Order of magnitude analysis, 114, 137 Ostrom, Elinor, 244 Outcomes, 196 distribution, 122–123, 122e economic outcomes, 158 policy/parameter change, impact, 157 prediction, 140 production, 130 value, 117–118 Output, sale, 214 Outside views, solicitation, 105 Overfishing common‐resource problem, 244 definition, 244 Morro Bay, case study, 247–250 obstacles, 246–247 restructuring, 246–247 solutions, 245–246, 245e wicked problem, 243–250 Over optimism, 101 P Pacific Fishery Management Council (PFMC), 244 Pacific salmon abundance/diversity, 54e change, vision (setting), 231e long‐term strategy portfolio, management (case study), 226–233 preservation, problem statement refinement, 34–39 problem statement evolution, 38e problem worksheet, 36e regional/topical strategies, management, 230–233 saving, case study, 53–58, 57e strategy portfolio, 229e TOC example, 227e Pain points, 44 Palter, Robert, 122 Pareto Principle, 114–115 Pareto Thinking, 129 Pareto, Vilfredo, 114 Payoff table, preparation, 171–172 Pearl, Judea, 151 Personal assets/savings, importance, 210 Personal problem solving, cleaving frame examples, 80 Perspective taking, 104 PFMC.
Sorting Things Out: Classification and Its Consequences (Inside Technology) by Geoffrey C. Bowker
affirmative action, business process, corporate governance, Drosophila, information retrieval, loose coupling, Menlo Park, Mitch Kapor, natural language processing, Occam's razor, QWERTY keyboard, Scientific racism, scientific worldview, sexual politics, statistical model, Stephen Hawking, Stewart Brand, the built environment, the medium is the message, transaction costs, William of Occam
When originally drawn up, it had a maximum of 200 categories. As we note above, this was not the number of diseases The Kindness of Strangers 65 in the world, but the number of lines on Austrian census forms. If too many diseases got identified then there would be no way of maintain ing and analyzing registers of causes of death, as the technology would not hold more information. In addition to this inheritance, there is a practical Occam's razor. When doctors come to code causes of death they are frequently faced with a set of difficult judgments (which may require an autopsy and further diagnostic work) . They can simply go for the easiest way, by using a generalized 'other' category. They can then get back to dealing with their live patients (Fagot-Largeault 1 989, chapter 3 ). So the clas sical beauty of the Aristotelian classification gives way to a fuzzier classification system that shares in practice key features with common sense prototype classifications-heterogeneous objects linked by meta phor or analogy.
In the face of incompatible information or data structures among users or among those specifying the system, attempts to create unitary knowledge categories are futile. Rather, parallel or multiple-repre sentational forms are required. So, for example, instead of trying to represent a disorder of energy diagnosed with acupuncture as a nerv ous disease in western medical terms, a parallel representational scheme will avoid imposing inappropriate categories. 2. Pragmatically, the Occam's razor of the coding of information means that too few categories will result in information that is not useful. 23 For instance, alive or dead, while having the virtues of sim plicity and [near] exhaustiveness, do not tell us much about disease in the world. On the other hand, too many categories will result in increased bias, or randomness, on the part of those filling out the forms. An lCD with five million category labels may be more ideally scientifically accurate, but most doctors would not even look at the resulting death certificate.
The next chapter touches on the implementation of the system in various field sites and its direct impact on nursing work. Here, we examine the upstream dilemmas. These are similar to dilemmas faced by many designers of information systems in a range of application domains. How does one make a successful, practically workable classification scheme of work practice? The problem of how to produce any clas sification scheme is an old one in the philosophy of knowledge, from Occam's razor to Quine's objects. Blurring categories means that existing differences are covered up, merged, or removed altogether; while distinctions construct new partitions or reinforcement of exist ing differences. This mutual process of constructing and shaping differences through classification systems is crucial in anyone's conceptualization of reality; it is the core of much taxonomic anthro pology.
Learning Scikit-Learn: Machine Learning in Python by Raúl Garreta, Guillermo Moncecchi
As our training data is not enough, we risk producing a model that could be very good at predicting the target class on the training dataset but fail miserably when faced with new data, that is, our model does not have the generalization power. That is why it is so important to evaluate our methods on previously unseen data. The general rule is that, in order to avoid overfitting, we should prefer simple (that is, with less parameters) methods, something that could be seen as an instantiation of the philosophical principle of Occam's razor, which states that among competing hypotheses, the hypothesis with the fewest assumptions should be selected. However, we should also take into account Einstein's words: "Everything should be made as simple as possible, but not simpler." The idem curse of dimensionality may suggest that we keep our models simple, but on the other hand, if our model is too simple we run the risk of suffering from underfitting.
The Golden Ticket: P, NP, and the Search for the Impossible by Lance Fortnow
Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Andrew Wiles, Claude Shannon: information theory, cloud computing, complexity theory, Donald Knuth, Erdős number, four colour theorem, Gerolamo Cardano, Isaac Newton, Johannes Kepler, John von Neumann, linear programming, new economy, NP-complete, Occam's razor, P = NP, Paul Erdős, Richard Feynman, Rubik’s Cube, smart grid, Stephen Hawking, traveling salesman, Turing machine, Turing test, Watson beat the top human players on Jeopardy!, William of Occam
We know him best for Occam’s razor, the principle that the simplest explanation is usually the best, denoted a “razor” supposedly because it allows us to “shave off” the complicated parts of a theory, leaving the simple explanation behind. This philosophy guided scientific and philosophical thinking throughout the Renaissance and continues to guide us today. René Descartes, a seventeenth-century French philosopher, used the Occam razor principle to argue even for the existence of the world around him. Descartes is, of course, most famous for his philosophical statement “Cogito ergo sum,” or “I think, therefore I am.” In his treatise Discourse of the Method, Descartes from assuming nothing deduces his own existence from the mere fact that he can reason about himself. What about the complex world that Descartes experiences? Could everything exist merely within Descartes’ consciousness?
Mastering Machine Learning With Scikit-Learn by Gavin Hackeling
computer vision, constrained optimization, correlation coefficient, Debian, distributed generation, iterative process, natural language processing, Occam's razor, optical character recognition, performance metric, recommendation engine
It predicts that a 16 inch pizza should cost less than $10, and an 18 inch pizza should cost more than $30. This model exactly fits the training data, but fails to learn the real relationship between size and price. [ 39 ] www.it-ebooks.info Linear Regression Regularization Regularization is a collection of techniques that can be used to prevent over-fitting. Regularization adds information to a problem, often in the form of a penalty against complexity, to a problem. Occam's razor states that a hypothesis with the fewest assumptions is the best. Accordingly, regularization attempts to find the simplest model that explains the data. scikit-learn provides several regularized linear regression models. Ridge regression, also known as Tikhonov regularization, penalizes model parameters that become too large. Ridge regression modifies the residual sum of the squares cost function by adding the L2 norm of the coefficients, as follows: n 2 p RS S ridge = ∑ ( yi − x β ) + λ ∑ β j2 T i i =1 j =1 λ is a hyperparameter that controls the strength of the penalty.
Forever Free by Joe Haldeman
"Wormholes. It's like exchanging one quantum state for another, and then going back." "Like a bungee jump," our fan of the twentieth century added. "With your starship," she continued, "you were actually leaving. You were going into the territory of the nameless." "They told you this?" Marygay asked. "You talk to the nameless?" "No," the man said. "It's just inference." "You would call it Occam's Razor," the woman said. "It's the least complicated explanation." "So we've provoked the wrath of God," I said. "If you want to put it that way," the plain one said. "What we're trying to figure out is how to get God's attention." I wanted to scream, but Sara expressed it more calmly. "If they're omnipotent and everywhere … we have their attention. Too much of it." The priest shook his head. "No.
You're Not Fooling Anyone When You Take Your Laptop to a Coffee Shop: Scalzi on Writing by John Scalzi
This is of course begging the question as to why they're so good, but just as American authors can have many reasons for slumping at the moment, these British authors can have myriad reasons for being at the top of their game, possibly some relating to nationality but other factors having little or nothing to do with it at all. It's fun to ascribe an overarching reason for the inclusion of these five particular books, to try to impose some sort of uniform causality. But ultimately these rationales aren't going to pan out. Occam's Razor returns us to the "really good book" theory. It works for me. *** The next piece you can see as a companion piece to "Science Fiction Outreach"— same ideas, many of the same examples, but a slightly different end point.—JS The Myth of the Science Fiction Monoculture (August 2, 2005) A number of people have written to alert me to Robert K.J. Killheffer's review of Old Man's War (among a number of other books) in the September 2005 issue of Fantasy & Science Fiction, with the intimation that the review is something of a slam.
The Great Railway Bazaar by Paul Theroux
From the train I could turn my eyes to the mountains and almost forget the country's name, but the truth was closer and cruel: the Vietnamese had been damaged and then abandoned, almost as if, dressed in our clothes, they had been mistaken for us and shot at; as if, just when they had come to believe that we were identified with them, we had bolted. It was not that simple, but it was nearer to describing that sad history than the urgent opinions of anguished Americans who, stropping Occam's Razor, classified the war as a string of atrocities, a series of purely political errors, or a piece of interrupted heroism. The tragedy was that we had come, and, from the beginning, had not planned to stay: Danang was to be proof of that. The train was under the gigantic Hai Van Pass ('The Pass of Clouds'), a natural division on the north side of Danang, like a Roman wall. If the Viet Cong got past it, the way would be clear to Danang, and already the Viet Cong were bivouacked on the far slopes, waiting.
Think Like a Rocket Scientist by Ozan Varol
Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, Amazon Web Services, Andrew Wiles, Apple's 1984 Super Bowl advert, Arthur Eddington, autonomous vehicles, Ben Horowitz, Cal Newport, Clayton Christensen, cloud computing, Colonization of Mars, dark matter, delayed gratification, different worldview, discovery of DNA, double helix, Elon Musk, fear of failure, functional fixedness, Gary Taubes, George Santayana, Google Glasses, Google X / Alphabet X, Inbox Zero, index fund, Isaac Newton, James Dyson, Jeff Bezos, job satisfaction, Johannes Kepler, Kickstarter, knowledge worker, late fees, lateral thinking, lone genius, longitudinal study, Louis Pasteur, low earth orbit, Marc Andreessen, Mars Rover, meta analysis, meta-analysis, move fast and break things, move fast and break things, multiplanetary species, obamacare, Occam's razor, out of africa, Peter Thiel, Pluto: dwarf planet, Ralph Waldo Emerson, Richard Feynman, Richard Feynman: Challenger O-ring, Ronald Reagan, Sam Altman, Schrödinger's Cat, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, Simon Singh, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, Upton Sinclair, Vilfredo Pareto, We wanted flying cars, instead we got 140 characters, Whole Earth Catalog, women in the workforce, Yogi Berra
Kyle Stock, “The Little Ion Engine That Could,” Bloomberg Businessweek, July 26, 2018, www.bloomberg.com/news/features/2018-07-26/ion-engine-startup-wants-to-change-the-economics-of-earth-orbit. 49. Stock, “Little Ion Engine.” 50. Tracy Staedter, “Dime-Size Thrusters Could Propel Satellites, Spacecraft,” Space.com, March 23, 2017, www.space.com/36180-dime-size-accion-thrusters-propel-spacecraft.html. 51. Keith Tidman, “Occam’s Razor: On the Virtue of Simplicity,” Philosophical Investigations, May 28, 2018, www.philosophical-investigations.org/2018/05/occams-razor-on-virtue-of-simplicity.html. 52. Sarah Freeman, “Alinea 2.0: Reinventing One of the World’s Best Restaurants: Why Grant Achatz and Nick Kokonas Hit the Reset Button,” Chicago Eater, May 19, 2016, https://chicago.eater.com/2016/5/19/11695724/alinea-chicago-grant-achatz-nick-kokonas. 53. Richard Duppa et al., The Lives and Works of Michael Angelo and Raphael (London: Bell & Daldy 1872), 151. 54.
Day We Found the Universe by Marcia Bartusiak
Albert Einstein, Albert Michelson, Arthur Eddington, California gold rush, Cepheid variable, Copley Medal, cosmic microwave background, cosmological constant, Edmond Halley, Edward Charles Pickering, Fellow of the Royal Society, fudge factor, Harlow Shapley and Heber Curtis, Harvard Computers: women astronomers, horn antenna, invention of the telescope, Isaac Newton, Louis Pasteur, Magellanic Cloud, Occam's razor, orbital mechanics / astrodynamics, Pluto: dwarf planet, Solar eclipse in 1919, William of Occam
(With 1 light-year equaling about six trillion miles, that's more than a hundred million trillion miles.) For Curtis the faint novae were bona fide proof that the nebulae resided far beyond the borders of the Milky Way. But Curtis was championing this idea too early, before the physics could explain it. Many of his fellow astronomers were still fairly skeptical, unwilling to conjure up new celestial creatures willy-nilly. For them “Occam's Razor” prevailed, the long-standing rule of thumb established by the English philosopher William of Occam in the fourteenth century. “Pluralitas non est ponenda sine necessitate,” declared Occam, which can be translated as “plurality must not be posited without necessity.” Best to choose the simplest interpretation over an unnecessarily complex one—unless forced to do otherwise. One type of nova was far more preferable than two.
The Teeth of the Tiger by Tom Clancy
"Civilized place like Rome, why bother?" Granger observed. But they would now, for a while at least. "How did we find out?" "Made the local papers that an official at the Israeli Embassy got whacked while taking a leak. The Agency Chief of Station fingered him for a spook. Some people at Langley are running around in circles trying to figure what it all means, but they'll probably fall back on Occam's razor and buy what the local cops think. Dead man. No wallet. Robbery where the crook got a little carried away." "You think the Israelis will buy that?" Granger wondered. "About as soon as they serve roast pork at an embassy dinner. He was knifed between the first and second vertebrae. A street hood is more likely to slash the throat, but a pro knows that's messy and noisy. The Carabinieri are working the case-but it sounds as though they don't have dick to work with, unless somebody at the restaurant has a hell of a good memory.
Antarctica by Kim Stanley Robinson
Because what it demonstrates very clearly is that what we think of as neutral objective science is actually a Utopian politics and worldview already. There is a big historical section describing the rise of science, showing that science is self-organizing and self-actualizing, and always trying to get better, to be more scientific, as one of its rules. And there is a big middle section showing how various features of normal scientific practice, the methodology and so on, are in fact ethical positions. Things like reproducibility, or Occam's razor, or peer review-almost everything in science that makes it specifically scientific, the authors show, is Utopian. Then the final section tells what the ramifications of this fact are, how scientists should behave now, once they realize this truth. And the book is a kind of underground bestseller! It goes from lab to lab, the graduate students are all reading it, the senior scientists who are still thinking- everyone!
Data Mining: Concepts and Techniques: Concepts and Techniques by Jiawei Han, Micheline Kamber, Jian Pei
bioinformatics, business intelligence, business process, Claude Shannon: information theory, cloud computing, computer vision, correlation coefficient, cyber-physical system, database schema, discrete time, distributed generation, finite state, information retrieval, iterative process, knowledge worker, linked data, natural language processing, Netflix Prize, Occam's razor, pattern recognition, performance metric, phenotype, random walk, recommendation engine, RFID, semantic web, sentiment analysis, speech recognition, statistical model, stochastic process, supply-chain management, text mining, thinkpad, Thomas Bayes, web application
[Dob90] Dobson, A.J., An Introduction to Generalized Linear Models. (1990) Chapman & Hall . [Dob01] Dobson, A.J., An Introduction to Generalized Linear Models. 2nd ed. (2001) Chapman & Hall . [Dom94] Domingos, P., The RISE system: Conquering without separating, In: Proc. 1994 IEEE Int. Conf. Tools with Artificial Intelligence (TAI’94) New Orleans, LA. (1994), pp. 704–707. [Dom99] Domingos, P., The role of Occam's razor in knowledge discovery, Data Mining and Knowledge Discovery 3 (1999) 409–425. [DP96] Domingos, P.; Pazzani, M., Beyond independence: Conditions for the optimality of the simple Bayesian classifier, In: Proc. 1996 Int. Conf. Machine Learning (ML’96) Bari, Italy. (July 1996), pp. 105–112. [DP97] Devore, J.; Peck, R., Statistics: The Exploration and Analysis of Data. (1997) Duxbury Press . [DP07] Dong, G.; Pei, J., Sequence Data Mining. (2007) Springer, New York .