@misc{santosneto-2007, title = {Tracking User Attention in Collaborative Tagging Communities}, author = {Elizeu Santos-Neto and Matei Ripeanu and Adriana Iamnitchi}, year = 2007, url = {http://arxiv.org/pdf/0705.1013}, description = {[0705.1013] Tracking User Attention in Collaborative Tagging Communities}, biburl = {http://www.bibsonomy.org/bibtex/2785df87d0942d1cb6da9b944df902730/andreab}, keywords = {citeulike tagging metrics interest entropy similarity bibsonomy measures user statistics} } @article{debowski-glotto, title = {Zipf´s law against the text size: a half-rational model}, author = {Lukasz Debowski}, journal = {Glottometrics}, pages = {49 - 60}, volume = 4, year = 2002, biburl = {http://www.bibsonomy.org/bibtex/2b1267434d81756fd05da338b50b3d623/andreab}, keywords = {zipf d4.1 entropy mandelbrot word frequency tagora glottometrics distribution doubleslope} } @article{kornai-glotto, title = {How many words are there?}, author = {Andr\'as Kornai}, journal = {Glottometrics}, pages = {61 - 86}, volume = 4, year = 2002, biburl = {http://www.bibsonomy.org/bibtex/25fda9b7aedb8eca6a970d0572beb9cac/andreab}, keywords = {zipf d4.1 entropy mandelbrot word kornai frequency tagora glottometrics distribution doubleslope} } @article{montemurro-glotto, title = {Frequency-rank distribution of words in large text samples: phenomenology and models}, author = {Marcelo A. Montemurro and D. Zanette}, journal = {Glottometrics}, pages = {87-99}, volume = 4, year = 2002, biburl = {http://www.bibsonomy.org/bibtex/2ca52767c942af8778595d7182849a38b/andreab}, keywords = {zipf d4.1 entropy mandelbrot word frequency tagora montemurro glottometrics distribution doubleslope} } @misc{crooks-2006, title = {Beyond Boltzmann-Gibbs statistics: Maximum entropy hyperensembles out-of-equilibrium}, author = {Gavin E. Crooks}, year = 2006, url = {http://www.citebase.org/abstract?id=oai:arXiv.org:cond-mat/0603120}, description = {[cond-mat/0603120] Beyond Boltzmann-Gibbs statistics: Maximum entropy hyperensembles out-of-equilibrium}, biburl = {http://www.bibsonomy.org/bibtex/273a6a41abfbaa20b46110f9620991a41/andreab}, keywords = {physics dynamics entropy non-equilibrium imported} } @misc{liu-2006, title = {Nonsymmetric entropy I: basic concepts and results}, author = {Chengshi Liu}, year = 2006, url = {http://www.citebase.org/abstract?id=oai:arXiv.org:cs/0611038}, description = {[cs/0611038] Nonsymmetric entropy I: basic concepts and results}, biburl = {http://www.bibsonomy.org/bibtex/24614f82692f88054ac74bd0c430908a1/andreab}, keywords = {2006 zipf entropy mandelbrot tagora imported liu} } @article{citeulike:686746, title = {Algorithmic information, complexity and Zipf's law}, author = {V. K. Balasubrahmanyan and S. Naranan}, journal = {Glottometrics}, pages = {1--26}, volume = 4, year = 2002, description = {CiteULike: Algorithmic information, complexity and Zipf's law}, abstract = {Zipf’s law of word frequencies for language discourses is established with statistical rigor. Data show a departure from Zipf’s power law term at low frequencies. This is accounted by a modi-fying exponential term. Both arise naturally in a model for word frequencies based on Information Theory, algorithmic coding of a text preserving the symbol sequence, concepts from quantum statistical physics and computer science and extremum principles. The Optimum Meaning Preserving Code (OMPC) of the discourse is realized when word frequencies follow the Modified Power Law (MPL). The model predicts a variant of the MPL for the relative frequencies of a small fixed set of symbols such as letters, phonemes and grammatical words. The OMPC can be viewed as containing orderly and random parts. This leads us to a quantitative definition of complexity of a string (C) that tends to 0 for the extremes of ‘all order’ and ‘all random’ but is a maximum (C = 1) for a mixture of both (Gell-Mann). It is found that natural languages have maximum complexity. The uniqueness of Zipf’s power law index (γ = 2) is shown to arise in four different ways, one of which depends on scale invariance characteristic of fractal structures. It is argued that random text models are unsuitable for natural languages. It is speculated that a drastic change in symbol frequency distribution starting from phrases is related to emergence of meaning and coherence of a discourse.}, biburl = {http://www.bibsonomy.org/bibtex/281af3604a0d101b67169733d5c8f67b8/andreab}, keywords = {zipf d4.1 entropy mandelbrot word frequency tagora glottometrics distribution} } @article{andrieux:150601, title = {Entropy Production and Time Asymmetry in Nonequilibrium Fluctuations}, author = {D. Andrieux and P. Gaspard and S. Ciliberto and N. Garnier and S. Joubaud and A. Petrosyan}, journal = {Physical Review Letters}, number = 15, pages = 150601, publisher = {APS}, volume = 98, year = 2007, url = {http://link.aps.org/abstract/PRL/v98/e150601}, collaboration = {}, numpages = {4}, eid = {150601}, abstract = { The time-reversal symmetry of nonequilibrium fluctuations is experimentally investigated in two out- of-equilibrium systems: namely, a Brownian particle in a trap moving at constant speed and an electric circuit with an imposed mean current. The dynamical randomness of their nonequilibrium fluctuations is characterized in terms of the standard and time-reversed entropies per unit time of dynamical systems theory. We present experimental results showing that their difference equals the thermodynamic entropy production in units of Boltzmann’s constant. }, biburl = {http://www.bibsonomy.org/bibtex/2d3f0e67942afdcded3c689280a6cf27e/andreab}, keywords = {processes nonequilibrium physics experiments dynamics entropy brownian stochastic flictuations imported} } @article{chi2007, title = {Understanding Navigability of Social Tagging Systems}, author = {Todd Mytkowicz Ed H. Chi}, year = 2007, url = {http://www.google.com/url?sa=t&ct=res&cd=1&url=http%3A%2F%2Fwww.viktoria.se%2Faltchi%2Findex.php%3Faction%3Dshowsubmission%26id%3D39&ei=VFDoRdG5FIy20wSnq9iPDA&usg=__NGsT9XM4DFpohSrGyOZzjAiQFBs=&sig2=vKW2dIH12OppxK-VX2XWxA}, abstract = {Given the rise in popularity of social tagging systems, it seems only natural to ask how efficient is the organically evolved vocabulary in describing any underlying document objects? Does this distributed process really provide a way to circumnavigate the traditional categorization problem with ontologies? We analyze a social tagging site, namely del.icio.us, with information theory in order to evaluate the efficiency of this social tagging site for navigation to information sources. We show that over time, del.icio.us is becoming harder and harder to navigate and provide an evaluation metric, namely entropy, that can be used to evaluate and drive system design choices. }, biburl = {http://www.bibsonomy.org/bibtex/28b3160b26e6deb3a904b033d9f11ba8b/andreab}, keywords = {stream d4.1 tagging navigation entropy folksonomy delicious tagora statistics} }