|Saturday, January 29th, 2005|
1:18a - КунсткамераОпенметы
СТРАНИЦЫ ИСТОРИИ КУНСТКАМЕРЫ
1704–1718 гг. Указы Петра I "О приносе родившихся уродов, так же найденных необыкновенных вещей" (Полное собрание законов Российской империи, т. IV, СПб., 1830, №№ 1964, 3159 и др.). Первоначально личные коллекции Петра I и коллекции по анатомии и зоологии хранились в Аптекарской канцелярии
В КунсткамереОпенметы собираются удивительные нлп-образчики. В КунсткамереОпенметы нас не интересует авторство, но только удивительная природа процессов, породивших выставленные чудеса.
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4:24p - The Relational Self in Theory Practice and Community
NEW from ZTT publishers!
Stephen Gilligan, Ph.D. & Dvorah Simon, Ph.D.
Self-Relations Therapy is, in part, a synthesis of theory and practice from various prior traditions. However, the approach is more than an amalgam of ideas; rather, SR offers a meta-framework in which multiplicity – of form, meaning, presence, and so on – can be contained within an actively adaptive, aware, and present relational self.
Editors Stephen Gilligan and Dvorah Simon have gathered in a mosaic of content and communication to explain the perspective and to show how it can be applied across contexts. Divided into five broad sections – The Self-Relations Approach, Applications of Self-Relations, Self-Relations and Spiritual Paths, Dimensions of Self-Relations, Self-Relations and Expressive and Somatic Approaches – the book can be dipped into or read from beginning to end. Like a rich and colorful mosaic, the material can inspire or invoke whether you come in very close to follow specific themes or you stand back to take in the whole.
Stephen Gilligan first presented the theory and practice of Self-Relations in his book The Courage to Love in 1997. In the years since, the work has continued to evolve through workshops and presentations, as well as through the dialog and sharing of ideas that he has invited along the way. Just as the approach itself is a kind of collaboration of entities, whether within an individual or between people or in the midst of a community, this new book encourages the multidimensionality of voices. The contributors are not confined by rigid structural or editorial requisites; they are invited to address their topics in the language that befits them. Thus, a sense of the SR ideal of “multiple truths at the same time” is embodied in the work.
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5:43p - Automatic Meaning Discovery Using Google
Authors: Rudi Cilibrasi (CWI), Paul M. B. Vitanyi (CWI, University of Amsterdam, National ICT of Australia)
Comments: 29 pages, 10 figures
Subj-class: Computation and Language; Artificial Intelligence; Databases; Information Retrieval; Learning
ACM-class: I.2.4; I.2.7
We propose a new method to extract semantic knowledge from the world-wide-web for both supervised and unsupervised learning using the Google search engine in an unconventional manner. The approach is novel in its unrestricted problem domain, simplicity of implementation, and manifestly ontological underpinnings. We give evidence of elementary learning of the semantics of concepts, in contrast to most prior approaches. The method works as follows: The world-wide-web is the largest database on earth, and it induces a probability mass function, the Google distribution, via page counts for combinations of search queries. This distribution allows us to tap the latent semantic knowledge on the web. Shannon's coding theorem is used to establish a code-length associated with each search query. Viewing this mapping as a data compressor, we connect to earlier work on Normalized Compression Distance. We give applications in (i) unsupervised hierarchical clustering, demonstrating the ability to distinguish between colors and numbers, and to distinguish between 17th century Dutch painters; (ii) supervised concept-learning by example, using Support Vector Machines, demonstrating the ability to understand electrical terms, religious terms, emergency incidents, and by conducting a massive experiment in understanding WordNet categories; and (iii) matching of meaning, in an example of automatic English-Spanish translation.
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