К семантическим основаниям понимания
Taking a vegetal motif in Proust's novel "A la recherche du temps perdu" as an example, the paper considers some problems connected with the text understanding and its semantic interpretation.
For the last two decades a large number of philosophical texts have been issued including texts that were formerly hard to access for a Russian reader – publications of the works of Russian philosophers that had not been issued for wide circles of readers, translations (including from eastern languages), publications of the archival materials and epistolary heritage of the philosophers. Notwithstanding, in cases of quality issues the process of publishing itself generally used to be accompanied by signiﬁ cant preparative work – research, philological, commentary and philosophically-interpretative work. Vast experience has been accumulated in this sphere. While at the same time, a number of signiﬁ cant philosophic-methodological problems have been revealed. At the center of this problem ﬁ eld lies the question – is there any speciﬁ city in the work of publishing preparation of archival philosophical texts? Is the publishing preparation of such a philosophical text differentiated from that of the preparation of any other translated or archival literary work that requires transcription or commentary? Or is this a sphere of exclusively philological work? What is the speciﬁ city of philosophical translation and can we represent the archival publication as a type of “translation”? And so on. Certain answers to these questions deﬁ ne not only the peculiarities of publishing projects and the choice of readership, but also the situation in the intellectual culture of Russia. Therefore it is often surrounded by quite distinct polemics. It is supposed, that an acute necessity of comprehensive discussion of correlated thematics has emerged today. Furthermore the accumulated experience allows the clariﬁcation of the practical requirements for publication.
The paper assesses the requirements to the level of foreign language skills in a non-linguistic institution. Professionally oriented teaching is consideredto be a technology ensuring efficient cognitive activity of students. Much attention is given to the role of traditional and non-traditional teaching methods in facilitating a person's activity in the learning process
There has been compared behavior of rats, corvid birds, and monkeys of different species at their performance of the Revecz–Krushinskii test (RKT) developed by L.V. Krushinskii to estimate the human capability for revealing rule of discrete translocation of hidden target object. RKT was introduced as an addition to the test for extrapolation of the movement direction of the lure seen only at the initial pathway fragment; this test is close to Piaget’s test (stage 6) evaluating the capability for mental representation and location of the moving hidden object. During RKT, the lure, hidden from animals, was placed, near where it was previous time: at the first test presentation— under the 1st cylinder, at the 2nd one—under the 2nd cylinder, etc. The animals were tested once. It was shown that they did not catch the necessary for successful solution rule of the lure translocation, direction and step of its translocation at each presentation. Only some of the animals solved RKT, found the lure 3 and more times in succession with no errors or with one error. Nevertheless, in all groups the number of errors was lower than that in the model situation of random search. Such optimization was a consequence of universal for all groups’ strategy of search in the places where the lure was found recently. With the similar number of errors, rats, birds, and monkeys performed the search differently. Rats were looking for lure mainly among the cylinders where they had found it previously, whereas monkeys and birds the first the new cylinders located near the target one, which implies the existence, to the weak extent, of elements of prognosis. For all groups of animals, RKT turned out to be more difficult both of the test for extrapolation and of the Piaget’s test.
A two-step approach to devising a hierarchical taxonomy of a domain is outlined. As the first step, a coarse “high-rank” taxonomy frame is built manually using the materials of the government and other representative sites. As the second step, the frame is refined topic-by topic using the Russian Wikipedia category tree and articles filtered of “noise”. A topic-to-text similarity score, based on annotated suffix trees, is used throughout. The method consists of three main stages: 1) clearing Wikipedia data of noise, such as irrelevant articles and categories; 2) refining the taxonomy frame with the remaining relevant Wikipedia categories and articles; 3) extracting key words and phrases from Wikipedia articles. Also, a set of so-called descriptors is assigned to every leaf; these are phrases explaining aspects of the leaf topic. In contrast to many existing taxonomies, our resulting taxonomy is balanced so that all the branches are of similar depths and similar numbers of leaves. The method is illustrated by its application to a mathematics domain, “Probability theory and mathematical statistics”.