Globalization: an open door for the knowledge economy

Globalization refers to an emphasized process of global integration and spreading a set of ideas related to the economical activity and goods’ production, the premises being the liberalization of international commerce and the capital flows, the speeding up of the technological progress and informational society. The cognitive society is more and more obvious and unanimously accepted, which actually proves its efficiency. If traditional, conservative communities, which are not open to change and reject from the start anything new on the horizon, still exist today, they are isolated cases that will eventually be "converted" by this wave of information that has become indispensable to any development because in its absence resources could not be used efficiently. Taking into consideration these elements, this paper wishes to give arguments to the fact that globalization can be seen as being an open door for the cognitive society.globalization, knowledge economy, multinational organizations

E-Government, Managerial Staff Preparation and Cognitive Society

In the context of E-Government and cognitive society development the necessity of managerial staff with new professional competencies preparation within innovative educational programs is actualized

A Data-Oriented Approach to Semantic Interpretation

In Data-Oriented Parsing (DOP), an annotated language corpus is used as a stochastic grammar. The most probable analysis of a new input sentence is constructed by combining sub-analyses from the corpus in the most probable way. This approach has been succesfully used for syntactic analysis, using corpora with syntactic annotations such as the Penn Treebank. If a corpus with semantically annotated sentences is used, the same approach can also generate the most probable semantic interpretation of an input sentence. The present paper explains this semantic interpretation method, and summarizes the results of a preliminary experiment. Semantic annotations were added to the syntactic annotations of most of the sentences of the ATIS corpus. A data-oriented semantic interpretation algorithm was succesfully tested on this semantically enriched corpus.Comment: 10 pages, Postscript; to appear in Proceedings Workshop on Corpus-Oriented Semantic Analysis, ECAI-96, Budapes

Decorrelation and shallow semantic patterns for distributional clustering of nouns and verbs

Distributional approximations to lexical semantics are very useful not only in helping the creation of lexical semantic resources (Kilgariff et al., 2004; Snow et al., 2006), but also when directly applied in tasks that can benefit from large-coverage semantic knowledge such as coreference resolution (Poesio et al., 1998; Gasperin and Vieira, 2004; Versley, 2007), word sense disambiguation (Mc- Carthy et al., 2004) or semantical role labeling (Gordon and Swanson, 2007). We present a model that is built from Webbased corpora using both shallow patterns for grammatical and semantic relations and a window-based approach, using singular value decomposition to decorrelate the feature space which is otherwise too heavily influenced by the skewed topic distribution of Web corpora

The systemic dimension of operational decision in complex systems work

This paper refers to some of my research findings on Decision Making processes in complex systems work. Starting as a complex cognitive process strongly contextualized in the operating environment, it ends up, in complex systems work, as an equally complex network of actors and systems (human and technological) that are confronted, in real time, with uncertainty , a large amount of information and feedback and with multiple standards and operating procedures...Complex systems work; Operational Decision; Mental Model; Situational awareness; Systemic decision

Hard, Harder, and the Hardest Problem: The Society of Cognitive Selves

The hard problem of consciousness is explicating how moving matter becomes thinking matter. Harder yet is the problem of spelling out the mutual determinations of individual experiences and the experiencing self. Determining how the collective social consciousness influences and is influenced by the individual selves constituting the society is the hardest problem. Drawing parallels between individual cognition and the collective knowing of mathematical science, here we present a conceptualization of the cognitive dimension of the self. Our abstraction of the relations between the physical world, biological brain, mind, intuition, consciousness, cognitive self, and the society can facilitate the construction of the conceptual repertoire required for an explicit science of the self within human society

Human assessments of document similarity

Two studies are reported that examined the reliability of human assessments of document similarity and the association between human ratings and the results of n-gram automatic text analysis (ATA). Human interassessor reliability (IAR) was moderate to poor. However, correlations between average human ratings and n-gram solutions were strong. The average correlation between ATA and individual human solutions was greater than IAR. N-gram length influenced the strength of association, but optimum string length depended on the nature of the text (technical vs. nontechnical). We conclude that the methodology applied in previous studies may have led to overoptimistic views on human reliability, but that an optimal n-gram solution can provide a good approximation of the average human assessment of document similarity, a result that has important implications for future development of document visualization systems

Knowledge economy, learning society and lifelong learning : a review of the French literature

In this article, we propose the hypothesis that “the Learning society” is more a political slogan and prospect than a social reality (In France, as in most OECD countries, public investment in formal education and training has actually decreased since the OECD started talking about lifelong learning). And there is no agreement as to what a future “learning society” should be. Firstly, the framework of knowledge economy has not yet been defined and analysts remain divided on the issue: is it (or will be) an extension of a deregulated, market economy and society, or a more regulated capitalist economy? Should knowledge be considered as a public good or as a marketable one (section 1). Secondly, the consequences of the resulting economic changes for workers and for citizens are unclear. Although most studies acknowledge the development of new (net) work organizations, of new skill requirements and of new opportunities for learning, some studies also emphasize new risks of economic and social exclusion (section 2). And the French specificities are particularly marked in terms of education and lifelong learning strategies. (section 3). Although lifelong learning strategies are sometimes explicitly (but more often implicitly) related to the prospect of a Knowledge Economy, part of the debate is purely endogenous to the educational sphere and initial education and further education remain separated.FPC - Formation professionnelle continue; Projet de formation; Politique de l'éducation; Accréditation; Formation tout au long de la vie; Economie de la connaissance; France; Revue de la littérature

Data-Oriented Language Processing. An Overview

During the last few years, a new approach to language processing has started to emerge, which has become known under various labels such as "data-oriented parsing", "corpus-based interpretation", and "tree-bank grammar" (cf. van den Berg et al. 1994; Bod 1992-96; Bod et al. 1996a/b; Bonnema 1996; Charniak 1996a/b; Goodman 1996; Kaplan 1996; Rajman 1995a/b; Scha 1990-92; Sekine & Grishman 1995; Sima'an et al. 1994; Sima'an 1995-96; Tugwell 1995). This approach, which we will call "data-oriented processing" or "DOP", embodies the assumption that human language perception and production works with representations of concrete past language experiences, rather than with abstract linguistic rules. The models that instantiate this approach therefore maintain large corpora of linguistic representations of previously occurring utterances. When processing a new input utterance, analyses of this utterance are constructed by combining fragments from the corpus; the occurrence-frequencies of the fragments are used to estimate which analysis is the most probable one. In this paper we give an in-depth discussion of a data-oriented processing model which employs a corpus of labelled phrase-structure trees. Then we review some other models that instantiate the DOP approach. Many of these models also employ labelled phrase-structure trees, but use different criteria for extracting fragments from the corpus or employ different disambiguation strategies (Bod 1996b; Charniak 1996a/b; Goodman 1996; Rajman 1995a/b; Sekine & Grishman 1995; Sima'an 1995-96); other models use richer formalisms for their corpus annotations (van den Berg et al. 1994; Bod et al., 1996a/b; Bonnema 1996; Kaplan 1996; Tugwell 1995).Comment: 34 pages, Postscrip