Concepts, Frames and Cascades in Semantics, Cognition and Ontology

This open access book presents novel theoretical, empirical and experimental work exploring the nature of mental representations that support natural language production and understanding, and other manifestations of cognition. One fundamental question raised in the text is whether requisite knowledge structures can be adequately modeled by means of a uniform representational format, and if so, what exactly is its nature. Frames are a key topic covered which have had a strong impact on the exploration of knowledge representations in artificial intelligence, psychology and linguistics; cascades are a novel development in frame theory. Other key subject areas explored are: concepts and categorization, the experimental investigation of mental representation, as well as cognitive analysis in semantics. This book is of interest to students, researchers, and professionals working on cognition in the fields of linguistics, philosophy, and psychology

Categories and classifications in EuroWordNet

In EuroWordNet we develop wordnets in 8 European languages, which are structured along the same lines as the Princeton WordNet. The wordnets are inter-linked in a multilingual database, where they can be compared. This comparison reveals many different lexicalizations of classes across the languages that also lead to important differences in the hierarchical structure of the wordnets. It is not feasible to include all these classes (the superset) in each language-specific wordnet and to reach consensus on the implicational effects across all the languages. Each wordnet is therefore limited to the lexicalized words and expressions of a language. The wordnets are thus autonomous language-specific structures that capture valuable information about the lexicalization of each language, which is important for information retrieval, machine translation and language generation. By connecting the wordnets to a separate ontology, semantic inferencing can still be guaranteed. Still, different types of classification schemes can be distinguished among the lexicalized classes. In this paper we will further describe the properties of these different classes and discuss the advantages and effects of distinguishing them in wordnet-like structures

Information Extraction from Text for Improving Research on Small Molecules and Histone Modifications

The cumulative number of publications, in particular in the life sciences, requires efficient methods for the automated extraction of information and semantic information retrieval. The recognition and identification of information-carrying units in text – concept denominations and named entities – relevant to a certain domain is a fundamental step. The focus of this thesis lies on the recognition of chemical entities and the new biological named entity type histone modifications, which are both important in the field of drug discovery. As the emergence of new research fields as well as the discovery and generation of novel entities goes along with the coinage of new terms, the perpetual adaptation of respective named entity recognition approaches to new domains is an important step for information extraction. Two methodologies have been investigated in this concern: the state-of-the-art machine learning method, Conditional Random Fields (CRF), and an approximate string search method based on dictionaries. Recognition methods that rely on dictionaries are strongly dependent on the availability of entity terminology collections as well as on its quality. In the case of chemical entities the terminology is distributed over more than 7 publicly available data sources. The join of entries and accompanied terminology from selected resources enables the generation of a new dictionary comprising chemical named entities. Combined with the automatic processing of respective terminology – the dictionary curation – the recognition performance reached an F1 measure of 0.54. That is an improvement by 29 % in comparison to the raw dictionary. The highest recall was achieved for the class of TRIVIAL-names with 0.79. The recognition and identification of chemical named entities provides a prerequisite for the extraction of related pharmacological relevant information from literature data. Therefore, lexico-syntactic patterns were defined that support the automated extraction of hypernymic phrases comprising pharmacological function terminology related to chemical compounds. It was shown that 29-50 % of the automatically extracted terms can be proposed for novel functional annotation of chemical entities provided by the reference database DrugBank. Furthermore, they are a basis for building up concept hierarchies and ontologies or for extending existing ones. Successively, the pharmacological function and biological activity concepts obtained from text were included into a novel descriptor for chemical compounds. Its successful application for the prediction of pharmacological function of molecules and the extension of chemical classification schemes, such as the the Anatomical Therapeutic Chemical (ATC), is demonstrated. In contrast to chemical entities, no comprehensive terminology resource has been available for histone modifications. Thus, histone modification concept terminology was primary recognized in text via CRFs with a F1 measure of 0.86. Subsequent, linguistic variants of extracted histone modification terms were mapped to standard representations that were organized into a newly assembled histone modification hierarchy. The mapping was accomplished by a novel developed term mapping approach described in the thesis. The combination of term recognition and term variant resolution builds up a new procedure for the assembly of novel terminology collections. It supports the generation of a term list that is applicable in dictionary-based methods. For the recognition of histone modification in text it could be shown that the named entity recognition method based on dictionaries is superior to the used machine learning approach. In conclusion, the present thesis provides techniques which enable an enhanced utilization of textual data, hence, supporting research in epigenomics and drug discovery

Cognitive Sociology

Cognitive sociology is the study of the conditions under which meaning is constituted through processes of reification. Cognitive sociology traces its origins to writings in the sociology of knowledge, sociology of culture, cognitive and cultural anthropology, and more recently, work done in cultural sociology and cognitive science. Its central questions revolve around locating these processes of reification since the locus of cognition is highly contentious. Researchers consider how individuality is related to notions of society (structures, institutions, systems, etc.) and notions of culture (cultural forms, cultural structures, sub-cultures, etc.). These questions further explore how these answers depend on learning processes (socialization, acculturation, etc.) which vary according to the position one takes on the role of language in cognition. It is from these positions that we operationalize a theory of human nature and construct a justification for the organization of the state of human affairs and the related conceptualizations of identity, self, and the subject. In this way, cognitive sociology seeks to establish the minimal model of the actor (the ontology) that underpins not only other subfields of sociology but also the human sciences in general. In this way, cognitive sociology analyzes the series of interpersonal processes that set up the conditions for phenomena to become “social objects,” which subsequently shape thinking and thought. In classical cognitive sociology, the historical traditions of the sociology of knowledge and phenomenology are emphasized, with the work of Bourdieu and Goffman given special treatment, given their contributions as precursors to many of the contemporary contingencies and consequences of debates in culture and cognition. The principle organizing the more contemporary literature are the paradigmatic assumptions concerning the locus of cognition, which have been organized into five ideal-types. These elucidate the points of agreement and disagreement in the field by addressing how thematic concerns (e.g., knowledge, rationality, embodiment, practices, discourse, etc.) highlight the priority of individuality in modeling society, to illustrate what makes cognitive sociology at once interdisciplinary yet contentiously distinct in addressing the politics of “tacit knowledge.

On relationships between the logic of law, legal positivism and semiotics of law

The issue of reciprocal relationships between the logic of law, positivistic theory of the logic of law, and legal semiotics is among the most important questions of the modern theoretical jurisprudence. This paper has not attempted to provide any comprehensive account of the modern jurisprudence (and legal logic). Instead, the emphasis has been laid on those aspects of positivist legal theories, logical studies of law and legal semiotics that allow tracing the common points or the differences between these paradigms of legal research. One of the theses of the present work is that, at the comparative methodological level, the limits of legal semiotics and its object of inquiry could only be defined in relation to legal posi tivism and logical studies of law. This paper also argues for a proper position for legal semiotics in between legal positivism and legal logic. The differences between legal positivism, legal logic and legal semiotics are best captured in the issue of referent

Storing the wisdom: chemical concepts and chemoinformatics

The purpose of the paper is to examine the nature of chemical concepts, and the ways in which they are applied in chemoinformatics systems. An account of concepts in philosophy and in the information sciences leads to an analysis of chemical concepts, and their representation. The way in which concepts are applied in systems for information retrieval and for structure–property correlation are reviewed, and some issues noted. Attention is focused on the basic concepts or substance, reaction and property, on the organising concepts of chemical structure, structural similarity, periodicity, and on more specific concepts, including two- and three-dimensional structural patterns, reaction types, and property concepts. It is concluded that chemical concepts, despite (or perhaps because of) their vague and mutable nature, have considerable and continuing value in chemoinformatics, and that an increased formal treatment of concepts may have value in the future