This article presents a measure of semantic similarity in an IS-A taxonomy based on the notion of shared information content. Experimental evaluation against a benchmark set of human similarity judgments demonstrates that the measure performs better than the traditional edge-counting approach. The article presents algorithms that take advantage of taxonomic similarity in resolving syntactic and semantic ambiguity, along with experimental results demonstrating their effectiveness.

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Semantic similarity in a taxonomy: an information-based measure and its application to problems of ambiguity in natural language

http://oro.open.ac.uk/3271/1/Expertise_Overview.pdf

Expertise in Design: an overview

The Ecology and Semiotics of Language Learning

The study of speech production has largely been divided into investigations of lower-level articulatory motor control and of higher-level linguistic processing, with these research traditions rarely interacting. In this Opinion article, Hickok argues that these approaches have much to offer each other, and he presents a model of speech production that incorporates ideas from both research traditions and findings from neuroscientific studies of sensorimotor integration. Speech production has been studied predominantly from within two traditions, psycholinguistics and motor control. These traditions have rarely interacted, and the resulting chasm between these approaches seems to reflect a level of analysis difference: whereas motor control is concerned with lower-level articulatory control, psycholinguistics focuses on higher-level linguistic processing. However, closer examination of both approaches reveals a substantial convergence of ideas. The goal of this article is to integrate psycholinguistic and motor control approaches to speech production. The result of this synthesis is a neuroanatomically grounded, hierarchical state feedback control model of speech production.

/pdf/computational-neuroanatomy-of-speech-production-4gegz6kngn.pdf

Computational neuroanatomy of speech production

Molecular Informatics utilises many ideas and concepts to find relationships between molecules. The concept of similarity, where molecules may be grouped according to their biological effects or physicochemical properties has found extensive use in drug discovery. Some areas of particular interest have been in lead discovery and compound optimisation. For example, in designing libraries of compounds for lead generation, one approach is to design sets of compounds ‘similar’ to known active compounds in the hope that alternative molecular structures are found that maintain the properties required while enhancing e.g. patentability, medicinal chemistry opportunities or even in achieving optimised pharmacokinetic profiles. Thus the practical importance of the concept of molecular similarity has grown dramatically in recent years. The predominant users are pharmaceutical companies, employing similarity methods in a wide range of applications e.g. virtual screening, estimation of absorption, distribution, metabolism, excretion and toxicity (ADME/Tox) and prediction of physicochemical properties (solubility, partitioning etc.). In this perspective, we discuss the representation of molecular structure (descriptors), methods of comparing structures and how these relate to measured properties. This leads to the concept of molecular similarity, its various definitions and uses and how these have evolved in recent years. Here, we wish to evaluate and in some cases challenge accepted views and uses of molecular similarity. Molecular similarity, as a paradigm, contains many implicit and explicit assumptions in particular with respect to the prediction of the binding and efficacy of molecules at biological receptors. The fundamental observation is that molecular similarity has a context which both defines and limits its use. The key issues of solvation effects, heterogeneity of binding sites and the fundamental problem of the form of similarity measure to use are addressed.

Ann J. Grafstein

Papers

MIT Encyclopedia of the Cognitive Sciences

Columbia Granger’s World of Poetry