This survey paper aims at summarizing the state of the art of computational semantic methods in speech recognition and understanding research. A taxonomy classifying the approaches adopted in the literature is divided into six main categories: semantic networks, semantic grammars, caseframes, statistical, unification-based and neural networks. For each approach, an overview of the variety of us...

In this paper, we extend some usual techniques of classification resulting from a large-scale data-mining and network approach. This new technology, which in particular is designed to be suitable to big data, is used to construct an open consolidated database from raw data on 4 million patents taken from the US patent office from 1976 onward. To build the pattern network, not only do we look at...

Email can be considered as a virtual working environment in which users are constantly struggling to manage the vast amount of exchanged data. Although most of this data belongs to well-defined workflows, these are implicit and largely unsupported by existing email clients. Semanta provides this support by enabling Semantic Email – email enhanced with machine-processable metadata about specific...

Automatic hypertext classification is an essential technique for organizing vast amount of Internet Web pages or HTML documents. One the of problems in classifying Web pages is that Web pages are usually short and contain insufficient text to clearly identify its category. Text classification mechanisms, by analyzing only the contents of the document itself, are relatively ineffective in classi...

A crucial step toward the goal of automatic extraction of propositional information from natural language text is the identification of semantic relations between constituents in sentences. We examine the problem of distinguishing among seven relation types that can occur between the entities “treatment” and “disease” in bioscience text, and the problem of identifying such entities. We compare ...

To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images into semantic categories based on trained pattern classifiers have become active research trends. In this paper, we present dual cascading learning frameworks that extract and combine intraimage and inter-class semant...

We investigate the effectiveness of semantic generalizations/classifications for capturing the regularities of the behavior of verbs in terms of their metaphoricity. Starting from orthographic word unigrams, we experiment with various ways of defining semantic classes for verbs (grammatical, resource-based, distributional) and measure the effectiveness of these classes for classifying all verbs...

Mathematical semantic web services are very useful in practice, but only a small number of research results are reported in this area. In this paper we present a method of obtaining an approximation of a mathematical semantic web service, from its semantic description, using existing mathematical semantic web services, approximation formulas, and numerical methods techniques. We also give a met...

We examine the impact on classification effectiveness of semantic differences in categories. Specifically, we measure broadness and narrowness of categories in terms of their distance to the root of a hierarchically organized thesaurus. Using categories of four different levels degrees of broadness, we show that classifying documents into narrow categories gives better scores than classifying t...

to write the history of arab literature, contemporary arab writers have used different methods. these methods differ from each other and each one has some advantages over the other methods, although there are some commonalities between them in classifying different stages of arab literature, the manner of introducing poets and writers, reviewing different types of poem and prose, and interpreti...