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Many event monitoring systems rely on counting known keywords in streaming text data to detect sudden spikes in frequency. But the dynamic and conversational nature of Twitter makes it hard to select known keywords for monitoring. Here we consider a method of automatically finding noun phrases (NPs) as keywords for event monitoring in Twitter. Finding NPs has two aspects, identifying the boundaries for the subsequence of words which represent the NP, and classifying the NP to a specific broad category such as politics, sports, etc. To classify an NP, we define the feature vector for the NP using not just the words but also the author's behavior and social activities. Our results show that we can classify many NPs by using a sample of training data from a knowledge-base. © 2012 ACM.

Countability is a universal lexical category that provides a binary division of nouns into countable and uncountable nouns or is also called count and mass nouns. Usually, count nouns refer to things or objects which can be individuated and thus counted, while mass nouns refer to substances or stuff such as water,wine, blood, or mud for which it is less easy to identify what and how to count. This cognitive division leaves abstract nouns out. Abstract nouns neither refer to things or objects nor to substances or stuff. On the contrary, the reference of abstract nouns is rather heterogeneous comprising different kinds of nouns such as processes, states, events, measure and time terms, and alike. The aim of this paper is to present the challenges abstract nouns pose for theories of countability, and to reflect on possibilities to incorporate abstract nouns in contemporary theories of countability. The research discussed in this paper circles around English abstract nouns but we will also discuss the application of certain semantic phenomena onto Bosnian nouns.

Introduction. The aim of the article is to determine whether syntactic behavior of linguistic unit depends on its part-of-speech identity or only its semantics. The importance of the research is determined by the absence of systematic description of the specificity of cognate words functioning in linguistics.Methodology and sources. The research deals with the cognate nouns and adjectives functioning. According to the classification of semantic types of predicates developed by A. G. Eliseeva, O. N. Seliverstova we define the researched predicates as the ones denoting state. These predicates are studied in terms of case grammar, i. e. they are compared in the aspect of an argument structure realization. In determining the semantic cases of predicates, we mainly rely on the set of semantic cases proposed by V. V. Bogdanov.Results and discussion. It is shown that the analyzed nouns, as a rule, expressing given or known information require a lower number of cases in its explicit forms which still can be implicit. The researched adjectives that usually denote new information are accompanied by a higher number of cases in a surface structure. These predicates also differ in the forms of their arguments.Conclusion. The revealed features of cognate nouns and adjectives functioning show the significant influence of the form of linguistic unit on syntactic behavior and indicate that formation of syntactic structures is not only determined by semantics.

The article discusses the onomastic conversion (lexical-semantic method) - a nominal, i.e. functional transfer of words is a common phenomenon in the language, in which the transfer of a lexeme from one-word group to another word group, the transition of appellate lexicon to a noun without any constructive means. In language, the transition of words from one category to another is uninterrupted, because word groups themselves are not a phenomenon with a fixed boundary, as a result of the constant movement of language, words tend to move towards one lexical-grammatical category and perform their function. Language development occurs through events such as derivation, transformation, transposition, and conversion.

ProposeThe purpose of this paper is to propose a local orientation and navigation framework based on visual features that provide location recognition, context augmentation, and viewer localization information to a blind or low‐vision user.Design/methodology/approachThe authors consider three types of "visual noun" features: signage, visual‐text, and visual‐icons that are proposed as a low‐cost method for augmenting environments. These are used in combination with an RGB‐D sensor and a simplified SLAM algorithm to develop a framework for navigation assistance suitable for the blind and low‐vision users.FindingsIt was found that signage detection cannot only help a blind user to find a location, but can also be used to give accurate orientation and location information to guide the user navigating a complex environment. The combination of visual nouns for orientation and RGB‐D sensing for traversable path finding can be one of the cost‐effective solutions for navigation assistance for blind and low‐vision users.Research limitations/implicationsThis is the first step for a new approach in self‐localization and local navigation of a blind user using both signs and 3D data. The approach is meant to be cost‐effective but it only works in man‐made scenes where a lot of signs exist or can be placed and are relatively permanent in their appearances and locations.Social implicationsBased on 2012 World Health Organization, 285 million people are visually impaired, of which 39 million are blind. This project will have a direct impact on this community.Originality/valueSignage detection has been widely studied for assisting visually impaired people in finding locations, but this paper provides the first attempt to use visual nouns as visual features to accurately locate and orient a blind user. The combination of visual nouns with 3D data from an RGB‐D sensor is also new.