Exploratory topic modeling with distributional semantics

As we continue to collect and store textual data in a multitude of domains, we are regularly confronted with material whose largely unknown thematic structure we want to uncover. With unsupervised, exploratory analysis, no prior knowledge about the content is required and highly open-ended tasks can be supported. In the past few years, probabilistic topic modeling has emerged as a popular approach to this problem. Nevertheless, the representation of the latent topics as aggregations of semi-coherent terms limits their interpretability and level of detail. This paper presents an alternative approach to topic modeling that maps topics as a network for exploration, based on distributional semantics using learned word vectors. From the granular level of terms and their semantic similarity relations global topic structures emerge as clustered regions and gradients of concepts. Moreover, the paper discusses the visual interactive representation of the topic map, which plays an important role in supporting its exploration.Comment: Conference: The Fourteenth International Symposium on Intelligent Data Analysis (IDA 2015

A Word Sense-Oriented User Interface for Interactive Multilingual Text Retrieval

In this paper we present an interface for supporting a user in an interactive cross-language search process using semantic classes. In order to enable users to access multilingual information, different problems have to be solved: disambiguating and translating the query words, as well as categorizing and presenting the results appropriately. Therefore, we first give a brief introduction to word sense disambiguation, cross-language text retrieval and document categorization and finally describe recent achievements of our research towards an interactive multilingual retrieval system. We focus especially on the problem of browsing and navigation of the different word senses in one source and possibly several target languages. In the last part of the paper, we discuss the developed user interface and its functionalities in more detail

Issues of shaping the students’ professional and terminological competence in science area of expertise in the sustainable development era

The paper deals with the problem of future biology teachers’ vocational preparation process and shaping in them of those capacities that contribute to the conservation and enhancement of our planet’s biodiversity as a reflection of the leading sustainable development goals of society. Such personality traits are viewed through the prism of forming the future biology teachers’ professional and terminological competence. The main aspects and categories that characterize the professional and terminological competence of future biology teachers, including terminology, nomenclature, term, nomen and term element, have been explained. The criteria and stages of shaping the future biology teachers’ professional and terminological competence during the vocational training process have been fixed. Methods, techniques, technologies, guiding principles and forms of staged work on the forming of an active terminological dictionary of students have been described and specified. The content of the distant special course “Latin. Botanical Terminology”, which provides training for future teachers to study the professional subjects and to understand of international scientific terminology, has been presented. It is concluded that the proper level of formation of the future biology teachers’ professional and terminological competence will eventually ensure the qualitative preparation of pupils for life in a sustainable development era

Exploring narrativity in data visualization in journalism

Many news stories are based on data visualization, and storytelling with data has become a buzzword in journalism. But what exactly does storytelling with data mean? When does a data visualization tell a story? And what are narrative constituents in data visualization? This chapter first defines the key terms in this context: story, narrative, narrativity, showing and telling. Then, it sheds light on the various forms of narrativity in data visualization and, based on a corpus analysis of 73 data visualizations, describes the basic visual elements that constitute narrativity: the instance of a narrator, sequentiality, temporal dimension, and tellability. The paper concludes that understanding how data are transformed into visual stories is key to understanding how facts are shaped and communicated in society