Visualizing the meaning of texts

We implemented SmartINFO, an experimental system for the visualization of the meaning of texts. SmartINFO consists of 4 modules: a universal grammar engine (UGE), an anaphora engine, a concept engine and a visualization engine. We discuss two methods of visualizing meanings of text. One approach is a word-centered approach and the other, a clausal-centered approach. © 2005 IEEE

Digital Presentation of Bulgarian Lexical Heritage. Towards an Electronic Historical Dictionary

The article presents the results of the project “ICT Tools for Historical Linguistic Studies”, funded by the European Social Fund, OP Human Resources. The main project goal was to elaborate electronic tools for creating a Historical Dictionary of Diachronic Type that should present the history of the Bulgarian words from their first written occurrence until today. By the end of the project the team (Faculty of Slavic Studies at Sofia University, Institute for Bulgarian Language, BAS and PAM Publishing Company, Sofia) had at their disposal a set of Old Bulgarian Unicode fonts, meant for publishing medieval texts and a convertor that converts non-Unicode documents into the new standard. The convertor allowed the participants to create in a relatively short time a Diachronic text corpus of Bulgarian medieval texts, containing already more than 90 texts dated from the 10th to the 18th century. The corpus software enables editing the texts and turned out to be an excellent tool for preparing electronic editions of the Old Bulgarian (OCS) manuscripts. In addition to the corpus an electronic dictionary of Old Bulgarian is available, which contains the digitized version of Старобългарски речник, produced by IBL. Both tools are accessible on the project website at the address histdict.uni-sofia.bg. The Standard of the Historical Dictionary took shape during the project course and respective software for elaborating new dictionary entries was designed and tested. The article also displays screenshots that demonstrate the functionalities of both the corpus and dictionary software.The article presents the results of the project “ICT Tools for Historical Linguistic Studies”, funded by the European Social Fund, OP Human Resources

WEST: A Web Browser for Small Terminals

We describe WEST, a WEb browser for Small Terminals, that aims to solve some of the problems associated with accessing web pages on hand-held devices. Through a novel combination of text reduction and focus+context visualization, users can access web pages from a very limited display environment, since the system will provide an overview of the contents of a web page even when it is too large to be displayed in its entirety. To make maximum use of the limited resources available on a typical hand-held terminal, much of the most demanding work is done by a proxy server, allowing the terminal to concentrate on the task of providing responsive user interaction. The system makes use of some interaction concepts reminiscent of those defined in the Wireless Application Protocol (WAP), making it possible to utilize the techniques described here for WAP-compliant devices and services that may become available in the near future

Automatic text scoring using neural networks

Automated Text Scoring (ATS) provides a cost-effective and consistent alternative to human marking. However, in order to achieve good performance, the predictive features of the system need to be manually engineered by human experts. We introduce a model that forms word representations by learning the extent to which specific words contribute to the text’s score. Using Long-Short Term Memory networks to represent the meaning of texts, we demonstrate that a fully automated framework is able to achieve excellent results over similar approaches. In an attempt to make our results more interpretable, and inspired by recent advances in visualizing neural networks, we introduce a novel method for identifying the regions of the text that the model has found more discriminative.This is the accepted manuscript. It is currently embargoed pending publication

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