Recent advancements in Natural Language Processing (NLP) have highlighted the success of transformer-based models in various tasks, including Named Entity Recognition (NER). This study evaluates and compares these models using GeoCorpus-3, Portuguese's most extensive annotated geological corpus. We investigate the performance of BERTimbau and XLM-RoBERTa models across 30 entity classes, incorporating both linear and CRF layers, and assess their effectiveness using micro, macro, and weighted F1-scores. Our results reveal that transformer models, particularly XLM-RoBERTa, achieve superior performance compared to previous methods. Statistical analysis indicates significant performance differences, with BERTimbau-Linear showing lower performance than the other models. This study provides a comprehensive evaluation of transformer models on a geological corpus and makes the updated corpus and models publicly available to advance research and development in this domain.

Abstract Node‐link infographics are visually very rich and can communicate messages effectively, but can be very difficult to create, often involving a painstaking and artisanal process. In this paper we present an investigation of node‐link visualizations for communication and how to better support their creation. We begin by breaking down these images into their basic elements and analyzing how they are created. We then present a set of techniques aimed at improving the creation workflow by bringing more flexibility and power to users, letting them manipulate all aspects of a node‐link diagram (layout, visual attributes, etc.) while taking into account the context in which it will appear. These techniques were implemented in a proof‐of‐concept prototype called GraphCoiffure, which was designed as an intermediary step between graph drawing/editing software and image authoring applications. We describe how GraphCoiffure improves the workflow and illustrate its benefits through practical examples.

MagnetViz was designed for the interactive manipulation of force-directed graph layouts, allowing the user to obtain visualizations based on the graph topology and/or the attributes of its nodes and edges. The user can introduce virtual magnets anywhere in the graph and these can be set to attract nodes and edges that fulfill user-defined criteria. When a magnet is placed, the force-directed nature of the layout forces it to reorganize itself in order to reflect the changes in the balance of forces, consequently changing the visualization into one that is more semantically relevant to the user. This paper describes MagnetViz’s concepts, illustrating them with examples and a case study based on a usage scenario. We also describe how the MagnetViz has evolved since its original version and present the evaluation of its latest version. This evaluation consists of two user studies aiming at assessing generated layout quality and how well the concepts can be apprehended and employed, and a task taxonomy assessment focusing on establishing which graph visualization tasks the technique is able to handle.

This paper presents an interactive physics-based technique for the exploration and dynamic reorganization of graph layouts that takes into account semantic properties which the user might need to emphasize. Many techniques have been proposed that take a graph as input and produce a visualization solely based on its topology, seldom ever relying on the semantic attributes of nodes and edges. These automatic topology-based algorithms might generate aesthetically interesting layouts, but they neglect information that might be important for the user. Among these are the force-directed or energy minimization algorithms, which use physics analogies to produce satisfactory layouts. They consist of applying forces on the nodes, which move until the physical system enters a state of mechanical equilibrium. We propose an extension of this metaphor to include tools for the interactive manipulation of such layouts. These tools are comprised of magnets, which attract nodes with user-specified criteria to the regions surrounding the magnets. Magnets can be nested and also used to intuitively perform set operations such as union and intersection, becoming thus an intuitive visual tool for sorting through the datasets. To evaluate the technique we discuss how they can be used to perform common graph visualization tasks.

A stock market investor relies on two schools of analysis of market behavior to determine a trading strategy: Technical Analysis and Fundamental Analysis. Fundamental Analysis is based on the study of the fundamental data of a company and more directed to long-term investments, not taking into account small short-term price oscillations. On the other hand, Technical Analysis is mostly used for mid and short-term investments and is based on the study of past price behavior through the use of statistical tools and price history charts, taking into consideration the hypothesis that prices form patterns and reflect all the relevant information about a company and about the psychology of other investors. The application of Technical Analysis requires a computational system capable of displaying price history charts and providing tools to be used with them. This paper presents a prototype for a portable, extensible and easy-to-use tool for desktop/laptop and handheld computers that provides the investor with techniques for the visualization of stock market data. Classical visualization techniques and tools, such as Line, Bar, Candlestick and Point and Figure Charts, as well as extra tools, such as candlestick pattern recognition, are available as built-in functions, but new tools and visualizations can be easily added. The software was built with the .NET and .NET Compact frameworks and utilizes XML to store the data set.