Related papers: Topic Maps as a Virtual Observatory tool
Topic modelling is a popular unsupervised method for identifying the underlying themes in document collections that has many applications in information retrieval. A topic is usually represented by a list of terms ranked by their…
With VODataService 1.2, service providers in the Virtual Observatory (VO) have a reasonably straightforward way to declare where in space, time, and spectrum the data within a resource (i.e., service or data collection) lie. Here, we…
A major difficulty in applying word vector embeddings in IR is in devising an effective and efficient strategy for obtaining representations of compound units of text, such as whole documents, (in comparison to the atomic words), for the…
Concept maps can be used to concisely represent important information and bring structure into large document collections. Therefore, we study a variant of multi-document summarization that produces summaries in the form of concept maps.…
Organizing a few webpages from social media websites into popular topics is one of the key steps to understand trends on web. Discovering popular topics from web faces a sea of noise webpages which never evolve into popular topics. In this…
Within the documentary system domain, the integration of thesauri for indexing and retrieval information steps is usual. In libraries, documents own rich descriptive information made by librarians, under descriptive notice based on Rameau…
High-dimensional data, characterized by many features, can be difficult to visualize effectively. Dimensionality reduction techniques, such as PCA, UMAP, and t-SNE, address this challenge by projecting the data into a lower-dimensional…
For users, recommendations can sometimes seem odd or counterintuitive. Visualizing recommendations can remove some of this mystery, showing how a recommendation is grouped with other choices. A drawing can also lead a user's eye to other…
Topic modeling is an unsupervised method for revealing the hidden semantic structure of a corpus. It has been increasingly widely adopted as a tool in the social sciences, including political science, digital humanities and sociological…
Topological mapping offers a compact and robust representation for navigation, but progress in the field is hindered by the lack of standardized evaluation metrics, datasets, and protocols. Existing systems are assessed using different…
Topic segmentation and labeling is often considered a prerequisite for higher-level conversation analysis and has been shown to be useful in many Natural Language Processing (NLP) applications. We present two new corpora of email and blog…
The VOEvent standard provides a means of describing transient celestial events in a machine-readable format. This is an essential step towards analysing and, where appropriate, responding to the large volumes of transients which will be…
Topic models are a useful analysis tool to uncover the underlying themes within document collections. The dominant approach is to use probabilistic topic models that posit a generative story, but in this paper we propose an alternative way…
The map of elections framework is a methodology for visualizing and analyzing election datasets. So far, the framework was restricted to elections that have equal numbers of candidates, equal numbers of voters, and where all the (ordinal)…
Choropleth maps are a common visual representation for region-specific tabular data and are used in a number of different venues (newspapers, articles, etc). These maps are human-readable but are often challenging to deal with when trying…
Topic modelling is a text mining technique for identifying salient themes from a number of documents. The output is commonly a set of topics consisting of isolated tokens that often co-occur in such documents. Manual effort is often…
The Virtual Observatory has reached sufficient maturity for its routine scientific exploitation by astronomers. To prove this statement, here I present a brief description of the complete VO-powered PhD thesis entitled "Galactic and…
Tag clouds provide an aggregate of tag-usage statistics. They are typically sent as in-line HTML to browsers. However, display mechanisms suited for ordinary text are not ideal for tags, because font sizes may vary widely on a line. As…
Topic models provide a useful tool to organize and understand the structure of large corpora of text documents, in particular, to discover hidden thematic structure. Clustering documents from big unstructured corpora into topics is an…
Vision-language models (VLMs) excel at tasks requiring joint understanding of visual and linguistic information. A particularly promising yet under-explored application for these models lies in answering questions based on various kinds of…