Demo Data from VLDB 2026 / reviewers in the wild / expert
Frizzi Alejandra San Roman Salazar
dblp:143/9605 · also Frizzi San Roman
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval › search interfaces
search result presentation |
0.2 | 1 | 2014 | Similarity Preserving Snippet-Based Visualization of Web Search Results · IEEE Trans. Vis. Comput. Graph. 2014 |
Visualization and visual analytics › information visualization › information retrieval visualization
search result visualization |
0.2 | 1 | 2014 | Similarity Preserving Snippet-Based Visualization of Web Search Results · IEEE Trans. Vis. Comput. Graph. 2014 |
Visualization and visual analytics
text visualization |
0.2 | 1 | 2014 | Similarity Preserving Snippet-Based Visualization of Web Search Results · IEEE Trans. Vis. Comput. Graph. 2014 |
Methods — techniques the papers use, named apart from their topics
multidimensional projection · 0.4energy functional minimization · 0.4cosine similarity · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Similarity Preserving Snippet-Based Visualization of Web Search ResultsabstractInternet users are very familiar with the results of a search query displayed as a ranked list of snippets. Each textual snippet shows a content summary of the referred document (or webpage) and a link to it. This display has many advantages, for example, it affords easy navigation and is straightforward to interpret. Nonetheless, any user of search engines could possibly report some experience of disappointment with this metaphor. Indeed, it has limitations in particular situations, as it fails to provide an overview of the document collection retrieved. Moreover, depending on the nature of the query--for example, it may be too general, or ambiguous, or ill expressed--the desired information may be poorly ranked, or results may contemplate varied topics. Several search tasks would be easier if users were shown an overview of the returned documents, organized so as to reflect how related they are, content wise. We propose a visualization technique to display the results of web queries aimed at overcoming such limitations. It combines the neighborhood preservation capability of multidimensional projections with the familiar snippet-based representation by employing a multidimensional projection to derive two-dimensional layouts of the query search results that preserve text similarity relations, or neighborhoods. Similarity is computed by applying the cosine similarity over a "bag-of-words" vector representation of collection built from the snippets. If the snippets are displayed directly according to the derived layout, they will overlap considerably, producing a poor visualization. We overcome this problem by defining an energy functional that considers both the overlapping among snippets and the preservation of the neighborhood structure as given in the projected layout. Minimizing this energy functional provides a neighborhood preserving two-dimensional arrangement of the textual snippets with minimum overlap. The resulting visualization conveys both a global view of the query results and visual groupings that reflect related results, as illustrated in several examples shown. Erick Gomez Nieto, Frizzi Alejandra San Roman Salazar, Paulo A. Pagliosa, Wallace Casaca, Elias Salomão Helou Neto, Maria Cristina Ferreira de Oliveira, Luis Gustavo Nonato |
IEEE Trans. Vis. Comput. Graph. | 2 |