Sara Elena Garza Villarreal

Learn More
In the midst of a developing Web that increases its size with a constant rhythm, automatic document organization becomes important. One way to arrange documents is by categorizing them into topics. Even when there are different forms to consider topics and their extraction, a practical option is to view them as document groups and apply clustering(More)
In a Web of increasing size and complexity, a key issue is automatic document organization, which includes topic extraction in collections. Since we consider topics as document clusters with semantic properties, we are concerned with exploring suitable clustering techniques for their identification on hyperlinked environments (where we only regard(More)
The structure of scientific collaboration networks provides insight on the relationships between people and disciplines. In this paper, we study a bipartite graph connecting authors to publications and extract from it clusters of authors and articles, interpreting the author clusters as research groups and the article clusters as research topics.(More)
Augmented-reality (AR) interfaces are receiving growing attention due to their versatility and usefulness in numerous application areas. In this paper, we tackle the problem of environmental awareness in consumers at the time of purchase: we design, implement, and evaluate a novel interface for overlaying product ecological information in the consumer's(More)
This paper introduces an approach for discovering thematically related document groups (a topic mining task) in massive document collections with the aid of graph local clustering. This can be achieved by viewing a document collection as a directed graph where vertices represent documents and arcs represent connections among these (e.g. hyperlinks). Because(More)
  • 1