In this article, we provide a comprehensive introduction to knowledge graphs, which have
recently garnered significant attention from both industry and academia in scenarios that …

We provide a comprehensive survey of the research literature that applies Information
Extraction techniques in a Semantic Web setting. Works in the intersection of these two …

The automatic extraction of information from unstructured sources has opened up new
avenues for querying, organizing, and analyzing data by drawing upon the clean semantics …

Table understanding methods extract, transform, and interpret the information contained in
tabular data embedded in documents/files of different formats. Such automatic …

This paper presents a novel approach for the detection of tables present in documents,
leveraging the potential of deep neural networks. Conventional approaches for table …

The prediction of tourist numbers is important for Destination Management and Marketing.
While most existing methods rely on well-structured statistical data, using web search …

This work addresses issues related to the design and implementation of focused crawlers.
Several variants of state-of-the-art crawlers relying on web page content and link information …

Tables in document images are an important entity since they contain crucial information.
Therefore, accurate table detection can significantly improve the information extraction from …

This paper presents PDF-TREX, an heuristic approach for table recognition and extraction
from PDF documents. The heuristics starts from an initial set of basic content elements and …

Table detection is a preliminary step in extracting reliable information from tables in scanned
document images. We present CasTabDetectoRS, a novel end-to-end trainable table …