Textual information is becoming available in abundance on the web, arising the requirement
of techniques and tools to extract the meaningful information. One of such an important …

This survey covers fifteen years of research in the Named Entity Recognition and
Classification (NERC) field, from 1991 to 2006. We report observations about languages …

Large-scale information processing systems are able to extract massive collections of
interrelated facts, but unfortunately transforming these candidate facts into useful knowledge …

In this survey, we provide an overview of the literature on knowledge graphs (KGs) in the
context of information retrieval (IR). Modern IR systems can benefit from information …

Semantic similarity measures play important roles in information retrieval and Natural
Language Processing. Previous work in semantic web-related applications such as …

Abstract With Linked Data, a very pragmatic approach towards achieving the vision of the
Semantic Web has gained some traction in the last years. The term Linked Data refers to a …

Recent years have seen a great deal of work that exploits collaborative, semi-structured
content for Artificial Intelligence (AI) and Natural Language Processing (NLP). This special …

Measuring the semantic similarity between words is an important component in various
tasks on the web such as relation extraction, community mining, document clustering, and …

Abstract, structured, representations of knowledge such as lexicons, taxonomies, and
ontologies have proven to be powerful resources not only for the systematization of …

Knowledge bases extracted automatically from the Web present new opportunities for data
mining and exploration. Given a large, heterogeneous set of extracted relations, new tools …