Temporal Information Processing: A Survey

Abstract

Temporal Information Processing is a subfield of Natural Language Processing, valuable in many tasks like Question Answering and Summarization. Temporal Information Processing is broadened, ranging from classical theories of time and language to current computational approaches for Temporal Information Extraction. This later trend consists on the automatic extraction of events and temporal expressions. Such issues have attracted great attention especially with the development of annotated corpora and annotations schemes mainly TimeBank and TimeML. In this paper, we give a survey of Temporal Information Extraction from Natural Language texts.

Information extraction from electronic medical documents: state of the art and future research directions

“…Indeed, understanding the semantic relations between enti-ties is required for many applications in IE such as semantic knowledge bases construction to infer the relationships between entities, and development of question answering systems for text summarization or concepts taxonomy construction. Semantic relations can be classified into two families according to their types, paradigmatic relations and syntagmatic relations [15]. Mainly, paradigmatic relations are operating on concepts of the same class.…”

Information Extraction in the Medical Domain

“…Many applications in information extraction, natural language understanding, or information retrieval require an understanding of the semantic relations between entities. There are several types of semantic relations, grouped into two main families, paradigmatic relations and syntagmatic relations see the survey of (Berrazega, 2012).…”

“…The IE is a research subject that covers many areas like customer care, personal information management, bio-informatics, community web sites. As it is mentioned in (Berrazega, 2012); these applications require IE for searching and responding queries.…”