Temporal information retrieval has been a topic of great interest in recent years. Its purpose
is to improve the effectiveness of information retrieval methods by exploiting temporal …

Question answering over knowledge graphs (KG-QA) is a vital topic in IR. Questions with
temporal intent are a special class of practical importance, but have not received much …

Extraction and normalization of temporal expressions from documents are important steps
towards deep text understanding and a prerequisite for many NLP tasks such as information …

Objectives To provide an overview of the problem of temporal reasoning over clinical text
and to summarize the state of the art in clinical natural language processing for this task …

The study of temporal dynamics and its impact can be framed within the so-called temporal
IR approaches, which explain how user behavior, document content and scale vary with …

Extracting time expressions from free text is a fundamental task for many applications. We
analyze the time expressions from four datasets and find that only a small group of words …

History helps us understand the present and even to predict the future to certain extent.
Given the huge amount of data about the past, we believe computer science will play an …

Time expression (aka, timex) recognition and normalization (TERN) is a crucial task for
downstream research. However, previous studies have overlooked the critical …

Time expressions and named entities play important roles in data mining, information
retrieval, and natural language processing. However, the conventional position-based …

In the last few years, open-domain question answering (ODQA) has advanced rapidly due to
the development of deep learning techniques and the availability of large-scale QA datasets …