Abstract The Semantic Web contains an enormous amount of information in the form of
knowledge bases (KB). To make this information available, many question answering (QA) …

Question answering systems (QASs) generate answers of questions asked in natural
languages. Early QASs were developed for restricted domains and have limited capabilities …

Over the past decade, large-scale supervised learning corpora have enabled machine
learning researchers to make substantial advances. However, to this date, there are no large …

We study open-domain question answering with structured, unstructured and semi-
structured knowledge sources, including text, tables, lists and knowledge bases. Departing …

Abstract Semantic Question Answering (SQA) removes two major access requirements to
the Semantic Web: the mastery of a formal query language like SPARQL and knowledge of …

The question answering system is frequently applied in the area of natural language
processing (NLP) because of the wide variety of applications. It consists of answering …

This article provides a comprehensive overview of the broad area of semantic search on text
and knowledge bases. In a nutshell, semantic search is “search with meaning”. This …

The need to query information content available in various formats including structured and
unstructured data (text in natural language, semi-structured Web documents, structured RDF …

With the development of the Semantic Web, a lot of new structured data has become
available on the Web in the form of knowledge bases (KBs). Making this valuable data …

Generating answer with natural language sentence is very important in real-world question
answering systems, which needs to obtain a right answer as well as a coherent natural …