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 …

This review presents various perspectives on converting user keywords into a formal query.
Without understanding the dataset's underlying structure, how can a user input a text-based …

Question Answering (QA) systems over Knowledge Graphs (KGs) aim to provide a concise
answer to a given natural language question. Despite the significant evolution of QA …

This paper presents ParaQA, a question answering (QA) dataset with multiple paraphrased
responses for single-turn conversation over knowledge graphs (KG). The dataset was …

Billions of facts pertaining to a multitude of domains are now available on the Web as RDF
data. However, accessing this data is still a difficult endeavour for non-expert users. In order …

Abstract Semantic Question Answering (SQA) systems automatically interpret user questions
expressed in a natural language in terms of semantic queries. This process involves …

With the ever-growing generation of data for the Semantic Web comes an increasing
demand for this data to be made available to non-semantic Web experts. One way of …

In this paper we introduce Spartiqulation, a system that translates SPARQL queries into
English text. Our aim is to allow casual end users of semantic applications with limited to no …

The paper presents recent work on the design and development of AI chatbots for museums
using Knowledge Graphs (KGs). The utilization of KGs as a key technology for implementing …

Relational databases play an important role in business, science, and more. However, many
users cannot fully unleash the analytical power of relational databases, because they are …