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 …

Question-answering plays an important role in e-commerce as it allows potential customers
to actively seek crucial information about products or services to help their purchase …

In customer service technical support, swiftly and accurately retrieving relevant past issues is
critical for efficiently resolving customer inquiries. The conventional retrieval methods in …

Visual Question Answering (VQA) has attracted much attention in both computer vision and
natural language processing communities, not least because it offers insight into the …

Training large-scale question answering systems is complicated because training sources
usually cover a small portion of the range of possible questions. This paper studies the …

Two important aspects of semantic parsing for question answering are the breadth of the
knowledge source and the depth of logical compositionality. While existing work trades off …

In this paper, we train a semantic parser that scales up to Freebase. Instead of relying on
annotated logical forms, which is especially expensive to obtain at large scale, we learn from …

Accurately answering a question about a given image requires combining observations with
general knowledge. While this is effortless for humans, reasoning with general knowledge …

This paper presents a system which learns to answer questions on a broad range of topics
from a knowledge base using few hand-crafted features. Our model learns low-dimensional …