Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs   A visual-relational knowledge graph (KG) is a multi-relational graph whose
entities are associated with images. We explore novel machine learning
approaches for answering visual-relational queries in web-extracted knowledge
graphs. To this end, we have created ImageGraph, a KG with 1,330 relation
types, 14,870 entities, and 829,931 images crawled from the web. With
visual-relational KGs such as ImageGraph one can introduce novel probabilistic
query types in which images are treated as first-class citizens. Both the
prediction of relations between unseen images as well as multi-relational image
retrieval can be expressed with specific families of visual-relational queries.
We introduce novel combinations of convolutional networks and knowledge graph
embedding methods to answer such queries. We also explore a zero-shot learning
scenario where an image of an entirely new entity is linked with multiple
relations to entities of an existing KG. The resulting multi-relational
grounding of unseen entity images into a knowledge graph serves as a semantic
entity representation. We conduct experiments to demonstrate that the proposed
methods can answer these visual-relational queries efficiently and accurately.

31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
22
The categories of this paper are: chao-dyn
11
The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
3
The categories of this paper are: physics
25
The categories of this paper are: patt-sol
21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
20
The categories of this paper are: acc-phys
35
The categories of this paper are: mtrl-th
8
The categories of this paper are: hep-ex
16
The categories of this paper are: stat
23
The categories of this paper are: solv-int
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin