Equipping machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

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 …

We present YAGO2, an extension of the YAGO knowledge base, in which entities, facts, and
events are anchored in both time and space. YAGO2 is built automatically from Wikipedia …

Abstract Knowledge graph (KG) completion adds new facts to a KG by making inferences
from existing facts. Most existing methods ignore the time information and only learn from …

We propose a new graph-based label propagation algorithm for transductive learning. Each
example is associated with a vertex in an undirected graph and a weighted edge between …

Motivated by the increasing availability of vehicle trajectory data, we propose learn-to-route,
a comprehensive trajectory-based routing solution. Specifically, we first construct a graph …

Users often need to gather information about" entities" of interest. Recent efforts try to
automate this task by leveraging the vast corpus of HTML tables; this is referred to as" entity …

One of the main tasks when creating and maintaining knowledge bases is to validate facts
and provide sources for them in order to ensure correctness and traceability of the provided …

Vehicle routing is an important service that is used by both private individuals and
commercial enterprises. Drivers may have different contexts that are characterized by …

Recent research has made significant advances in automatically constructing knowledge
bases by extracting relational facts (eg, Bill Clinton-presidentOf-US) from large text corpora …