@InProceedings{jiang-EtAl:2016:COLING2,
  author    = {Jiang, Tingsong  and  Liu, Tianyu  and  Ge, Tao  and  Sha, Lei  and  Chang, Baobao  and  Li, Sujian  and  Sui, Zhifang},
  title     = {Towards Time-Aware Knowledge Graph Completion},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {1715--1724},
  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
	time-unknown
	fact triples. In dynamic environments that evolve over time, it is important
	and challenging
	for knowledge graph completion models to take into account the temporal aspects
	of facts. In
	this paper, we present a novel time-aware knowledge graph completion model that
	is able to
	predict links in a KG using both the existing facts and the temporal
	information of the facts. To
	incorporate the happening time of facts, we propose a time-aware KG embedding
	model using
	temporal order information among facts. To incorporate the valid time of facts,
	we propose
	a joint time-aware inference model based on Integer Linear Programming (ILP)
	using temporal
	consistencyinformationasconstraints.
	Wefurtherintegratetwomodelstomakefulluseofglobal
	temporal information. We empirically evaluate our models on time-aware KG
	completion task.
	Experimental results show that our time-aware models achieve the
	state-of-the-art on temporal
	facts consistently.
	Author{7}{Affiliation}},
  url       = {http://aclweb.org/anthology/C16-1161}
}