We present the first comprehensive, open source multimedia knowledge extraction system
that takes a massive stream of unstructured, heterogeneous multimedia data from various …

One of the key requirements to facilitate the semantic analytics of information regarding
contemporary and historical events on the Web, in the news and in social media is the …

Relation Extraction suffers from dramatical performance decrease when training a model on
one genre and directly applying it to a new genre, due to the distinct feature distributions …

We focus on improving name tagging for low-resource languages using annotations from
related languages. Previous studies either directly project annotations from a source …

Within any scientific disciplines, a large amount of data are buried within various literature
depositories and archives, making it difficult to manually extract useful information from the …

An analyst or a planner seeking a rich, deep understanding of an emergent situation today is
faced with a paradox-multimodal, multilingual realtime information about most emergent …

Clustering unlinkable entity mentions across documents in multiple languages (cross-lingual
NIL Clustering) is an important task as part of Entity Discovery and Linking (EDL). This task …

Maritime security requires full-time monitoring of the situation, mainly based on technical
data (radar, AIS) but also from OSINT-like inputs (eg, newspapers). Some threats to the …

We propose Neural variational set expansion to extract actionable information from a noisy
knowledge graph (KG) and propose a general approach for increasing the interpretability of …

Knowledge Bases (KB) are used in many fields, such as business intelligence or user
assistance. They aggregate knowledge that can be exploited by computers to help decision …