A survey of location prediction on twitter
Locations, eg, countries, states, cities, and point-of-interests, are central to news, emergency
events, and people's daily lives. Automatic identification of locations associated with or …
events, and people's daily lives. Automatic identification of locations associated with or …
Learning entity type embeddings for knowledge graph completion
Missing data is a severe problem for algorithms that operate over knowledge graphs (KGs).
Most previous research in KG completion has focused on the problem of inferring missing …
Most previous research in KG completion has focused on the problem of inferring missing …
S-mart: Novel tree-based structured learning algorithms applied to tweet entity linking
Non-linear models recently receive a lot of attention as people are starting to discover the
power of statistical and embedding features. However, tree-based models are seldom …
power of statistical and embedding features. However, tree-based models are seldom …
Multimodal entity linking for tweets
In many information extraction applications, entity linking (EL) has emerged as a crucial task
that allows leveraging information about named entities from a knowledge base. In this …
that allows leveraging information about named entities from a knowledge base. In this …
Tweetnerd-end to end entity linking benchmark for tweets
Abstract Named Entity Recognition and Disambiguation (NERD) systems are foundational
for information retrieval, question answering, event detection, and other natural language …
for information retrieval, question answering, event detection, and other natural language …
Inferring missing entity type instances for knowledge base completion: New dataset and methods
Most of previous work in knowledge base (KB) completion has focused on the problem of
relation extraction. In this work, we focus on the task of inferring missing entity type instances …
relation extraction. In this work, we focus on the task of inferring missing entity type instances …
Attention-based multimodal entity linking with high-quality images
Multimodal entity linking (MEL) is an emerging research field which uses both textual and
visual information to map an ambiguous mention to an entity in a knowledge base (KB) …
visual information to map an ambiguous mention to an entity in a knowledge base (KB) …
Reddit entity linking dataset
We introduce and make publicly available an entity linking dataset from Reddit that contains
17,316 linked entities, each annotated by three human annotators and then grouped into …
17,316 linked entities, each annotated by three human annotators and then grouped into …
An attention factor graph model for tweet entity linking
The rapid expansion of Twitter has attracted worldwide attention. With more than 500 million
tweets posted per day, Twitter becomes an invaluable information and knowledge source …
tweets posted per day, Twitter becomes an invaluable information and knowledge source …
Building a multimodal entity linking dataset from tweets
The task of Entity linking, which aims at associating an entity mention with a unique entity in
a knowledge base (KB), is useful for advanced Information Extraction tasks such as relation …
a knowledge base (KB), is useful for advanced Information Extraction tasks such as relation …