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 …

Abstract Knowledge graph embedding aims at modeling entities and relations with low-dimensional
vectors. Most previous methods require that all entities should be seen during …

In this paper, we propose RNN-Capsule, a capsule model based on Recurrent Neural
Network (RNN) for sentiment analysis. For a given problem, one capsule is built for each …

Chinese spelling check (CSC) is a challenging yet meaningful task, which not only serves
as a preprocessing in many natural language processing (NLP) applications, but also …

In this work, the alternating multi-layer structured reduced graphene oxide&polyether
sulfone (RGO x &PES y ) film is fabricated via a facile thermal pressure process, which has …

Identifying the named entities mentioned in text would enrich many semantic applications at
the downstream level. However, due to the predominant usage of colloquial language in …

Entity disambiguation, also known as entity linking, is the task of mapping mentions in text to
the corresponding entities in a given knowledge base, eg Wikipedia. Two key challenges …

Hypertext documents, such as web pages and academic papers, are of great importance in
delivering information in our daily life. Although being effective on plain documents, …

Many users casually reveal their locations such as restaurants, landmarks, and shops in their
tweets. Recognizing such fine-grained locations from tweets and then linking the location …

Knowledge bases have shown their effectiveness in facilitating services like Web search
and question-answering. Nevertheless, it remains challenging for ordinary users to fully …