Add to ORKGThis paper describes the participation of the UNIBA team in the Named Entity rEcognition and Linking (NEEL) Challenge. We propose a completely unsupervised algorithm able to recognize and link named entities in English tweets. The approach combines the simple Lesk algorithm with information coming from both a distributional semantic model and usage frequency of Wikipedia concepts. The results show encouraging performance
Twitter is a rich source of continuously and instantly updated information. Shortness and informalit...
Twitter is a rich source of continuously and instantly updated information. Shortness and informalit...
International audienceIn many information extraction applications, entity linking (EL) has emerged a...
This paper describes the participation of the UNIBA team in the Named Entity rEcognition and Linking...
The large number of tweets generated daily is providing decision makers with means to obtain insight...
The large number of tweets generated daily is providing policy makers with means to obtain insights ...
Applying natural language processing for mining and intelligent information access to tweets (a form...
Named Entity Linking (NEL) is the task of semantically annotating entity mentions in a portion of te...
Named Entity Linking (NEL) is the task of semantically annotating entity mentions in a portion of te...
Twitter is a potentially rich source of continuously and instantly updated information. Shortness an...
This work proposes a novel approach in Named Entity rEcognition and Linking (NEEL) in tweets, applyi...
This paper describes a simple way to improve performance of Named Entity Recognition systems across ...
Social media is a rich source of information. To make use of this information, it is sometimes requi...
Abstract: Social media is a rich source of information. To make use of this information, it is somet...
Twitter is a rich source of continuously and instantly updated information. Shortness and informalit...
Twitter is a rich source of continuously and instantly updated information. Shortness and informalit...
Twitter is a rich source of continuously and instantly updated information. Shortness and informalit...
International audienceIn many information extraction applications, entity linking (EL) has emerged a...
This paper describes the participation of the UNIBA team in the Named Entity rEcognition and Linking...
The large number of tweets generated daily is providing decision makers with means to obtain insight...
The large number of tweets generated daily is providing policy makers with means to obtain insights ...
Applying natural language processing for mining and intelligent information access to tweets (a form...
Named Entity Linking (NEL) is the task of semantically annotating entity mentions in a portion of te...
Named Entity Linking (NEL) is the task of semantically annotating entity mentions in a portion of te...
Twitter is a potentially rich source of continuously and instantly updated information. Shortness an...
This work proposes a novel approach in Named Entity rEcognition and Linking (NEEL) in tweets, applyi...
This paper describes a simple way to improve performance of Named Entity Recognition systems across ...
Social media is a rich source of information. To make use of this information, it is sometimes requi...
Abstract: Social media is a rich source of information. To make use of this information, it is somet...
Twitter is a rich source of continuously and instantly updated information. Shortness and informalit...
Twitter is a rich source of continuously and instantly updated information. Shortness and informalit...
Twitter is a rich source of continuously and instantly updated information. Shortness and informalit...
International audienceIn many information extraction applications, entity linking (EL) has emerged a...