International audienceIn this paper, we present the participation of the Computer Science Laboratory of Avignon (LIA) to RepLab 2013 edition. RepLab is an evaluation campaign for Online Reputation Management Systems. LIA has produced a important number of experiments for every tasks of the campaign: filtering, topic priority detection, Polarity for Reputation and topic detection. Our approaches rely on a large variety of machine learning methods. We have chosen to mainly exploit tweet contents. In several of our experiments we have also added selected metadata. A fewer number of our proposals have integrated external information by using provided links to Wikipedia and users homepage
The diue system uses a supervised Machine Learning approach for the polarity classification subtask ...
Abstract. Opinion and trend mining on micro blogs like twitter re-cently attracted research interest...
Abstract. We present a semi-automatic tool that assists experts in their daily work of monitoring th...
International audienceIn this paper, we present the participation of the Computer Science Laboratory...
ilps.science.uva.nl Abstract. This paper describes the organisation and results of RepLab 2014, the ...
This paper describes the organisation and results of RepLab 2014, the third competitive evaluation c...
Abstract. This paper describes our participation at the RepLab 2014 reputation dimensions scenario. ...
In this paper we present our experiments on the RepLab 2014 Reputation Dimension task. RepLab is a c...
Abstract. Filtering tweets relevant to a given entity is an important task for online reputation man...
Abstract. In this paper we present our experiments on the RepLab 2014 Repu-tation Dimension task. Re...
Abstract. In this paper we introduce our contribution to the RepLab 2013 – An evaluation campaign fo...
This paper describes our participation at the RepLab 2014 reputation dimensions scenario. Our idea w...
Abstract. This paper describes our participation in the Polarity for Reputation classification task ...
Abstract. This paper describes our participation in the RepLab 2014 Reputa-tion Dimensions task. The...
Abstract. Social media repositories serve as a significant source of ev-idence when extracting infor...
The diue system uses a supervised Machine Learning approach for the polarity classification subtask ...
Abstract. Opinion and trend mining on micro blogs like twitter re-cently attracted research interest...
Abstract. We present a semi-automatic tool that assists experts in their daily work of monitoring th...
International audienceIn this paper, we present the participation of the Computer Science Laboratory...
ilps.science.uva.nl Abstract. This paper describes the organisation and results of RepLab 2014, the ...
This paper describes the organisation and results of RepLab 2014, the third competitive evaluation c...
Abstract. This paper describes our participation at the RepLab 2014 reputation dimensions scenario. ...
In this paper we present our experiments on the RepLab 2014 Reputation Dimension task. RepLab is a c...
Abstract. Filtering tweets relevant to a given entity is an important task for online reputation man...
Abstract. In this paper we present our experiments on the RepLab 2014 Repu-tation Dimension task. Re...
Abstract. In this paper we introduce our contribution to the RepLab 2013 – An evaluation campaign fo...
This paper describes our participation at the RepLab 2014 reputation dimensions scenario. Our idea w...
Abstract. This paper describes our participation in the Polarity for Reputation classification task ...
Abstract. This paper describes our participation in the RepLab 2014 Reputa-tion Dimensions task. The...
Abstract. Social media repositories serve as a significant source of ev-idence when extracting infor...
The diue system uses a supervised Machine Learning approach for the polarity classification subtask ...
Abstract. Opinion and trend mining on micro blogs like twitter re-cently attracted research interest...
Abstract. We present a semi-automatic tool that assists experts in their daily work of monitoring th...