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Adrian CHIFU

Publication type: Conference Papers

In this paper, we introduce FreSaDa, a French Satire Data Set, which is composed of 11,570 articles from the news domain. In order to avoid reporting unreasonably high accuracy rates due to the learning of characteristics specific to publication sources, we divided our samples into training, validation and test, such that the training publication sources […]

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Publication type: Conference Papers

While (mainly) designed to answer users’ needs, search engines and recommendation systems do not necessarily guarantee the exposure of the data they store and index while it can be essential for information providers. A recent research direction so called “fair” exposure of documents tackles this problem in information retrieval. It has mainly been cast into […]

Comments Off on Fair Exposure of Documents in Information Retrieval: a Community Detection Approach

Publication type: Conference Papers

Natural Language Processing (NLP) of textual data is usually broken down into a sequence of several subtasks, where the output of one the subtasks becomes the input to the following one, which constitutes an NLP pipeline. Many third-party NLP tools are currently available, each performing distinct NLP subtasks. However, it is difficult to integrate several […]

Comments Off on DeepNLPF: A Framework for Integrating Third Party NLP Tools

Publication type: Conference Papers

This article presents the model that generated the runs submitted by the R2I LIS team to the VarDial2019 evaluation campaign, more particularly, to the binary classification by dialect sub-task of the Moldavian vs. Romanian Cross-dialect Topic identification (MRC) task. The team proposed a majority vote-based model, between five supervised machine learning models, trained on forty […]

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