Zobrazeno 1 - 10
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pro vyhledávání: '"Bagheri, Ayoub"'
Popular word embedding methods such as GloVe and Word2Vec are related to the factorization of the pointwise mutual information (PMI) matrix. In this paper, we link correspondence analysis (CA) to the factorization of the PMI matrix. CA is a dimension
Externí odkaz:
http://arxiv.org/abs/2405.20895
Understanding the spread of SARS-CoV-2 has been one of the most pressing problems of the recent past. Network models present a potent approach to studying such spreading phenomena because of their ability to represent complex social interactions. Whi
Externí odkaz:
http://arxiv.org/abs/2310.14767
Autor:
Fang, Qixiang, Giachanou, Anastasia, Bagheri, Ayoub, Boeschoten, Laura, van Kesteren, Erik-Jan, Kamalabad, Mahdi Shafiee, Oberski, Daniel L
Text-based personality computing (TPC) has gained many research interests in NLP. In this paper, we describe 15 challenges that we consider deserving the attention of the research community. These challenges are organized by the following topics: per
Externí odkaz:
http://arxiv.org/abs/2212.06711
Stance detection (SD) concerns automatically determining the viewpoint (i.e., in favour of, against, or neutral) of a text's author towards a target. SD has been applied to many research topics, among which the detection of stances behind political t
Externí odkaz:
http://arxiv.org/abs/2212.06543
Compositional data are non-negative data collected in a rectangular matrix with a constant row sum. Due to the non-negativity the focus is on conditional proportions that add up to 1 for each row. A row of conditional proportions is called an observe
Externí odkaz:
http://arxiv.org/abs/2109.04875
Autor:
Bagheri, Ayoub, Groenhof, T. Katrien J., Veldhuis, Wouter B., de Jong, Pim A., Asselbergs, Folkert W., Oberski, Daniel L.
Electronic health records (EHRs) contain structured and unstructured data of significant clinical and research value. Various machine learning approaches have been developed to employ information in EHRs for risk prediction. The majority of these att
Externí odkaz:
http://arxiv.org/abs/2008.11979
Fair inference in supervised learning is an important and active area of research, yielding a range of useful methods to assess and account for fairness criteria when predicting ground truth targets. As shown in recent work, however, when target labe
Externí odkaz:
http://arxiv.org/abs/2003.07621
Publikováno v:
Applied Sciences (2076-3417); Oct2024, Vol. 14 Issue 19, p8620, 27p
Autor:
Bagheri, Ayoub, Saraee, Mohamad
Publikováno v:
International Journal of Artificial Intelligence 12.2 (2014): 115-129
In the recent decade, with the enormous growth of digital content in internet and databases, sentiment analysis has received more and more attention between information retrieval and natural language processing researchers. Sentiment analysis aims to
Externí odkaz:
http://arxiv.org/abs/1412.8079
Publikováno v:
Applied Network Science; 7/2/2024, Vol. 9 Issue 1, p1-27, 27p