Silva, Renato MFed Univ Sao Carlos UFSCarAlmeida, Tiago AFed Univ Sao Carlos UFSCarNeurocomputingCardoso, E.F.; Silva, R.M.; Almeida, T.A. Towards automatic filtering of fake reviews. Neurocomputing 2018, 309, 106-116. [CrossRef]...
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Regardless of the terminology employed to delineate this phenomenon of “hallucination” in artificial intelligence, its existence undeniably yields detrimental repercussions for people. On the one hand, from the users’ perspective, this phenomenon has incited concerns over the veracity of information. O...
One participant had indicated employment in the Prolific sample filtering fields, but reported being unemployed at the time of the survey, the rest were (self)-employed. 2.2.3. Age, education, computer expertise The retained sample had a mean age of 36.15 years (SD = 10.25, range ...
Based on Mind2Web, we conduct an initial exploration of using large language models (LLMs) for building generalist web agents. While the raw HTML of real-world websites are often too large to be fed to LLMs, we show that first filtering it with a small LM significantly improves the ...
This inspired the development of a simple classifier to automatically detect fake reviews in app stores. On a labelled and imbalanced dataset including one-tenth of fake reviews, as reported in other domains, our classifier achieved a recall of 91% and an AUC/ROC value of 98%. We discuss ...
Clare Fin
For automatic text redaction, we explored two approaches: Canny Edge Detection [12], which aims to bound text with boxes, and Gabor-wavelet filtering [13], which aims to classify individual pixels as “text” or “non-text.” For Gabor, we looked at both unsupervised classification and super...
of fake news. As a result, it is preferable to have a system that allows consumers to obtain balanced news information. Some researchers attempted to detect false and authentic news using tagged data and had some success. Online social groups propagate digital false news or fake news material ...
Section 6 concludes the paper and points out some of our future research. 2. Related Work The traditional static defense of network security is divided into three types: reinforcement protection of the system, intrusion detection, and network deception [15]. Firewall (including packet filtering, ...