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Titlebook: Intelligent Systems and Applications; Proceedings of the 2 Kohei Arai Conference proceedings 2022 The Editor(s) (if applicable) and The Aut

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Automatic Monitoring and Analysis of Brands Using Data Extracted from Twitter in Romanian,lysis text classifier for distinguishing Twitter posts between positive or negative, which was trained and tested using a novel dataset of tweets in Romanian, labelled by the authors. We created and compared four adapted preprocessing pipelines, that generated four sets of data, on which we trained
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Discovering Influence of Yelp Reviews Using Hawkes Point Processes,r question is how much influence these have on other users’ behavior. In this paper, we focused on Yelp, an online platform for customers to share information of their visiting experiences on restaurants, to explore the possible relationships between past reviews and future reviews of a restaurant t
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AIRM: A New AI Recruiting Model for the Saudi Arabia Labor Market, unemployment has a negative effect on any countries gross domestic product. Artificial Intelligence is the fastest developing technology these days. It has served in many specialties. Recently, Artificial Intelligence technology has shined in the field of recruiting. Researchers are working to inve
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Global Postal Automation,he U.S. and focus on the major innovations that have been implemented to increase productivity and decrease labor costs. From the beginning of the New Field Theory approach to image processing technologies, we focus on the role of Optical Character Recognition (OCR). Similarly, we also discuss how o
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Automated Corpus Annotation for Cybersecurity Named Entity Recognition with Small Keyword Dictionard text data is scarce and expensive, Named Entity Recognition (NER) is used to detect the relevant domain entities from the raw text. To train a new NER model for cybersecurity, traditional NER requires a training corpus annotated with cybersecurity entities. Our previous work proposed a Human-Machi
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