Natural language is inherently fuzzy. Medium Logic (ML) reveals that the essence of language fuzziness is the intermediary state of its semantics, and the measuring of Medium Truth Degree (MMTD) is the tool quantifyin...
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This study aims to improve corporate brand public opinion management through user emotional reasoning, focusing on understanding users' psychological states and applying emotion analysis methods. Existing research...
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ISBN:
(数字)9798331519254
ISBN:
(纸本)9798331519261
This study aims to improve corporate brand public opinion management through user emotional reasoning, focusing on understanding users' psychological states and applying emotion analysis methods. Existing research typically uses end-to-end generative models, fine-tuning small pre-trained language models for emotion analysis. However, these methods lack fine-grained emotional state understanding, resulting in lower sentiment analysis accuracy and limited model interpretability. To address this, the study introduces a novel framework, Co De (Chaln-of-User-Emotlonal), based on large language models. CoDebreaks down emotion analysis into a phased reasoning process with three chains: emotion reasoning, public opinion trend, and response generation. By using background enhancement strategies, the method improves emotional state analysis and sentiment prediction, enabling real-time market sentiment monitoring and reducing brand public opinion crises.
Cancer victims, particularly those with lung cancer, are more susceptible and at higher danger of COVID-19 and associated consequences as a result of their compromised immune systems, which makes them particularly sen...
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Cancer victims, particularly those with lung cancer, are more susceptible and at higher danger of COVID-19 and associated consequences as a result of their compromised immune systems, which makes them particularly sensitive. Because of a variety of circumstances, cancer patients' diagnosis, treatment, and aftercare are very complicated and time-consuming during an epidemic. In such circumstances, advances in artificial intelligence (AI) and machine learning algorithms (ML) offer the capacity to boost cancer sufferer diagnosis, therapy, and care via the use of cutting technologies. For example, using clinical and imaging data combined with machine learning methods, the researchers may be able to distinguish among lung alterations induced by corona virus and those produced by immunotherapy and radiation. During this epidemic, artificial intelligence (AI) may be utilized to guarantee that the appropriate individuals are recruited in cancer clinical trials more quickly and effectively than in the past, which was done in a conventional and complicated manner. In order to better care for cancer patients and find novel and more effective therapies, It is critical that we move beyond traditional research methods and use artificial intelligence (AI) and machine learning to update our research (ML). Artificial intelligence (AI) and machine learning (ML) are being utilised to help with several aspects of the COVID-19 epidemic, such as epidemiology, molecular research and medication development, medical diagnosis and treatment, and socioeconomics. The use of artificial intelligence (AI) and machine learning (ML) in the diagnosis and treatment of COVID-19 patients is also being investigated. The combination of artificial intelligence and machine learning in COVID-19 may help to identify positive patients more quickly. In order to understand the dynamics of an epidemic that is relevant to artificial intelligence, when used in different patient groups, AI-based algorithms can quic
For decades music has been used successfully in sports and especially physical rehabilitation in order to motivate people and increase satisfaction in the actual workout. The novel principle of "Music Feedback Ex...
For decades music has been used successfully in sports and especially physical rehabilitation in order to motivate people and increase satisfaction in the actual workout. The novel principle of "Music Feedback Exercise (MFE)" allows to individually influence the music according to the actual dynamics a person generates — more dynamics in the movement leads to more dynamics in the music and vice versa. Research by Max Planck Institute for Human Cognitive and Brain sciences gives evidence of the positive arousal effects on persons. In a cooperation with Anhalt University of Applied sciences a technical framework has been developed that is able to receive and analyze respective sensor data and to create musical output according to the generated intensity. This paper documents under which assumptions and how the MFE principle has been implemented into the Soundjack (also known as fast-music) core technology in order to take advantage of the versatile GUI options, low-latency audio streaming and also networking features.
In this work, we revisit linguistic acceptability in the context of large language models. We introduce CoLAC - Corpus of Linguistic Acceptability in Chinese, the first large-scale acceptability dataset for a nonIndo-...
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Whether and how language models (LMs) acquire the syntax of natural languages has been widely evaluated under the minimal pair paradigm. However, a lack of wide-coverage benchmarks in languages other than English has ...
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A smart home allows automated technology to control systems and appliances to assist daily life activities. In the current work, a prototype of a designed smart home health-aware system is presented. Three predefined ...
A smart home allows automated technology to control systems and appliances to assist daily life activities. In the current work, a prototype of a designed smart home health-aware system is presented. Three predefined ruled agents have been used to gather data, communicate between themselves, interpret the data based on several machine learning algorithms to predict abnormality for cardiac conditions. The paper also compares results obtained by running five machine learning algorithms. The agents function in accordance with predefined dataset describing residents ’ age, gender, height, weight, systolic and diastolic blood pressure, cholesterol, and glucose levels, smoking and alcohol consumption habits, and lastly, physical activity. Our plan is to simplify ubiquitous health monitoring for smart home’s residents. The proposed solution aims to monitor parametric measurements to alert health specialists in case of emergencies.
In this work, we present the largest benchmark to date on linguistic acceptability: Multilingual Evaluation of Linguistic Acceptability—MELA, with 46K samples covering 10 languages from a diverse set of language fami...
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Offensive language detection is essential for maintaining respectful and inclusive online environments. By implementing detection systems, platforms aim to protect users from harmful content, curb the spread of hate s...
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ISBN:
(数字)9798331508913
ISBN:
(纸本)9798331508920
Offensive language detection is essential for maintaining respectful and inclusive online environments. By implementing detection systems, platforms aim to protect users from harmful content, curb the spread of hate speech, and promote positive interactions within digital communities. Leveraging natural language processing (NLP) techniques, this area has become a key focus in computational linguistics research and development. To address this challenge, we created the ParsOffensive dataset, consisting of approximately 8,433 Persian comments labeled as Offensive or Neutral. These comments were sourced from Instagram and labeled by two linguists. Machine learning models were trained on this dataset, with the ParsBert model achieving 90% accuracy in detecting offensive speech in Persian.
The investment industry has recently continued to provide the greatest experience and has grown the number of investors to this day. It also increases the quantity of traded investment assets because of its varied cen...
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