Information Engineering Express

Characteristics of Datasets for Fake News Detection to Mitigate Domain Bias

2024-02-06T16:13:37+00:00

“Fake news”, news intentionally containing false information, has become quite common and often causes social disruption. Many researches on automatic detection of fake have been extensively studied. The classification accuracy is improving, but a major challenge for practical application still remains: models can not work well for news in unknown fields, called “domains”, due to bias caused by different words and phrases among domains. To improve the accuracy of cross-domain fake news detection, it is crucial to mitigate the domain bias since unknown news articles to be classified can be in unknown domains. As a preliminary experiment, we trained a classifier using news articles whose noun phrases were masked because they are considered as a major source of the bias. However, contrary to expectations, masking did not improve accuracy. From the preliminary experiment, we obtained the hypothesis that pairs of fake and real news on the same topic can mitigate the domain bias. Using comparative experiments, we show that accuracy is higher when trained on paired news articles than when trained on unpaired ones.This result strongly suggests that a fake news dataset consisting of paired news could be effective for cross-domain detection.

A Method to Reduce the Burden of the Recreation Moderator by Using a Humanoid Communication Robot

2024-03-25T09:50:20+00:00

The authors proposed a method to reduce the burden on the recreation moderator by using a humanoid communication robot. This system projects quizzes on the screen, and humanoid communication robots read the explanations to proceed with the recreation. This paper presents the details of the proposed system, the method of implementing recreation using the system, the effect of recreation on participants, and the effect of reducing the burden on nursing care staff. An experiment was conducted comparing cases in which nursing care staff acted as moderators and robots acted as moderators. As a result, it became clear that the burden on nursing care staff could be reduced while recreation remained active.

Improving the Consistency of Dialog Models Through Speaker Separation Learning

2024-04-03T12:09:51+00:00

In recent years, dialog systems, a type of application in the field of natural language processing, have become more prevalent in our daily lives, such as through help desk services. In dialog response generation, responses generated for a specific context may differ from those for other contexts not only grammatically but also semantically in some cases. Thus, simply applying translation technologies would cause issues with the diversity of the generated responses. Previous studies, such as VHRED and GVT, used sampled latent variables for response generation to achieve response diversity. In this study, we propose a method (extended GVTSC) for classifying dialogs before reflecting them in internal dialog processing, in addition to the characteristics of each speaker, to improve diversity while maintaining consistency.

Some Antecedents of Employee Engagement of Japanese Companies

2024-02-15T06:34:55+00:00

Corporate human resource managers and institutional investors place a high value on employee engagement (EE) in Japanese companies and demand proactive disclosure of this information as human capital information (HCI). Currently, this demand for disclosure has been growing stronger in Europe and the United States. Therefore, Western HR consulting firms are providing services to Japanese companies with suggestions for improving EE. It is unclear whether this service is suitable because of the differences in employment systems between Western countries and Japan. However, EE should be appropriately enhanced in Japanese companies. This paper uses an employee survey of Japanese companies to identify EE antecedents. A multiple-indicator model was created by analyzing the covariance structure of the survey results. Four factors were extracted from this analysis. Two antecedents, “Empowerment” and “Loyalty,” were identified as constituting “Engagement.” This result is generally consistent with the “job engagement” results of Saks’ study. This consistency indicates that our research results are adequate. In the future, we will also investigate organizational engagement, which is missing in our findings, and identify more EE antecedents.

Interactive Evolutionary Computation Creating Congruent Media Content Composed of Different Media Types

2024-03-25T11:26:18+00:00

We use multiple media content every day, and using congruent media content composed of different media types is ideal for users. However, it is still difficult to obtain congruent media content. Interactive Evolutionary Computation (IEC) is a well-known method for obtaining good media content suited to each user’s feelings as solutions to search problems. Conventional IECs were used for searching sole media type. This study proposes a new IEC that searches the congruent media content as a good combination of different types of media content. In the proposed IEC, the solution candidate contains variables corresponding to different media types. A system was constructed with a genetic algorithm, and it was used to investigate the efficiencies of the pro-posed IEC in the experiment. The target of creation was a relaxing set of music melody and scent. Twenty participants evaluated sets of music melodies and scents throughout ten generations in the search experiment. The experimental results showed a significant increase in the mean fitness and a significant decrease in the distance between solutions. No significant increase was observed in the maximum fitness values.