• Asia pacific journal of information systems
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• v.31 no.4
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• pp.472-490
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• 2021

The detection of products with manipulated reviews has received widespread research attention, given that a truthful, informative, and useful review helps to significantly lower the search effort and cost for potential customers. This study proposes a method to recognize products with manipulated online customer reviews by examining the sequence of each review's sentiment, readability, and rating scores by product on randomness, considering the example of a Russian online retail site. Additionally, this study aims to examine the association between brand awareness and existing manipulation with products' reviews. Therefore, we investigated the difference between well-known and unknown brands' products online reviews with and without manipulated reviews based on the average star rating and the extremely positive sentiment scores. Consequently, machine learning techniques for predicting products are tested with manipulated reviews to determine a more useful one. It was found that about 20% of all product reviews are manipulated. Among the products with manipulated reviews, 44% are products of well-known brands, and 56% from unknown brands, with the highest prediction performance on deep neural network.

• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.81-98
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• 2009

Collaborative filtering, one of the most successful technologies among recommender systems, is a system assisting users in easily finding the useful information and supporting the decision making. However, despite of its success and popularity, one notable issue is incredibility of recommendations by unreliable users called shilling attacks. To deal with this problem, in this paper, we analyze the type of shilling attacks and propose a unique method of building a model for protecting the recommender system against manipulated ratings. In addition, we present a method of applying the model to collaborative filtering which is highly robust and stable to shilling attacks.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.437-443
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• 2013

Recently, sustainable building design, a growing field within architectural design, has been emerged in the construction industry as the practice of designing, constructing, and operating facilities in such a manner that their environmental impact, which has become a great concern of construction professionals, can be minimized. A number of different green rating systems have been developed to help assess that a building project is designed and built using strategies intended to minimize or eliminate its impact on the environment. In the United States, the widely accepted national standards for sustainable building design are known as the LEED (Leadership in Energy and Environmental Design) Green Building Rating System. The assessment of sustainability using the LEED green rating system is a challenging and time-consuming work due to its complicated process. In effect, the LEED green rating system awards points for satisfying specified green building criteria into five major categories: sustainable sites, water efficiency, energy and atmosphere, materials and resources, and indoor environmental quality; and sustainability of a project is rated by accumulating scores (100 points maximum) from these five major categories. The sustainability rating process could be accelerated and facilitated by using computer technology such as BIM (Building Information Modeling), an innovative new approach to building design, engineering, and construction management that has been widely used in the construction industry. BIM is defined as a model-based technology linked with a database of project information, which can be accessed, manipulated, and retrieved for construction estimating, scheduling, project management, as well as sustainability rating. This paper will present a framework representing the building knowledge contained in the LEED green building criteria. The proposed building knowledge framework will be implemented into a BIM platform (e.g. Autodesk Revit Architecture) in which sustainability rating of a building design can be automatically performed. The development of the automated sustainability rating system and the results of its implementation will be discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2171-2195
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• 2017

When purchasing an online product, a customer tends to be influenced strongly by its reputation, the aggregation of other customers' ratings on it. The reputation, however, is not always trustable since it can be manipulated easily by attackers who intentionally give unfair ratings to their target products. In this paper, we first address identifying trustable users who tend to give fair ratings to products in online rating systems and then propose a method of computing true reputation of a product by aggregating only those trustable users' ratings. In order to identify the trustable users, we list some candidate features that seem related significantly to the trustworthiness of users and verify the robustness of each of the features through extensive experiments. By finding and exploiting these robust features, we are able to identify trustable users and to compute true reputation effectively and efficiently based on fair ratings of those trustable users.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.703-708
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• 2009

The present paper describes the application of an improved impression transfer vector method (Sakurai et al., 2007) to transform the three basic dimensions (Evaluation, Activity, and Potency) of higher-order impression. First, a set of shapes and surface textures of faces was represented by multi-dimensional vectors. Second, the variation among faces was coded in reduced parameters derived by applying principal component analysis. Third, a facial attribute along a given impression dimension was analyzed to select discriminative parameters from among principal components with higher sensitivity to impressions, and obtain an impression transfer vector. Finally, the parametric coordinates were changed by adding or subtracting the impression transfer vector and the image was manipulated so that its facial appearance clearly exhibits the transformed impression. A psychological rating experiment confirmed that the impression transfer vector modulated three dimensions of higher-order impression. We discussed the versatility of the impression transfer vector method.

• Science of Emotion and Sensibility
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• v.10 no.4
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• pp.523-538
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• 2007

This study examined effects of gender and empathic emotional expression of an anthropomorphic interface agent on users. assessment of the agent. In addition, it examined effects of gender and emotional expression regardless of whether visual fidelity of the agent. In Study 1, The agents were manipulated by photographs of human face. The agent expressed empathic emotion by making an other-oriented emotional response congruent with another's perceived welfare. Subjects participated in a task with the agent and then they assessed the agent by rating interpersonal assessment scale. The result reported their preference to the female agent. In addition, they tended to make positive assessment to the agent of opposite gender. In the study 2, gender and expressed emotion of the agent with low fidelity was manipulated. Subjects participated in a task with the agent and then they assessed the agent by rating the same interpersonal assessment scale as study 1. The result reported their preference to the female agent. In addition, they preferred the agent expressing empathic emotion to the agent expressing self-oriented emotion or no emotion. Though the agent had low visual fidelity, its gender and expressed empathic emotion could make a significant effect on users' assessment.

• Korean Journal of Human Ecology
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• v.19 no.2
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• pp.399-407
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• 2010

The purpose of this study was to investigate the visual images of shirts according to coloration and the interval of checked patterns. The experimental stimulus and questionnaires for scaling response were developed for this study. The stimuli were 12 color pictures, in which the gender, coloration(WG: white+gray, WK: white+black, GK: gray+black), and interval(0.5 cm, 1.5 cm, 3.5 cm, 5.5 cm) were manipulated. The 7-point rating scale was used for evaluation of the visual image. Data were obtained from 144 male college students and 144 female college students living in Gyeonggi, Gyeongnam, Seoul, Gwangju, Daegu, and Busan on December 2009. For data analysis, ANOVA and the Duncan-test were used by using the SPSS program. The results of this study were as follows; the visual images for shirts according to the coloration and interval of checked patterns consisted of four dimensions of attractiveness, appeal, youth, and modesty. Gender was the main factor when looking at attractiveness. Coloration had the main effect on appeal, youth, and modesty. Also, there was a significant interaction effect of gender and coloration on attractiveness, while there was a significant interaction effect of coloration and interval on modesty.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.201-208
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• 2014

The objective of the present study is to investigate the relationships among the perceptions of performance appraisal politics(POPAP)), employee's attitude to work, and team-based work system characteristics. Using survey data from various occupationally heterogeneous sample of white-collar employees(N=195) from various organizations, the results indicate that when employees perceive performance rating to be manipulated because of rater's personal bias and punishment motive, they reduce organizational commitment. Contrarily, the employees' POPAP with motivational motive increases organizational commitment. And task interdependency has positive effect on employees' POPAP.