• Title/Summary/Keyword: Review Features

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Development of a Deep Learning Model for Detecting Fake Reviews Using Author Linguistic Features (작성자 언어적 특성 기반 가짜 리뷰 탐지 딥러닝 모델 개발)

  • Shin, Dong Hoon;Shin, Woo Sik;Kim, Hee Woong
    • The Journal of Information Systems
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    • v.31 no.4
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    • pp.01-23
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    • 2022
  • Purpose This study aims to propose a deep learning-based fake review detection model by combining authors' linguistic features and semantic information of reviews. Design/methodology/approach This study used 358,071 review data of Yelp to develop fake review detection model. We employed linguistic inquiry and word count (LIWC) to extract 24 linguistic features of authors. Then we used deep learning architectures such as multilayer perceptron(MLP), long short-term memory(LSTM) and transformer to learn linguistic features and semantic features for fake review detection. Findings The results of our study show that detection models using both linguistic and semantic features outperformed other models using single type of features. In addition, this study confirmed that differences in linguistic features between fake reviewer and authentic reviewer are significant. That is, we found that linguistic features complement semantic information of reviews and further enhance predictive power of fake detection model.

FEROM: Feature Extraction and Refinement for Opinion Mining

  • Jeong, Ha-Na;Shin, Dong-Wook;Choi, Joong-Min
    • ETRI Journal
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    • v.33 no.5
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    • pp.720-730
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    • 2011
  • Opinion mining involves the analysis of customer opinions using product reviews and provides meaningful information including the polarity of the opinions. In opinion mining, feature extraction is important since the customers do not normally express their product opinions holistically but separately according to its individual features. However, previous research on feature-based opinion mining has not had good results due to drawbacks, such as selecting a feature considering only syntactical grammar information or treating features with similar meanings as different. To solve these problems, this paper proposes an enhanced feature extraction and refinement method called FEROM that effectively extracts correct features from review data by exploiting both grammatical properties and semantic characteristics of feature words and refines the features by recognizing and merging similar ones. A series of experiments performed on actual online review data demonstrated that FEROM is highly effective at extracting and refining features for analyzing customer review data and eventually contributes to accurate and functional opinion mining.

Feature Analysis for Detecting Mobile Application Review Generated by AI-Based Language Model

  • Lee, Seung-Cheol;Jang, Yonghun;Park, Chang-Hyeon;Seo, Yeong-Seok
    • Journal of Information Processing Systems
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    • v.18 no.5
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    • pp.650-664
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    • 2022
  • Mobile applications can be easily downloaded and installed via markets. However, malware and malicious applications containing unwanted advertisements exist in these application markets. Therefore, smartphone users install applications with reference to the application review to avoid such malicious applications. An application review typically comprises contents for evaluation; however, a false review with a specific purpose can be included. Such false reviews are known as fake reviews, and they can be generated using artificial intelligence (AI)-based text-generating models. Recently, AI-based text-generating models have been developed rapidly and demonstrate high-quality generated texts. Herein, we analyze the features of fake reviews generated from Generative Pre-Training-2 (GPT-2), an AI-based text-generating model and create a model to detect those fake reviews. First, we collect a real human-written application review from Kaggle. Subsequently, we identify features of the fake review using natural language processing and statistical analysis. Next, we generate fake review detection models using five types of machine-learning models trained using identified features. In terms of the performances of the fake review detection models, we achieved average F1-scores of 0.738, 0.723, and 0.730 for the fake review, real review, and overall classifications, respectively.

Oral carcinoma cuniculatum, an unacquainted variant of oral squamous cell carcinoma: A systematic review

  • Farag, Amina Fouad;Abou-Alnour, Dalia Ali;Abu-Taleb, Noha Saleh
    • Imaging Science in Dentistry
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    • v.48 no.4
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    • pp.233-244
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    • 2018
  • Purpose: Oral carcinoma cuniculatum is a rare well-differentiated variant of oral squamous cell carcinoma. The purpose was to systematically review its unique features to differentiate it from other variants as verrucous carcinoma, papillary squamous cell carcinoma and well-differentiated squamous cell carcinoma. Materials and Methods: A systematic review was performed using MEDLINE, Dentistry and Oral Sciences Source and PubMed databases and any existing articles related to the research subject missed in the search strategy to screen ones reporting cases occurring exclusively in the oral cavity in English literature. Variables analyzed included clinical, etiologic, imaging, histopatholgical features, treatment, follow-up and survival rates. Results: From 229 hits, 17 articles with 43 cases were included in the systematic review. Clinically it showed a female predilection with pain and/or ulceration of a relatively long duration and exudation being the most common symptoms. Histologically, it showed more endophytic features comprising well-differentiated squamous epithelium with absent or minimal cytological atypia and multiple keratin filled crypts or cuniculus. Inflammatory stromal reaction and discharging abscesses were reported in most of the cases. Bone destruction was predominant in most imaging features. Complete surgical resection with a safety margin was the treatment of choice in most of the cases with few recorded recurrence cases. Conclusion: Apprehensive knowledge of oral carcinoma cuniculatum unique features is essential to avoid its misdiagnosis and provide proper treatment especially for recurrent cases.

The Surrealistic Features of Viktor & Rolf's Design (빅터 & 롤프 의상에 나타난 초현실주의 특성)

  • Lee, Young-Min;Lee, Youn-Hee;Park, Jae-Ok
    • The Research Journal of the Costume Culture
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    • v.15 no.2 s.67
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    • pp.352-367
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    • 2007
  • Viktor and Rolf, despite their short career in the field, has been continuously giving a fresh impact on fashion design by grafting a surrealistic approach to their design works. As a basis of this study, we review the features of surrealistic drawing and the surrealistic features expressed in surrealistic clothes. The purpose of this study is to analyze the surrealistic features detected in the clothes designed by Viktor and Rolf on the basis of the above standard and review and predict the future trend in fashion. As for the research method, we review the previous researches and analyze the drawing works by some representative surrealistic artists, in particular, Schiaparelli's clothes in the 1930s, the clothes of surrealistic trend since 2000, and Viktor & Rolf's clothes. The result of the analysis is as follows. The surrealistic features of Viktor & Rolf clothes can be found in the movement of natural objects, the movement of everyday materials, the movement of clothing items, and visual illusion on clothes. As a whole, the surrealistic features clearly stood out in their clothes. High technology will rapidly change the modern society and we humans are likely to resort to something fresh or different as our emotion and feelings are getting tired and weary. Something that stimulates our feeling and emotion hidden behind our reason or logic will be reflected in design far more than something complex and functional. For this reason, as it reveals human imagination inherently, surrealism is expected to establish itself as a mega trend in the future.

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Several issues regarding the diagnostic imaging of medication-related osteonecrosis of the jaw

  • Kim, Jo-Eun;Yoo, Sumin;Choi, Soon-Chul
    • Imaging Science in Dentistry
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    • v.50 no.4
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    • pp.273-279
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    • 2020
  • This review presents an overview of some diagnostic imaging-related issues regarding medication-related osteonecrosis of the jaws(MRONJ), including imaging signs that can predict MRONJ in patients taking antiresorptive drugs, the early imaging features of MRONJ, the relationship between the presence or absence of bone exposure and imaging features, and differences in imaging features by stage, between advanced MRONJ and conventional osteomyelitis, between oncologic and osteoporotic patients with MRONJ, and depending on the type of medication, method of administration, and duration of medication. The early diagnosis of MRONJ can be made by the presence of subtle imaging changes such as thickening of the lamina dura or cortical bone, not by the presence of bone exposure. Most of the imaging features are relatively non-specific, and each patient's clinical findings and history should be referenced. Oral and maxillofacial radiologists and dentists should closely monitor plain radiographs of patients taking antiresorptive/antiangiogenic drugs.

A Review of the Opinion Target Extraction using Sequence Labeling Algorithms based on Features Combinations

  • Aziz, Noor Azeera Abdul;MohdAizainiMaarof, MohdAizainiMaarof;Zainal, Anazida;HazimAlkawaz, Mohammed
    • Journal of Internet Computing and Services
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    • v.17 no.5
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    • pp.111-119
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    • 2016
  • In recent years, the opinion analysis is one of the key research fronts of any domain. Opinion target extraction is an essential process of opinion analysis. Target is usually referred to noun or noun phrase in an entity which is deliberated by the opinion holder. Extraction of opinion target facilitates the opinion analysis more precisely and in addition helps to identify the opinion polarity i.e. users can perceive opinion in detail of a target including all its features. One of the most commonly employed algorithms is a sequence labeling algorithm also called Conditional Random Fields. In present article, recent opinion target extraction approaches are reviewed based on sequence labeling algorithm and it features combinations by analyzing and comparing these approaches. The good selection of features combinations will in some way give a good or better accuracy result. Features combinations are an essential process that can be used to identify and remove unneeded, irrelevant and redundant attributes from data that do not contribute to the accuracy of a predictive model or may in fact decrease the accuracy of the model. Hence, in general this review eventually leads to the contribution for the opinion analysis approach and assist researcher for the opinion target extraction in particular.

Factors and Implications for Creative Scientists: A Systems View of Creativity

  • Kim, Wangdong
    • STI Policy Review
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    • v.1 no.2
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    • pp.33-50
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    • 2010
  • This study examines three factors - personal, academic features and governmental research environment - that influences the research of creative scientists based on a Systems Model of Creativity and tries to deprive policy implications. First, this study investigates the characteristics of creative scientists' research through a literature review. Next, it analyzes the features of academic characteristics, and creative research environments by the interviews of nine creative scientists in Korea. Lastly, it draws its implications and analyzes the limitations of this research.

Evolution and Features of Korea's Science & Technology Policy Coordination System

  • Seong, Jieun
    • STI Policy Review
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    • v.2 no.1
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    • pp.1-12
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    • 2011
  • Korea is examining how to coordinate its S&T policies and solidify its position as a leader of infrastructure innovation policy that forms the foundation for many different policies. A number of questions have been raised, such as whether to install a superior coordinating body like the National Science and Technology Council (NSTC) or separate the budget allocation and coordination authority from the budget-planning ministry. Korea has tried using various institutional coordination devices and functions such as reorganizing its administrative ministries based on related functions and installing or reinforcing a superior coordinating body. In line with these discussions, the strengthening of the S&T policy coordination function through the NSTC is currently under review. In order to design an effective S&T coordination system in step with changing political and social demands, it is important to have a clear recognition of the current context as well as the unique institutional characteristics of Korea. This study examines the evolution of Korea's S&T policy coordination systems and analyzes its features.

Radiomics in Breast Imaging from Techniques to Clinical Applications: A Review

  • Seung-Hak Lee;Hyunjin Park;Eun Sook Ko
    • Korean Journal of Radiology
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    • v.21 no.7
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    • pp.779-792
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    • 2020
  • Recent advances in computer technology have generated a new area of research known as radiomics. Radiomics is defined as the high throughput extraction and analysis of quantitative features from imaging data. Radiomic features provide information on the gray-scale patterns, inter-pixel relationships, as well as shape and spectral properties of radiological images. Moreover, these features can be used to develop computational models that may serve as a tool for personalized diagnosis and treatment guidance. Although radiomics is becoming popular and widely used in oncology, many problems such as overfitting and reproducibility issues remain unresolved. In this review, we will outline the steps of radiomics used for oncology, specifically addressing applications for breast cancer patients and focusing on technical issues.