• Title/Summary/Keyword: service recommendation

Search Result 783, Processing Time 0.034 seconds

XML based on Clustering Method for personalized Product Category in E-Commerce

  • Lee, Kwon-Soo;Kim, Hoon-Hyun
    • Proceedings of the KAIS Fall Conference
    • /
    • 2003.11a
    • /
    • pp.118-126
    • /
    • 2003
  • In data mining, having access to large amount of data sets for the purpose of predictive data does not guarantee good method, even where the size of Real data is Mobile commerce unlimited. In addition to searching expected Goods objects for Users, it becomes necessary to develop a recommendation service based on XML. In this paper, we design the optimized XML Recommender product data. Efficient XML data preprocessing is required, include of formatting, structural, and attribute representation with dependent on User Profile Information. Our goal is to find a relationship among user interested products from E-Commerce and M-Commerce to XDB. Firstly, analyzing user profiles information. In the result creating clusters with analyzed user profile such as with set of sex, age, job. Secondly, it is clustering XML data which are associative products classify from user profile in shopping mall. Thirdly, after composing categories and goods data in which associative objects exist from the first clustering, it represent categories and goods in shopping mall and optimized clustering XML data which are personalized products. The proposed personalized user profile clustering method has been designed and simulated to demonstrate it's efficient.

  • PDF

Determinants of Audit Fees and the Role of the Board of Directors and Ownership Structure: Evidence from Jordan

  • SHAKHATREH, Mohammad Ziad;ALSMADI, Safaa Adnan
    • The Journal of Asian Finance, Economics and Business
    • /
    • v.8 no.5
    • /
    • pp.627-637
    • /
    • 2021
  • This research extends the literature on the effect of board characteristics and ownership structure on audit fees; these factors affect the firm's agency costs and how the auditor assesses various risks, hence the audit efforts and fees. The paper introduces political connections as a determinant of audit fees for the first time in Jordan, where the political connection is prevalent and affects decision making on the Jordanian boards. The sample consists of 109 manufacturing and service firms listed on the Amman Stock Exchange (ASE) over the years 2012-2019. Data is obtained from the ASE and the company's annual reports. Board characteristics are measured by board size, independence, leadership duality, meetings frequency, political connections, and audit committee. Ownership structure was measured by concentration, foreign ownership, and Institutional ownership. The study hypotheses were tested by using Generalized Least Squares regression. The Findings showed that larger boards, politically connected firms, and firms with leadership duality are more likely to pay higher fees. Besides, Firms with greater foreign ownership pay less fees, whereas the rest of the variables are insignificant. Results suggest that political connections play a major role in determining audit fees; this provides a recommendation to policymakers in Jordan to reconsider regulations regarding political connections.

A Course Recommendation System as Course Coordinator based on WIPI (코스 코디네이터의 역할을 하는 WIPI 기반 과목 추천 시스템)

  • Han, Yong-Jae;Lee, Young-Seok;Cho, Jung-Won;Choi, Byung-Uk
    • Proceedings of the Korea Information Processing Society Conference
    • /
    • 2004.05a
    • /
    • pp.973-976
    • /
    • 2004
  • IT 관련 기술의 발전은 'Any Time, Any Where, Any Service'를 사용자에게 제공할 수 있는 제반 여건을 마련하였다. 기존 웹 기반의 학사정보 시스템에서는 사용자의 이동성이 제한적이었고, 이를 해결하고자 한 무선 인터넷 기반의 학사정보 시스템은 클라이언트의 어플리케이션이 표준화된 환경에서 구축되지 않아서 모바일 기기의 플랫폼에 종속적이었다. 또한, 선택과목이 많은 학부제에서는 코스 코디네이터의 역할이 매우 중요하지만, 코스 코디네이터의 역할을 하는 지도교수와 학생 간의 커뮤니케이션의 부족으로 학생들은 도움을 받기 어렵다. 본 논문에서는 JAVA와 WIPI를 이용하여 플랫폼에 독립적이며 전공분야의 중요과목을 추천해 주는 과목 추천 시스템을 제안한다. 과목 추천 시스템은 학생들에게 수강과목에 대해 조언을 해 주는 코스 코디네이터의 역할을 대신할 수 있을 것이다. 또 학생들은 언제 어디서나 개인 휴대폰을 이용하여 수강신청에 관한 학사정보를 관리할 수 있고, 시스템의 추론에 따른 추천 과목을 수강하여 전공 분야에 대한 깊은 지식을 갖출 수 있을 것이다.

  • PDF

Cultural Region-based Clustering of SNS Big Data and Users Preferences Analysis (문화권 클러스터링 기반 SNS 빅데이터 및 사용자 선호도 분석)

  • Rho, Seungmin
    • Journal of Advanced Navigation Technology
    • /
    • v.22 no.6
    • /
    • pp.670-674
    • /
    • 2018
  • Social network service (SNS) related data including comments/text, images, videos, blogs, and user experiences contain a wealth of information which can be used to build recommendation systems for various clients' and provide insightful data/results to business analysts. Multimedia data, especially visual data like image and videos are the richest source of SNS data which can reflect particular region, and cultures values/interests, form a gigantic portion of the overall data. Mining such huge amounts of data for extracting actionable intelligence require efficient and smart data analysis methods. The purpose of this paper is to focus on this particular modality for devising ways to model, index, and retrieve data as and when desired.

User Physical Information Analysis based Fitness System (사용자 신체 정보 분석에 기반 피트니스 시스템)

  • Lee, Jong-Won;Kang, Hee-Beom;Park, Byung-Don;Kim, Ho-Sung;Jung, Hoe-Kyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2016.10a
    • /
    • pp.784-786
    • /
    • 2016
  • Recent research has been related to the health of the various systems. In contrast the system are the level insufficient for accurate analysis that the body of the user information and service information. In this paper, in order to solve this problem, we propose a fitness system based on the algorithm for analyzing the body of the user information. Algorithm to analyze the user's body information by analyzing the user's height and weight to calculate the BMI(Body Mass Index) index and BMR(Basal Metabolic Rate) value. The proposed system is considered to be able to give recommendations to the user for the exercise on the basis of the calculated BMI index and BMR value.

  • PDF

Online Shopping Research Trend Analysis Using BERTopic and LDA

  • Yoon-Hwang, JU;Woo-Ryeong, YANG;Hoe-Chang, YANG
    • The Journal of Economics, Marketing and Management
    • /
    • v.11 no.1
    • /
    • pp.21-30
    • /
    • 2023
  • Purpose: As one of the ongoing studies on the distribution industry, the purpose of this study is to identify the research trends on online shopping so far to propose not only the development of online shopping companies but also the possibility of coexistence between online and offline retailers and the development of the distribution industry. Research design, data and methodology: In this study, the English abstracts of 645 papers on online shopping registered in scienceON were obtained. For the analysis through BERTopic and LDA using Python 3.7 and identifying which topics were interesting to researchers. Results: As a result of word frequency analysis and co-occurrence analysis, it was found that studies related to online shopping were frequently conducted on factors such as products, services, and shopping malls. As a result of BERTopic, five topics such as 'service quality' and 'sales strategy' were derived, and as a result of LDA, three topics including 'purchase experience' were derived. It was confirmed that 'Customer Recommendation' and 'Fashion Mall' showed relatively high interest, and 'Sales Strategy' showed relatively low interest. Conclusions: It was suggested that more diverse studies related to the online shopping mall platform, sales content, and usage influencing factors are needed to develop the online shopping industry.

Gender Classification of Speakers Using SVM

  • Han, Sun-Hee;Cho, Kyu-Cheol
    • Journal of the Korea Society of Computer and Information
    • /
    • v.27 no.10
    • /
    • pp.59-66
    • /
    • 2022
  • This research conducted a study classifying gender of speakers by analyzing feature vectors extracted from the voice data. The study provides convenience in automatically recognizing gender of customers without manual classification process when they request any service via voice such as phone call. Furthermore, it is significant that this study can analyze frequently requested services for each gender after gender classification using a learning model and offer customized recommendation services according to the analysis. Based on the voice data of males and females excluding blank spaces, the study extracts feature vectors from each data using MFCC(Mel Frequency Cepstral Coefficient) and utilizes SVM(Support Vector Machine) models to conduct machine learning. As a result of gender classification of voice data using a learning model, the gender recognition rate was 94%.

Comparison of big data image analysis techniques for user curation (사용자 큐레이션을 위한 빅데이터 영상 분석 기법 비교)

  • Lee, Hyoun-Sup;Kim, Jin-Deog
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2021.05a
    • /
    • pp.563-565
    • /
    • 2021
  • The most important feature of the recently increasing content providing service is that the amount of content increase over time is very large. Accordingly, the importance of user curation is increasing, and various techniques are used to implement it. In this paper, among the techniques for video recommendation, the analysis technique using voice data and subtitles and the video comparison technique based on keyframe extraction are compared with the results of implementing and applying the video content of real big data. In addition, through the comparison result, a video content environment to which each analysis technique can be applied is proposed.

  • PDF

Customized Recommendation and Information Service for Men Cosmetics (남성 화장품 맞춤 추천 및 정보 제공 서비스)

  • Park, Eun-seo;Lee, Min-ji;Jeong, Min-ji;Bak, Do-yeon;Moon, Yoo-Jin
    • Proceedings of the Korean Society of Computer Information Conference
    • /
    • 2021.01a
    • /
    • pp.353-354
    • /
    • 2021
  • 본 연구에서는 빠르게 발전하는 남성 화장품 시장 트렌드에 맞춰서 남성 고객과 남성 화장품을 타겟으로 하는 기업에 유용한 정보를 제공할 수 있는 데이터베이스 시스템을 구축하고자 한다. 아직까지는 여성에 비해 남성 고객과 남성 화장품에 대한 데이터 분석 및 연구가 현저히 적은 편이다. 본 연구는 남성 고객의 데이터와 빅데이터 자료를 바탕으로 구매율이 높은 상위 10개 제품명과 브랜드명, 소비자가 원하는 가격대의 유명하고 인기있는 제품, 특정 피부고민을 가진 고객이 구매한 제품 중 알레르기 유발 물질이 포함된 제품의 정보와 같은 유용한 정보들을 데이터베이스 시스템을 활용하여 산출해냈다. 이를 통해, 남성 화장품 시장이 앞으로 나아갈 방향에 대해 파악하고 국내 남성 화장품 시장의 발전에도 이바지할 수 있을 것으로 예측된다.

  • PDF

Crop Recommendation Service based on Agriculture Environment Data (농업 환경 데이터에 기반한 농작물 추천 서비스)

  • Bae, Jiwon;Lee, Sangwook;Lee, Sywan;Lee, Yeji;Choi, Jun Hyung;Cho, Pil Kuk;Gil, Joon-Min
    • Proceedings of the Korea Information Processing Society Conference
    • /
    • 2021.11a
    • /
    • pp.193-195
    • /
    • 2021
  • 최근 우리나라에서 재배되고 있는 농작물은 지구 온난화 등의 영향으로 점점 북상하고 있다. 이러한 농업 환경의 변화에 적극적으로 대처하기 위해 본 논문에서는 농업 재배지의 환경 데이터를 수집하고 분석하여 현재 농업 재배지에 최적화된 농작물을 추천할 수 있는 농작물 추천 서비스를 제안한다. 이를 위해 농작물 추천 서비스에 활용하기 위해 농업 환경 데이터의 모니터링과 농작물 데이터 관리 스마트팜 모형을 설계 및 구축한다.