EFFECTIVE FEATURES ON DEMAND MANAGEMENT IN WEB BASED E-MARKETPLACE BUSINESSES BY MACHINE LEARNING ALGORITHMS (CASE STUDY)

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Jafari Aram; Shahryar Soltanali; KHASTAR HAMZA

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2019 | Issue:5

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Title

EFFECTIVE FEATURES ON DEMAND MANAGEMENT IN WEB BASED E-MARKETPLACE BUSINESSES BY MACHINE LEARNING ALGORITHMS (CASE STUDY)

Author(s)

Jafari Aram | Shahryar Soltanali | KHASTAR HAMZA

Keywords

MACHINE LEARNING

FEATURE SELECTION

E-MARKETPLACE

DEMAND FORECASTING

CORRELATION

Abstract

DEMAND MANAGEMENT AND SALES FORECASTING FORM THE FOUNDATION FOR ALL PLANNING AND DELIVERING PROCESSES. THE BEGINNING OF PROCESS HAS STARTED BY SELECTING CORRECT FEATURES. CORRELATION ANALYSIS IS AN EXTENSIVELY USED TECHNIQUE THAT IDENTIFIES INTERESTING RELATIONSHIPS IN DATA. EACH PRODUCT CATEGORY HAS OWN EFFECTIVE FEATURES AND THESE RELATIONSHIPS HELP US REALIZE THE RELEVANCE OF ATTRIBUTES WITH RESPECT TO THE TARGET CLASS TO BE PREDICTED. IN THIS STUDY, PARAMETERS HAVE CHOSEN BY VISUALIZED PEARSON AND PCA METHODS. THE RESULT SHOWS 8 PARAMETERS ARE GOOD TO USE IN FORECASTING OUT OF 23 PARAMETERS.

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APA: Copy

Jafari, Aram, Shahryar, Soltanali, & KHASTAR, HAMZA. (2019). EFFECTIVE FEATURES ON DEMAND MANAGEMENT IN WEB BASED E-MARKETPLACE BUSINESSES BY MACHINE LEARNING ALGORITHMS (CASE STUDY). INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/949122/en

Vancouver: Copy

Jafari Aram, Shahryar Soltanali, KHASTAR HAMZA. EFFECTIVE FEATURES ON DEMAND MANAGEMENT IN WEB BASED E-MARKETPLACE BUSINESSES BY MACHINE LEARNING ALGORITHMS (CASE STUDY). 2019. Available from: https://sid.ir/paper/949122/en

IEEE: Copy

Aram Jafari, Soltanali Shahryar, and HAMZA KHASTAR, “EFFECTIVE FEATURES ON DEMAND MANAGEMENT IN WEB BASED E-MARKETPLACE BUSINESSES BY MACHINE LEARNING ALGORITHMS (CASE STUDY),” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2019, [Online]. Available: https://sid.ir/paper/949122/en

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