Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Faculty of Business | en_US |
| dc.contributor.advisor | Li, Qing (COMP) | en_US |
| dc.creator | Zheng, Shenggang | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/12513 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | PRS-CASS : towards a personalized recommender system for college admission systems with scholarships | en_US |
| dcterms.abstract | This study demonstrates a personalized recommender system for college admission systems with scholarship by taking advantage of collaborative filtering as well as dispersion calculation in order to address college programme admissions with scholarship prediction problems. This PRS-CASS system is composed of three stages. First of all, it predicts three types of college or university choices including insurance choices, high possibility choices, and low possiblity choices by the calculation of the admission possibility which is a linear relationship with dispersion calculated. In the second stage, it predicts subject admission possibility based on the first stage through calculating the lowest admission ranking position, the average admission ranking position, and the highest admission ranking position of the subject or programme in the province or province-level municipality in the past three year. In the third stage, it involves five weighted factors like scholarships offered by colleges or universities that the applicant plans to select, university ranking, subject ranking, district type that the city where the university locates at, and tuition fees. It matches colleges or universities and subjects or programmes well with the applicant’s personalized demands and interests. | en_US |
| dcterms.abstract | In the PRS-CASS, the subscription business model and the advertising business model may be combined together in order to utilize their own advantages to make up each other’s weaknesses. The subscription model is suitable for users like applicants and the advertising model is suitable for those colleges or programmes lack of sufficient applicants. In order to validate system trustability, 100 mock applicants were put into it and results show that it works well. Beyond that, an online questionnaire has been done and 103 of 109 participants are valid participants. 70.9 % of participants give 6 point or above on satisfaction of PRS-CASS on a scale of 1 to 10. There are 73.8% of participants give 6 point or above on a scale of 1 to 10 in the helpful level of PRS-CASS to them. The personalized services play a significant role in e-commerse and increase customers’ purchase intentions. In order to prove personalized services still working well in the field of RS-CASS of the educational market. Two hypothesis are supposed. H1: The personalized service of PRS-CASS has a significant positive effect on RS-CASS choice of applicants. H2: The scholarship prediction feature of PRS-CASS has a significant positive effect on RS-CASS choice of applicants. Both of H1 and H2 are supported by the results of the online questionnaire. The personalized services play a significant role in prompting users to select PRS-CASS. It may fill in gaps in the field of RS-CASS in the educational market from the point of view in business research. Therefore, it may has a significant contribution in the business research of this area. | en_US |
| dcterms.extent | v, 114 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2023 | en_US |
| dcterms.educationalLevel | DFinTech | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.LCSH | Recommender systems (Information filtering) | en_US |
| dcterms.LCSH | Universities and colleges -- Admission | en_US |
| dcterms.LCSH | College choice | en_US |
| dcterms.LCSH | Learning and scholarship | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 6961.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 1.14 MB | Adobe PDF | View/Open |
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