Matches in SemOpenAlex for { <https://semopenalex.org/work/W4382042497> ?p ?o ?g. }
- W4382042497 endingPage "124" @default.
- W4382042497 startingPage "105" @default.
- W4382042497 abstract "A higher education system needs to ensure its teaching process and materials are aligned with the graduate employment market needs and expectations. If a university has built trust in the industry, it would be more likely to have its graduates to find suitable relevant jobs in the market. As a result, this will have positive feedback to absorb better students to select the desired university as their first choice to study; consequently, the university’s reputation will improve. In this research, a novel prototype has been suggested to support strategic decision-making in academic curriculum planning based on the university’s ‘business-focus’ vision. To achieve the aim, the CRISP-DM model was used, and different Python libraries were applied for scraping data, creating a dataset, data preparation, and weighting keyword technologies depending on the most demanded skills. A job dataset was created by scraping job descriptions from social media. In this research, the skills, gathered from Stack Overflow’s survey, were counted in job descriptions and the most popular skills were identified. Finally, the job dataset was categorised based on the top-ranked skills." @default.
- W4382042497 created "2023-06-27" @default.
- W4382042497 creator A5007282661 @default.
- W4382042497 creator A5036711977 @default.
- W4382042497 creator A5037774353 @default.
- W4382042497 creator A5048745928 @default.
- W4382042497 date "2023-01-01" @default.
- W4382042497 modified "2023-09-24" @default.
- W4382042497 title "Strategic Decision-Making for Pedagogical Course Planning Using NLP in Social Media Data" @default.
- W4382042497 cites W1139185857 @default.
- W4382042497 cites W1530276735 @default.
- W4382042497 cites W1571245262 @default.
- W4382042497 cites W1972627317 @default.
- W4382042497 cites W1998948107 @default.
- W4382042497 cites W2010283199 @default.
- W4382042497 cites W2012266188 @default.
- W4382042497 cites W2025605741 @default.
- W4382042497 cites W2037594831 @default.
- W4382042497 cites W2042228598 @default.
- W4382042497 cites W2043011534 @default.
- W4382042497 cites W2046940298 @default.
- W4382042497 cites W2051639611 @default.
- W4382042497 cites W2054141820 @default.
- W4382042497 cites W2087596448 @default.
- W4382042497 cites W2101409192 @default.
- W4382042497 cites W2117281325 @default.
- W4382042497 cites W2141824101 @default.
- W4382042497 cites W2153441753 @default.
- W4382042497 cites W2163419627 @default.
- W4382042497 cites W2171960770 @default.
- W4382042497 cites W2179018291 @default.
- W4382042497 cites W2398391135 @default.
- W4382042497 cites W2515120505 @default.
- W4382042497 cites W2515748867 @default.
- W4382042497 cites W2579393094 @default.
- W4382042497 cites W2593454894 @default.
- W4382042497 cites W2596352504 @default.
- W4382042497 cites W2606989390 @default.
- W4382042497 cites W2756268972 @default.
- W4382042497 cites W2763172566 @default.
- W4382042497 cites W2770313115 @default.
- W4382042497 cites W2772773094 @default.
- W4382042497 cites W2772952572 @default.
- W4382042497 cites W2780526393 @default.
- W4382042497 cites W2791327891 @default.
- W4382042497 cites W2797753066 @default.
- W4382042497 cites W2802966978 @default.
- W4382042497 cites W2803478834 @default.
- W4382042497 cites W281665770 @default.
- W4382042497 cites W2864717551 @default.
- W4382042497 cites W2906819001 @default.
- W4382042497 cites W2909846792 @default.
- W4382042497 cites W2912866523 @default.
- W4382042497 cites W2914866826 @default.
- W4382042497 cites W2915676182 @default.
- W4382042497 cites W2921396150 @default.
- W4382042497 cites W2946715088 @default.
- W4382042497 cites W2946916365 @default.
- W4382042497 cites W2950262217 @default.
- W4382042497 cites W2953020728 @default.
- W4382042497 cites W3004766324 @default.
- W4382042497 cites W3004971355 @default.
- W4382042497 cites W3023883624 @default.
- W4382042497 cites W3128139448 @default.
- W4382042497 cites W3156854631 @default.
- W4382042497 cites W3165290256 @default.
- W4382042497 cites W3170152309 @default.
- W4382042497 cites W4210577509 @default.
- W4382042497 cites W4232617529 @default.
- W4382042497 cites W4246055473 @default.
- W4382042497 cites W4311561869 @default.
- W4382042497 doi "https://doi.org/10.1007/978-3-031-33627-0_5" @default.
- W4382042497 hasPublicationYear "2023" @default.
- W4382042497 type Work @default.
- W4382042497 citedByCount "0" @default.
- W4382042497 crossrefType "book-chapter" @default.
- W4382042497 hasAuthorship W4382042497A5007282661 @default.
- W4382042497 hasAuthorship W4382042497A5036711977 @default.
- W4382042497 hasAuthorship W4382042497A5037774353 @default.
- W4382042497 hasAuthorship W4382042497A5048745928 @default.
- W4382042497 hasConcept C111919701 @default.
- W4382042497 hasConcept C126838900 @default.
- W4382042497 hasConcept C136764020 @default.
- W4382042497 hasConcept C144024400 @default.
- W4382042497 hasConcept C145420912 @default.
- W4382042497 hasConcept C154945302 @default.
- W4382042497 hasConcept C15744967 @default.
- W4382042497 hasConcept C183115368 @default.
- W4382042497 hasConcept C19417346 @default.
- W4382042497 hasConcept C2522767166 @default.
- W4382042497 hasConcept C36289849 @default.
- W4382042497 hasConcept C41008148 @default.
- W4382042497 hasConcept C47177190 @default.
- W4382042497 hasConcept C48798503 @default.
- W4382042497 hasConcept C518677369 @default.
- W4382042497 hasConcept C519991488 @default.
- W4382042497 hasConcept C56739046 @default.
- W4382042497 hasConcept C71924100 @default.