[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124613-en":3,"doc-seo-124613-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124613,687197100911,"Himbo","https://ap-avatar.wpscdn.com/avatar/a000239b6f1da00475?x-image-process=image/resize,m_fixed,w_180,h_180&k=1785132997149421697",8,"Research & Report","Innovative Food Recommendation Systems - a Machine Learning Approach - Doctor of Philosophy Thesis","Recommendation systems use user history to predict preferences and have been applied across domains such as biology, e-commerce, and healthcare. Traditional content-based, collaborative-based, and hybrid methods cannot adequately solve all real-world tasks, especially the challenging area of food recommendation, which requires guidance toward healthy, balanced, and personalized meal choices. This PhD thesis develops new machine learning approaches: a many-objective transformation for more balanced results, a unified sequence-based personalization framework for dynamic behavior, and a temporal dependent graph neural network with data augmentation for accurate and robust recommendations.","Innovative Food Recommendation  \nSystems: a Machine Learning Approach  \nJieyu Zhang  \nDepartment of Computer Science Brunel University London  \nThis thesis is submitted for the degree of Doctor of Philosophy  \nI would like to dedicate this thesis to my parents.  \nDeclaration  \nI, Jieyu Zhang, hereby declare that this thesis and the work presented in it are entirely my own. Some of the work has been previously published in journal or conference papers, and this has been mentioned in the thesis. Where I have consulted the work of others, this is always clearly stated.  \nJieyu Zhang May 2023  \nAcknowledgements  \nFirst, I would like to express my sincere gratitude to my supervisors, Prof. Xiaohui Liu and Prof. Zidong Wang, for their consistent encouragement, inspiring motivation, professional guidance, and constant help. They have guided me through the entire process of writing this thesis. Without their unwavering guidance and enlightenment, this thesis would not have achieved its current form. Prof. Xiaohui Liu was consistently encouraging of my explorationsin research and provided me with kindly guidance. His guidance, motivation, and patience have always been of tremendous assistance to me throughout my academic journey. I would also like to take this opportunity to express my sincere thanks to Prof. Zidong Wang. His words of encouragement and assistance have been an invaluable source of strength for me.  \nSecond, I would like to express my heartfelt gratitude to the following people for useful discussions, suggestions, comments, and supports of my research during the PhD stage: Dr. Weibo Liu, Dr. Chuang Wang, Dr. Yani Xue, Dr. Nan Hou, Dr. Wei Chen, Dr. Mincan Li. It is my honor to meet you in these years.  \nLast but not least, I want to express my gratitude to my dear family for their unwavering support, thoughtfulness, and high level of trust in me throughout the years. My parents have always supported me and helped me when I was in need without ever complaining. Their selfless love and concern have motivated me and kept me going.  \nAbstract  \nRecommendation systems employ users history data records to predict their preference, and have been widely used in diverse fields including biology, e-commerce, and healthcare. Traditional recommendation techniques include content-based, collaborative-based and hybrid methods but not all real-world problems can be best addressed by these classical recommendation techniques. Food recommendation is one such challenging problem where there is an urgent need to use novel recommendation systems in assisting people to select healthy, balanced and personalized food plans. In this thesis, we make several advances in food recommendation systems using innovative machine learning methods. First, a novel recommendation approach is proposed by transforming an original recommendation problem into a many-objective optimisation one that contains several different objectives resulting in more balanced recommendations. Second, a unified approach to designing sequence-based personalised food recommendation systems is investigated to accommodate dynamic user behaviours. Third, a new food recommendation approach is developed with a temporal dependent graph neural network and data augmentation techniques leading to more accurate and robust recommendations. The experimental results show that these proposed approaches have not only provided a more balanced and accurate way of recommending food than the traditional methods but also led to promising areas for future research.","cbCaibWFKuv7jnv2","https://ap.wps.com/l/cbCaibWFKuv7jnv2","pdf",1941386,1,132,"English","en",105,"# Abstract\n## Research motivation and problem scope\n## Proposed machine learning advances\n## Experimental outcomes and future directions","[{\"question\":\"为什么食物推荐属于具有挑战性的推荐任务？\",\"answer\":\"食物推荐需要在真实场景中实现健康、均衡且个性化的选择，而传统内容/协同/混合方法并不能最好地覆盖所有现实问题。\"},{\"question\":\"论文提出了哪些核心方法来改进食物推荐？\",\"answer\":\"论文提出：将原推荐问题转化为多目标优化以获得更均衡的推荐；研究统一的序列式个性化方法以适配用户动态行为；并使用时间相关图神经网络结合数据增强以提升准确性与鲁棒性。\"},{\"question\":\"实验结果主要表明了什么改进？\",\"answer\":\"实验结果显示，所提出方法相比传统方法在推荐的均衡性与准确性方面更具优势，并为后续研究提供了有前景的方向。\"}]","Innovative Food Recommendation Systems - a Machine Learning Approach - Doctor of Philosophy Thesis | PDF",1785893323,333,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"innovative-food-recommendation-systems-a-machine-learning-approach-doctor-of-philosophy-thesis","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/innovative-food-recommendation-systems-a-machine-learning-approach-doctor-of-philosophy-thesis/124613/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"为什么食物推荐属于具有挑战性的推荐任务？","Question",{"text":75,"@type":76},"食物推荐需要在真实场景中实现健康、均衡且个性化的选择，而传统内容/协同/混合方法并不能最好地覆盖所有现实问题。","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"论文提出了哪些核心方法来改进食物推荐？",{"text":80,"@type":76},"论文提出：将原推荐问题转化为多目标优化以获得更均衡的推荐；研究统一的序列式个性化方法以适配用户动态行为；并使用时间相关图神经网络结合数据增强以提升准确性与鲁棒性。",{"name":82,"@type":73,"acceptedAnswer":83},"实验结果主要表明了什么改进？",{"text":84,"@type":76},"实验结果显示，所提出方法相比传统方法在推荐的均衡性与准确性方面更具优势，并为后续研究提供了有前景的方向。","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]