نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد، دانشکده علوم ریاضی و رایانه دانشگاه علامه طباطبائی

2 استادیار گروه رایانه دانشگاه علامه طباطبائی

چکیده

سلامت، بهداشت و خدمات درمانی قسمت جدایی‌ناپذیر زندگی هر فردی در طول زندگی‌اش است. هر فردی در دوره‌های مختلف زندگی خود به‌نوعی نیازهای متنوعی در حوزه سلامت احساس می‌کند که با استفاده از امکانات موجود، سعی در پاسخ‌گویی به‌این نیازها را دارد. با توجه به استقبال زیاد افراد از شبکه‌های اجتماعی در دو دهه اخیر، یکی از ابزارهایی که می‌تواند امکانات مختلفی را در اختیار افراد در حوزه سلامت بگذارد شبکه‌های اجتماعی است. در این پژوهش ی1ک شبکه اجتماعی سلامت معرفی‌ شده است که بر روی ارتباط کاربران یا بیماران با پزشکان و خدمات درمانی مختلف تمرکز دارد. برای بهبود کارایی این شبکه یک سیستم توصیه‌گر پیشنهاد شده است که می‌تواند به کاربران یک پزشک، یک حوزه تخصصی جهت اخذ مشاوره پزشکی و یا یک مطلب را بر اساس نیازمندی‌های آنان پیشنهاد دهند. از شبکه‌های اطلاعاتی ناهمگون برای مدل‌سازی شبکه اجتماعی سلامت بهره گرفته‌ایم. این شبکه‌ها وجود چندین نوع شیء، مانند پزشک، بیمار و مشاوره، و چندین نوع رابطه، مانند درخواست مشاوره و پاسخ به مشاوره، را در برمی‌گیرند. برای مدل توصیه، با توجه به روش‌هایی که شبکه‌های ناهمگون ارائه می‌دهند، از بازخوردهای ضمنی‌ای که هر فرد در شبکه ثبت می‌کند، استفاده کردیم تا با یافتن شباهت‌های مطابق با این بازخوردها، بهترین پیشنهاد‌ها را به وی ارائه دهیم. برای الگوریتم یادگیری مدل توصیه از رتبه‌بندی، شخصی‌سازی‌ شده بیزین استفاده‌ شده است. الگوریتم ارائه‌ شده ترکیبی از روش امتیاز رتبه‌بندی و الگوریتم یادگیری مذکور است. در انتها با اعمال روش پیشنهادی بر روی مجموعه داده، کارایی این شبکه اجتماعی و سیستم توصیه‌گر نشان داده‌ شده است.

کلیدواژه‌ها

عنوان مقاله [English]

Health Social Network: a Recommender System with Heterogeneous Information Network approach

نویسندگان [English]

  • seyed saeed mortazavi 1
  • Fereshteh-Azadi Parand 2

1 Allameh Tabataba'i University - Faculty of mathematics & computer science  

2 Allameh Tabataba'i University - Faculty of mathematics & computer science, Tehran, Iran  

چکیده [English]

Health and health services are two inseparable parts of one's life. Each person has had different needs for health services at least several times during their life cycle and would resolve them with available facilities. Regarding the high popularity of social networks in the last two decades, one of the tools that can provide many opportunities for people in the health field is social networking. In this research, we introduce a health social network which focuses on users or patients’ association with doctors and a variety of health services. In order to improve this network’s performance, we suggest a recommender system that can offer users a doctor, a special expertise in order to ask medical consultation, or an article, based on their needs. We have used heterogeneous information networks for modeling the health social network. These networks cover several types of objects, such as physicians, patients and consultation, and also several types of relationships, such as requesting or answering a consultation. For the recommender model, we use each user’s implicit feedback which they register on the network, according to the methods provided by the heterogeneous information networks. Bayesian Personalized Ranking is used in recommender model’s learning algorithm. This algorithm is a combination of ranking scores method and the foresaid learning algorithm. In the end, we will show how to use this social network and the recommender system, by applying the suggested method on our dataset.

کلیدواژه‌ها [English]

  • Health
  • recommender system
  • heterogeneous information network
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