شماره ركورد كنفرانس :
578
عنوان مقاله :
Suggestions for What to Eat and What Not, Based on Your Mood: Presenting a Model Works with Social Network Analysis
پديدآورندگان :
Tasviri Maryam نويسنده , hashemi golpayegani alireza نويسنده , Ghavamipoor Hoda نويسنده
كليدواژه :
temperaments on traditional medicine , user’s mental mood , COMPONENT , network analysis , Data mining , Healthy nutrition
عنوان كنفرانس :
سومين كنفرانس بين المللي وب پژوهي
چكيده فارسي :
This study presents a model offering people which food is healthier and makes them more satisfied based on their moods and food consumption behaviors. The social network analysis techniques are applied on the food consumption of the people whom were recorded in information systems. The implementation method is according to this procedure: first, people classified to 6 groups based on their nutrition style getting from the Islamic traditional medicine and some previous papers in the modern medicine. Then, a data network was made from people’s relationships. Afterwards, a model has been presented based on the analysis of that network. To evaluate this model, the proposed method is applied on a university’s self-service restaurant system. The results show that people with a healthy or "hot and wet" temperament nutrition style, have personality traits of “extraversion”, “openness” and “conscientiousness”. Moreover, people with a traditional nutrition style or "cold and wet" temperament nutrition, are people with personality traits of “introversion” and “neuroticism”.
شماره مدرك كنفرانس :
4445660