ﺳﯿﺴﺘﻢ ﭘﯿﺸﻨﻬﺎد دﻫﻨﺪه ﺧﺮﯾﺪ ﺗﻠﻔﻦ ﻫﻤﺮاه ﺑﺎ اﺳﺘﻔﺎده از ﻓﯿﻠﺘﺮﯾﻨﮓ داﻧﺶﻣﺤﻮر

Mobile Recommender System using Knowledge based Filtering

ﺑﺮاي ﺗﺴﺮﯾﻊ در اﻧﺘﺨﺎب و ﺗﺼﻤﯿﻢﮔﯿﺮي ﺻﺤﯿﺢ در ﺣﻮزه ﺗﻠﻔﻦ ﻫﻤﺮاه، ﺳﯿﺴﺘﻢ ﭘﯿﺸﻨﻬﺎد دﻫﻨﺪه ﺗﻠﻔﻦ ﻫﻤﺮاه داﻧﺶ ﻣﺤﻮر ﻫﻤﺮاه ﺑﺎ ﭘﺮﺳﺸﻨﺎﻣﻪ ﻋﻼﯾﻖ ﻓﺮدي در اﯾﻦ ﺗﺤﻘﯿﻖ اراﺋﻪ ﺷﺪه اﺳﺖ. در اﺑﺘﺪا دادهﻫﺎي ﻣﺸﺨﺼﺎت ﻓﻨﯽ ﺗﻠﻔﻦ ﻫﻤﺮاه ﮔﺮدآوري، ﭘﺎﮐﺴﺎزي، اﻧﺘﺨﺎب و ﺗﺒﺪﯾﻞ ﺷﺪ. ﺳﭙﺲ ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ ﻧﯿﺎز ﮐﺎرﺑﺮان، ﺑﺮﭼﺴﺐﻫﺎﯾﯽ ﻃﺒﻖ ﭼﻨﺪﯾﻦ ﻗﺎﻧﻮن اﺳﺘﺨﺮاج و ﺑﻪ دادهﻫﺎ اﺧﺘﺼﺎص داده ﺷﺪ. ﭘﺲ از آن ﺑﺎ اﺳﺘﻔﺎده از اﻟﮕﻮرﯾﺘﻢ ﻫﺎي ﻃﺒﻘﻪ ﺑﻨﺪي ﻣﺎﻧﻨﺪ درﺧﺖ ﺗﺼﻤﯿﻢ، ﺑﯿﺰ ﺳﺎده و ﻣﺪل ﺧﻄﯽ ﺗﻌﻤﯿﻢ ﯾﺎﻓﺘﻪ ﯾﮏ ﻣﺪل ﺗﺮﮐﯿﺒﯽ اراﺋﻪ ﺷﺪ. اﯾﻦ ﻣﺪل ﺗﺮﮐﯿﺒﯽ ﻫﻤﺮاه ﺑﺎ اﻟﮕﻮرﯾﺘﻢ ﻫﺎي ﯾﺎدﮔﯿﺮي ﻋﻤﯿﻖ و ﺟﻨﮕﻞ ﺗﺼﺎدﻓﯽ ﺑﻪ ﺻﻮرت ﺟﺪاﮔﺎﻧﻪ ﺟﻬﺖ ﻃﺒﻘﻪﺑﻨﺪي ﺗﻠﻔﻦ ﻫﺎي ﻫﻤﺮاه اﺳﺘﻔﺎده ﺷﺪ. در ﻧﻬﺎﯾﺖ اﯾﻦ ﻣﺪلﻫﺎ از ﻟﺤﺎظ دﻗﺖ ارزﯾﺎﺑﯽ ﺷﺪﻧﺪ. ﮐﺎرﺑﺮان ﻣﯽﺗﻮاﻧﻨﺪ ﺑﺎ اﺳﺘﻔﺎده از ﻣﺪل ﭘﯿﺸﻨﻬﺎدي و وارد ﮐﺮدن ﺗﺮﺟﯿﺤﺎت ﺧﻮد ﺗﻮﺳﻂ ﭘﺮﺳﺸﻨﺎﻣﻪ ﻋﻼﯾﻖ ﻓﺮدي، ﺑﻪ اﻧﺘﺨﺎب ﺗﻠﻔﻦ ﻫﻤﺮاه ﻣﻨﺎﺳﺐ ﺧﻮد ﺑﭙﺮدازﻧﺪ.

In order to provide quick selection and decision making in the field of mobile phones marketing, a knowledge-based mobile recommender system along with a personal interest questionnaire is proposed in this research. Initially, the mobile technical data was collected, cleaned, selected, and converted, then assigned labels to the data according to several extracted rules according to users' needs. Then a hybrid model was proposed using classification algorithms such as decision tree, naive Bayes and generalized linear model. This hybrid model along with deep learning algorithms and random forest were used to classify cell phones separately. Finally, these models were evaluated in terms of accuracy. Users can choose their preferred mobile phone using the suggested model and enter their preferences using the Personal Interests Questionnaire.