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دسته بندی:
داده های بزرگ - big data
سال انتشار:
2018
عنوان انگلیسی مقاله:
Food Trend Based on Social Media for Big Data Analysis Using K-Mean Clustering and SAW
ترجمه فارسی عنوان مقاله:
روند تغذیه بر اساس رسانه های اجتماعی برای تجزیه و تحلیل داده های بزرگ با استفاده از خوشه بندی K-Mean و SAW
منبع:
IEEE - 2018 International Conference on Information and Communications Technology (ICOIACT)
نویسنده:
Mihuandayani ، Herda D. Ramandita ، Arief Setyanto Ikhwan B. Sumafta
چکیده انگلیسی:
tracking customer preferences is an important
aspect of business success. Having information on hand about
most favorite food is a key success for everyone who takes apart
in the culinary business. Exact sales data on certain food is
hardly available to the public. Restaurant owner tends to keep
their data for their own business strategy. Therefore, generating
a food trend in a certain community is hardly possible using food
sales data. This paper discussed extracting food general trend
from social media, with the case study on Twitter data with a
certain regional area of interest. Social media provides a
tremendous amount of data including people choice of food when
they visit the certain place. However, the available data is
unstructured in human language. The challenge is twofold: to
grasp the meaning and extract the relevant information to the
food trends. We proposed a bag of words technique to gather
relevant information in the Indonesian language for feature
extracting purpose. While K-mean Clustering and Simple
Additive Weighting (SAW) algorithm are proposed to draw up
the food rank. In order to measure the accuracy, we compare our
result with the sales data of some restaurants in Yogyakarta. We
test the algorithm using 4 weeks of data, the result is compared
against the available data and an accuracy of 72.75 % is
achieved
Keywords: social media; food trend; big data; bag of words; K mean clustering; simple additive weighting
قیمت: رایگان
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