International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395 -0056
Volume: 04 Issue: 3 | Mar -2017
p-ISSN: 2395-0072
www.irjet.net
Survey on Location Based Recommendation System Using POI Devendra Chopade1, Ashutosh Patil2, Puja Sinha3, Rahul Kumar4 1Student,
Information Technology, SKN Sinhgad Institute of Technology, Maharashtra, India Information Technology, SKN Sinhgad Institute of Technology, Maharashtra, India 3Student, Information Technology, SKN Sinhgad Institute of Technology, Maharashtra, India 4Student, Information Technology, SKN Sinhgad Institute of Technology, Maharashtra, India 2Student,
---------------------------------------------------------------------***--------------------------------------------------------------------1. Data Mining Abstract – POI based recommendation system is a web based application, That facilitates, analysis of an individual. The point of interest (POI) is geographical can also be temporal. Such a system would prove valuable tool in the inventory of a corporation or individual. The services provided By this system could be optimized with the consideration of user interest drift. Development of mobile devices with parallel advancement in GPS (Global Position System) and web technology unable the user to share data information based on its relevance to application user. This information is gathered using data mining technique. It is important to foe users
Data mining is the process of discovering actionable information from large sets of data. Data mining is typically uses the mathematical analysis to derive the patterns that exist in data. In data mining these patterns cannot be discovered by traditional data exploration because the relationships are too complex or maybe there is too large amount of data.
Key Words: Data Mining, POI recommendation, User Interest Drift, Collective Inference, User Modelling.
1.2 System Architecture
1.INTRODUCTION In modern world with the rapid development of mobile devices web technologies and point of interest is becoming very popular now days locations revolutionized communication in social temporal with their friends they share their locations and photos uploading via internet for POI. To make use of the rich information on social relationships Users recommend the new locations to explore them. These data is then received and represents it in different formats like HTML, JavaScript and CSS. It has been traditionally used to communicate with the web services. It also provides the messaging services. On the internet where the number of choices is overwhelming, there is need to filter, prioritize and efficiently deliver the relevant information in order to alleviate the problem of information overload, which create a potential problem too many users. Recommender system solves this problem by searching through the large volume of dynamically generated information to provide users with personalized content which are in user’s point of interest. So it is easy for users to Drift across the region.
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Fig. System Architecture
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