Multi-Point Travel Destination Recommendation System in Yogyakarta Using Hybrid Location Based Service-Floyd Warshall Method1

With the deep cross-border integration of tourism and big data, the personalized demand of tourist groups is increasingly strong. Precision marketing has become a new marketing mode that the tourism industry needs to pay close attention to and explore. Based on the advantages of big data platform and location-based service, starting from the precise marketing demand of tourism, we design data flow mining technology framework for user’s mobile behavior trajectory based on location services in mobile e-commerce environment to get user track data that incorporates location information, consumption information, and social information. Data mining clustering technology is used to analyze the characteristics of users’ mobile behavior trajectories, and the precise recommendation system of tourism is constructed to provide support for tourism decision making. It can target the tourist group for precise marketing and make tourists travel smarter.

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Analysis on Research Paper Publication Recommendation System with Composition of Papers and Conferences Matrices

International Journal of Scientific Research in Science Engineering and Technology ◽

10.32628/ijsrset207330 ◽

2020 ◽

pp. 120-127

Author(s):

Htay Htay Win ◽

Aye Thida Myint ◽

Mi Cho Cho

Keyword(s):

Social Network ◽

Dimensionality Reduction ◽

Correspondence Analysis ◽

Recommendation System ◽

Research Paper ◽

Topic Modelling ◽

Research Papers ◽

The Right ◽

Publication Recommendation

For years, achievements and discoveries made by researcher are made aware through research papers published in appropriate journals or conferences. Many a time, established s researcher and mainly new user are caught up in the predicament of choosing an appropriate conference to get their work all the time. Every scienti?c conference and journal is inclined towards a particular ?eld of research and there is a extensive group of them for any particular ?eld. Choosing an appropriate venue is needed as it helps in reaching out to the right listener and also to further one’s chance of getting their paper published. In this work, we address the problem of recommending appropriate conferences to the authors to increase their chances of receipt. We present three di?erent approaches for the same involving the use of social network of the authors and the content of the paper in the settings of dimensionality reduction and topic modelling. In all these approaches, we apply Correspondence Analysis (CA) to obtain appropriate relationships between the entities in question, such as conferences and papers. Our models show hopeful results when compared with existing methods such as content-based ?ltering, collaborative ?ltering and hybrid ?ltering.

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