SKYLINE QUERY BASED ON USER PREFERENCES IN CELLULAR ENVIRONMENTS

The recommendation system is an important tool for providing personalized suggestions to users about products or services. However, previous research on individual recommendation systems using skyline queries has not considered the dynamic personal preferences of users. Therefore, this study aims to develop an individual recommendation model based on the current individual preferences and user location in a mobile environment. We propose an RFM (Recency, Frequency, Monetary) score-based algorithm to predict the current individual preferences of users. This research utilizes the skyline query method to recommend local cuisine that aligns with the individual preferences of users. The attributes used in selecting suitable local cuisine include individual preferences, price, and distance between the user and the local cuisine seller. The proposed algorithm has been implemented in the JALITA mobile-based Indonesian local cuisine recommendation system. The results effectively recommend local cuisine that matches the dynamic individual preferences and location of users. Based on the implementation results, individual recommendations are provided to mobile users anytime and anywhere they are located. In this study, three skyline objects are generated: soto betawi (C5), Mie Aceh Daging Goreng (C4), and Gado-gado betawi (C3), which are recommended local cuisine based on the current individual preferences (U1) and user location (L1). The implementation results are exemplified for one user located at (U1L1), providing recommendations for soto betawi (C5) with an individual preference score of 0.96, Mie Aceh Daging Goreng (C4) with an individual preference score of 0.93, and Gado-gado betawi (C3) with an individual preference score of 0.98. Thus, this research contributes to the field of individual recommendation systems by considering the dynamic user location and preferences

Multimedia data integration and retrieval in planning support systems

Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 1998.Includes bibliographical references (p. 83-86).by Carleton Tsui.M.C.P

Advances in knowledge discovery and data mining Part II

19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II</p

Tangible Scalar Fields

Data Visualization is a field that explores how to most efficiently convey information to the user, most often via visual representations like plots, graphs or glyphs. While this field of research has had great growth within the last couple of years, most of the work has been focused on the visual part of the human visual and auditory system - much less visualization work has been done in regards to the visually impaired. In this thesis, we will look at some previous methods and techniques for visualizing scalar fields via the sense of touch, and additionally provide two novel approaches to visualize a two-dimensional scalar field. Our first approach creates passive physicalizations from a scalar field in a semi-automatic pipeline by encoding the scalar value and field coordinates as positions in 3D space, which we use to construct a triangular mesh built from hexagonal pillars that can be printed on a 3D printer. We further enhance our mesh by encoding a directional attribute on the pillars, creating a visual encoding of the model orientation and improving upon a readability issue by mirroring the mesh. Our second approach uses a haptic force-feedback device to simulate the feeling of moving across a surface based on the scalar field by replicating three physical forces: the normal force, the friction force and the gravity force. We also further extend our approach by introducing a local encoding of global information about the scalar field via a volume representation build from the scalar field.Masteroppgave i informatikkINF399MAMN-PROGMAMN-IN