Wang-Chien Lee

TL;DR: ROAD, a system framework for processing location dependent spatial queries (LDSQs) that search for spatial objects of interest on road networks is developed and explained how it can support efficient location-dependent nearest neighbor search.

TL;DR: In the panel discussion session of International Workshop on Mobile Data Access, an enthusiastic audience was invited to join the panel of experts, Prof. Dik Lun Lee (Hong Kong University of Science and Technology, Hong Kong), Dr. Radhakrishna Pillai (Kent Ridge Digital Labs, Singapore), Hiroki Takakura (Kyoto University, Japan) and Mr. Stuart Jacobs (GTE Laboratories, USA) to explore several important issues relating to the data access aspect of mobile computing.

TL;DR: A framework for business location planning that takes into account both factors of geographical proximity and social influence is proposed and a suite of algorithms based on Targeted Region-oriented strategy is designed to enhance the processing efficiency.

TL;DR: A learning framework, namely, SNMD-Aware Personalized nEwsfeed Ranking (SAPER), that exploits features extracted from social network data to measure the addictive degree of a newsfeed and a randomized algorithm called Computing Budget Optimization for MEMIC with Newsfeed Di‚erentiation (CBOM-ND), which is promising for alleviating the symptoms of online social network users with potential SNMDs.

TL;DR: This paper first investigates the fundamental shortest-path query in VR as the building block for spatial queries, and designs a fully polynomial-time approximation scheme, Dual Entangled World Navigation (DEWN), and shows that the existing spatial query algorithms and index structures can leverage DEWN as a building block to support kNN and range queries in the dual worlds of VR.