Alternative group trip planning queries in spatial databases

Trip Planning Queries are considered as one of the popular services offered by Location-Based Services. We propose a new query type called an Alternative Group Trip Planning Query (AGTPQ) which is an extended version of Sequenced Group Trip Planning Queries (SGTPQs). Given a set of users’ source locations and destination locations and a sequence of Categories of Interest (COIs) that the users want to visit, an AGTPQ generates a new COI sequence order using one of the proposed techniques and finds an optimal trip starting from the source locations, passing through the new sequenced COI order and ending at the destination locations. We propose three approaches: Permutation Strategy on Sequenced Group Trip Planning Queries (PSGTPQs), Greedy Strategy on Sequenced Group Trip Planning Queries (GSGTPQs) and Random Strategy on Sequenced Group Trip Planning Queries (RSGTPQs). We compare the results of our proposed strategies with the PGNE strategy through experimental evaluation

Spatial Queries for Indoor Location-based Services

Indoor Location-based Services (LBS) facilitate people in indoor scenarios such as airports, train stations, shopping malls, and office buildings. Indoor spatial queries are the foundation to support indoor LBSs. However, the existing techniques for indoor spatial queries are limited to support more advanced queries that consider semantic information, temporal variations, and crowd influence. This work studies indoor spatial queries for indoor LBSs. Some typical proposals for indoor spatial queries are compared theoretically and experimentally. Then, it studies three advanced indoor spatial queries, a) Indoor Keyword-aware Routing Query. b) Indoor Temporal-variation aware Routing Query. c) Indoor Crowd-aware Routing Query. A series of techniques are proposed to solve these problems.</p