ﻻ يوجد ملخص باللغة العربية
The trip planning query searches for preferred routes starting from a given point through multiple Point-of-Interests (PoI) that match user requirements. Although previous studies have investigated trip planning queries, they lack flexibility for finding routes because all of them output routes that strictly match user requirements. We study trip planning queries that output multiple routes in a flexible manner. We propose a new type of query called skyline sequenced route (SkySR) query, which searches for all preferred sequenced routes to users by extending the shortest route search with the semantic similarity of PoIs in the route. Flexibility is achieved by the {it semantic hierarchy} of the PoI category. We propose an efficient algorithm for the SkySR query, bulk SkySR algorithm that simultaneously searches for sequenced routes and prunes unnecessary routes effectively. Experimental evaluations show that the proposed approach significantly outperforms the existing approaches in terms of response time (up to four orders of magnitude). Moreover, we develop a prototype service that uses the SkySR query, and conduct a user test to evaluate its usefulness.
Traditional relational data interfaces require precise structured queries over potentially complex schemas. These rigid data retrieval mechanisms pose hurdles for non-expert users, who typically lack language expertise and are unfamiliar with the det
Graph-based data models allow for flexible data representation. In particular, semantic data based on RDF and OWL fuels use cases ranging from general knowledge graphs to domain specific knowledge in various technological or scientific domains. The f
The broadening adoption of machine learning in the enterprise is increasing the pressure for strict governance and cost-effective performance, in particular for the common and consequential steps of model storage and inference. The RDBMS provides a n
Arising user-centric graph applications such as route planning and personalized social network analysis have initiated a shift of paradigms in modern graph processing systems towards multi-query analysis, i.e., processing multiple graph queries in pa
We study the hardness of Approximate Query Processing (AQP) of various types of queries involving joins over multiple tables of possibly different sizes. In the case where the query result is a single value (e.g., COUNT, SUM, and COUNT(DISTINCT)), we