الفهرس | Only 14 pages are availabe for public view |
Abstract Skyline queries have received much attention throughout the past few years due to their importance in search space reduction as well as decision making through providing the users with data that best match their interest. The user can filter the interesting points only from a huge set of data. Unlike most aggregate functions which only get the best match based on one dimension, skyline can be applied on multiple dimensions. The user can select these dimensions based on the preference. Likewise, graph databases have become increasingly important within both application and research domains due to the growing volumes and connectedness of today’s data. Graph databases store data in the form of nodes and edges between nodes. This helps retrieve data easily, unlike the complications of multiple joins in relational databases. Computing skyline on graph database is not an easy operation. The proposed work in this thesis aims to augment graph databases with skyline queries. In addition, a new skyline operator has been implemented and added to perform more efficient queries in graph databases and make it easier to write skyline queries in graph databases. In this thesis, we adapt two skyline query processing algorithms; nested loops and divide-and-conquer to be used in graph databases |