Abstract: A database management system for performing a graph query based on one or more graph views of a relational-graph database is disclosed. The database management system is configured to determine a plurality of graph views from the relational-graph database based on one or more previous graph queries of the relational-graph database to obtain a plurality of candidate graph views of the relational-graph database. Moreover, the database management system is configured to store a subset of the plurality of candidate graph views of the relational-graph database and perform a graph query of the relational-graph database based on the subset of the plurality of candidate graph views of the relational-graph database. By virtue of the selected subset of the plurality of candidate graph views from the relational-graph database, the database management system can increase the processing speed of graph queries.

Abstract: A database management system for performing a graph query based on one or more graph views of a relational-graph database is disclosed. The database management system is configured to determine a plurality of graph views of the relational-graph database based on one or more previous graph queries of the relational-graph database to obtain a plurality of candidate graph views of the relational-graph database. Moreover, the database management system is configured to store a subset of the plurality of candidate graph views of the relational-graph database and perform a graph query of the relational-graph database based on the subset of the plurality of candidate graph views of the relational-graph database. By means of the selected subset of the plurality of candidate graph views of the relational-graph database, the database management system advantageously allows increasing the processing speed of graph queries.

Abstract: A computer process, called VGRAM, improves the performance of these string search algorithms in computers by using a carefully chosen dictionary of variable-length grams based on their frequencies in the string collection. A dynamic programming algorithm for computing a tight lower bound on the number of common grams shared by two similar strings in order to improve query performance is disclosed. A method for automatically computing a dictionary of high-quality grams for a workload of queries. Improvement on query performance is achieved by these techniques by a cost-based quantitative approach to deciding good grams for approximate string queries. An approach for answering approximate queries efficiently based on discarding gram lists, and another is based on combining correlated lists. An indexing structure is reduced to a given amount of space, while retaining efficient query processing by using algorithms in a computer based on discarding gram lists and combining correlated lists.

Abstract: A computer process, called VGRAM, improves the performance of these string search algorithms in computers by using a carefully chosen dictionary of variable-length grams based on their frequencies in the string collection. A dynamic programming algorithm for computing a tight lower bound on the number of common grams shared by two similar strings in order to improve query performance is disclosed. A method for automatically computing a dictionary of high-quality grams for a workload of queries. Improvement on query performance is achieved by these techniques by a cost-based quantitative approach to deciding good grams for approximate string queries. An approach for answering approximate queries efficiently based on discarding gram lists, and another is based on combining correlated lists. An indexing structure is reduced to a given amount of space, while retaining efficient query processing by using algorithms in a computer based on discarding gram lists and combining correlated lists.