An improved database management system (DBMS) stores, retrieves and manipulates directed graph data structures in a relational database. Each directed graph data structure contains one or more records of data which are interconnected by pointers. Data is stored in the database in the form of two dimensional tables, also known as flat files. The improved DBMS defines a schema for each table in the database. The schema defines the name and data type of each column in a database table. In tables used to store directed graph data structures, at least one column will be defined as having a reference data type. Non-empty entries in that column are pointers to rows in a specified table. Directed graph data structures are stored in specified tables by storing each record of the directed graph in a distinct row of one of the specified tables, with references corresponding to interconnections between records being stored in reference data type columns. Portions of a directed graph are retrieved from the specified table, in accordance with a single specified query and then the query is automatically expanded by also retrieving additional portions of the tables which are referenced by the previously retrieved portions, thereby performing a transitive closure. The retrieved data is stored in a buffer as a list of rows, and then communicated to an application process. An interface program converts the list of rows stored in the buffer into a directed graph data structure.
Any existing transitive closure in a database can be found using a method based on standard 4th Generation Structured Query Language (SQL) without non-standard extensions to perform recursion analysis. There are no requirements to stay within a preset number of levels in the database to prevent breakdown as in previous known methods. The method represents each database as a graph and builds path and edge tables which are updated as data, that is verticies and edges, are added or deleted. Since this method uses instructions that are entirely within standard 4GL SQL, it can be used over multiple platforms as long as the platforms are 4GL SQL compliant.
Improved database structure is described in which the fields of each database record are divided into two classes, navigational and informational data. The data in the navigational fields is stored in a topological map which may be viewed as a tree structure or the merger of two or more such tree structures. The informational data is preferably stored in a conventional relational database. Each leaf node in the topological map specifies a unique record in the relational database.
A newly defined data type is added to a database management system. Information about a query component assisting in querying data belonging to the newly defined data type is registered along with data type information in a query component information. If the data type being queried is the newly added data type, the query component information is searched to find a query component for assisting queries to data belonging to the particular data type. The matching query component is activated and a screen is displayed to input information needed to query data belonging to the data type. The information is input and a query statement is generated using the inputted information. The generated query statement is issued to the database management system and query results are obtained.
A newly defined data type is added to a database management system. Information about a query component assisting in querying data belonging to the newly defined data type is registered along with data type information in a query component information. If the data type being queried is the newly added data type, the query component information is searched to find a query component for assisting queries to data belonging to the particular data type. The matching query component is activated and a screen is displayed to input information needed to the query data belonging to the data type. The information is input and a query statement is generated using the inputted information. The generated query statement is issued to the database management system and query results are obtained.
An information-retrieval system comprises a workstation having an input device and an output device. The workstation is connected to an intelligent interface which in turn is connected to a date base memory system. The interface comprises a lexical analyzer, a semantic associator, a query code generator and an output formatter. The user inputs a query as an ordered stream of characters in natural language (e.g., English or German). The lexical analyzer partitions the character stream into sections which are then compared with and matched against the contents of a look-up table held in a local memory and if a match is located, converted to a single token record for transmission to the Semantic Associator. Associator stores all the node/link records and those corresponding to the received tokens are identified to form the initial starting point of the conceptual graph which is operated on by a Steiner Marcher within Associator in order to identify the Steiner Tree which is then interpreted link by link by the code generator. The query in coded form is then delivered to the DBMS which delivers its consequential output to the formatter which formats the answer to the query for presentation to the user on the display device.
