C. de Maindreville and E. Simon, A production rule based approach to deductive databases, In Proc. of the Fourth Int. Conf. on Data Engineering, (Feb,1988) 234-241  Home/Search   Document Not in Database   Summary   Related Articles   Check

....[1] 18] The expert system shells, however, have one important drawback that both their styles of fuzzy reasoning and their semantics are not compatible with those of relational framework. Many advantages have been identified in conforming the styles of inference to those of the relational one [13][19] 21] The advantages include the exploitation of SQL in the reasoning without impedance mismatch [9] the optimization of rules with techniques well developed in the relational databases, and easy construction of trigger mechanism and integrity constraints thanks to the production rules. ....

....as a query to the databases. It may be a natural consequence that such an alternative entails a seamless integration of our framework into the relational databases. In other words, the design alternative can make all the approaches providing persistence to production systems also available to us [13][20] 17] 21] Another design alternative of our work is to enhance the semantic expressiveness of conventional production rule based languages by providing fuzzy match facility. As a uniform construct to handle fuzzy linguistic variables as well as fuzzy numbers, it enables users to describe the ....

C. de Maindreville and E. Simon, A production rule based approach to deductive databases, In Proc. of the Fourth Int. Conf. on Data Engineering, (Feb,1988) 234-241

....conditions. The languages, however, shows much difference from these two facilities both in semantic and syntax, which makes the integration difficult to achieve. Many advantages have been reported to be gained when conforming the styles of their rule processing to those of relational framework [15][20] 23] Some works such as [5] 18] 21] feature such attempts to implement relational production languages, relocating facts into the relational databases from working memory in discrimination networks [6] 8] 16] Currently, production languages such as OPS5 [6] and ECLPS [9] are being used to ....

....memory implementation of production languages. However, differently from such a main memory implementation, the structure of our information including facts is defined in a way to have the least semantic gap with relations. Since there are many database implementations of the production languages [15][18] 21] 23] our design criterion adopted in the structure may leave our information persistent by enabling our framework to fully exploit the implementations. We now begin this section by defining a fuzzy set. Definition 1 A fuzzy set F in a classical universe of discourse U is characterized ....

C. de Maindreville and E. Simon, A production rule based approach to deductive databases, In Proc. of the Fourth Int. Conf. on Data Engineering, (Feb, 1988) 234-241.

....on rule languages started with logic languages and have resulted in a comprehensive theoretical framework to study declarative query languages. Production languages for databases still do not have a theoretical framework even if some languages and systems have been developed, for instance, RDL1 [20], Heraclitus [35] and Starburst [26] In the following we introduce databases based on logic languages and we provide examples of both the families of rule languages. A deductive database (DB) can be seen as a set of sentences defining data (facts) or views (deductive rules) Facts are stored in ....

....the query language from the update language. However, the most interesting languages and systems are those that integrate the query and update languages, for example, Dynamic logic programming (DLP) 41] LDL [43] transaction logic programming (T R ) 14] Declarative Languages (DL) 3] and RDL1 [20]. Languages, providing integrated query and update facilities, can in turn be classified depending on whether updates are defined in the rule bodies (DLP, LDL and TR ) or in the rule heads (DL and RDL1) These two approaches were developed with different goals. The first family was developed to ....

C. de Maindreville and E. Simon. A Production Rule based approach to Deductive databases. In Proc. Fourth Int'l Conf. on Data Engineering, 1988.

....bases. One research effort in DBMS rule processing has been to extend the syntax of production rule languages with set oriented constructs and use more efficient set oriented DBMS query processing strategies to evaluate conditions and execute actions of rules. This research has been reported in [8, 9, 10, 15, 36, 37, 44]. Parallelism has also been used to improve the efficiency in executing rule actions as well as in evaluating conditions [2, 6, 16, 17, 18, 20, 24, 27, 34, 35, 39] Research reported in [2, 6, 18, 34, 35, 39] has investigated the execution of a number of rules in parallel, and the corresponding ....

.... and Etheredge devised a similar extension to SQL, namely, the Relational Production Language (RPL) it uses a variation of the Rete Network for a main memory implementation of a rule management system [10, 11] Finally, de Maindreville and Simon have proposed a production rule language, RDL1 [8], and examined an implementation that provides efficient execution [21] 3.2. Parallelism in Production Rule Execution In an effort to improve the execution efficiency of production rules, there has been research in using parallelism to solve the task of searching the database and identifying ....

de Maindreville, C., and Simon, E. A production rule-based approach to deductive databases. Proceedings of the Fourth International Conference on Data Engineering, Los Angeles, CA (1988).

....techniques that are also important to LDL include the unification of complex terms, the compile time analysis to detect unsafe queries, and the compiling of safe queries. These are discussed in [165, 166] 2.2. 7 RDL1 and RDL C Unlike LDL [108, 154] or other deductive database systems [155] RDL1 [32, 76] rules are not in clausal form in the style of PROLOG or DATALOG, but closer to forward chaining rule based languages like OPS5. Again, 31 the design goal is to integrate production rule language with a relational DBMS. A rule consists of a condition part which is any tuple relational calculus ....

....way of executing rule programs, it also means that all available techniques and tools for the analysis, transformation, and optimization of PrTN can be used on PCN. The reader interested in the details of PCN, including how to transform a rule program into and execute it on a PCN, is referred to [31, 32]. Another facility provided by RDL1 is a control language for annotating PCN with information of flow of control and the sequence of rule firing. For a complete and formal description of the language, see [30] 32 In summary, RDL1 is a powerful rule language that supports negations in conditions ....

Christophe de Maindreville and Eric Simon. A production rule based approach to deductive databases. In Intl. Conf. on Data Engineering, pages 234--241, 1988. 158

....systems and database management systems. Some work, such as [DE89,SLR88, Tzv88] focuses on using database technology to efficiently support OPS like production rules languages [BFKM85] Other work including ours focuses on extending database systems to include a production rules facility [Coh89, dMS88, Esw76, Han89, KDM88, MD89, RS89, SHP88, SJGP90]. Generally, production rules take the form when X then Y, where X is a triggering condition and Y is an action: whenever condition X is true, action Y is performed. Specific forms of such rules may be used in particular environments. Author s current address: Tandem Computers, 19333 Vallco ....

....existing proposals leave some of these issues unresolved or unclear, or suggest restrictive solutions. We provide a precise semantics that allows an easy understanding of rule behavior while remaining expressive and flexible. Most other proposals for production rules in database systems (e.g. [Coh89, dMS88,Esw76, MD89, SJGP90]) consider instance oriented rules: rules that are applied once for each data item satisfying the condition part of the rule. For example, one might define an instanceoriented rule that is applied once for each tuple inserted into the database. In contrast, we propose setoriented rules: rules ....

C. de Maindreville and E. Simon. A production rule based approach to deductive databases. In Proceedings of the Fourth International Conference on Data Engineering, pages 234--241, Los Angeles, California, February 1988.

....constraints or triggers, there is usually no concept of a fixpoint. It is important that the semantics of executing a sequence of production rules in a program, against the database, be well understood. There has been some research in understanding the semantics of rule execution in a DBMS [AiWH92, MaSi88, ZhHs90] but this research has not provided a declarative meaning for rule execution. There has also been research on providing a semantics for updates in a DBMS [AbSV90, AbVi90, AbVi91] but this research has had little impact on a semantics that can easily be implemented in a DBMS. The success in ....

....closer to the meaning commonly associated with rules that delete facts, from the perspective of a designer in a DBMS environment. This contrasts with their solution of equating deletions with negative conclusions in the heads of rules. The research most similar to our approach is described in [MaSi88, SiMa88]. They consider production rule languages that are extensions of logical query languages such as Datalog with updates in the head of the rules. They provide an operational and declarative semantics for stratified Datalog programs that have a sequence of updates in the heads of the rules. Their ....

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Maindreville, C. de and Simon, E. A production rule based approach to deductive databases. In Proceedings of the Fourth International Conference on Data Engineering, 1988.

....can be incrementally maintained as user defined priorities are altered. We also discuss how the proposed scheme can be extended to build a multi level hierarchical priority system. 1 Introduction Incorporation of production rules into database systems has recently received considerable attention [6, 7, 8, 11, 19, 21, 25, 26, 27, 30]. A central issue in production rule systems is conflict resolution [20, 14] Given that two or more rules are triggered, a conflict resolution mechanism determines which rule is considered first for execution. Some rule systems (for example, Postgres Current address: Computer Science ....

C. de Maindreville and E. Simon. A Production Rule Based Approach to Deductive Databases. In Proc. 4th IEEE International Conference on Data Engineering, pages 234--241, Los Angeles, February 1988.

....reason with large quantities of data. As the production rule base and the database grow larger, these programs have to access information stored on disk. Thus, for performance reasons, it is important that PS programs be implemented using database technology. Research in this area is reported in [DeEt88, MaSi88, RaSL88, SiMa88, SeLR88 and WiFi89]. Fortunately, the forward chaining PS paradigm has some similarities with processing in a database management system (DBMS) For example, triggers and integrity constraints are very important in DBMS research; they are activated in response to updates made to the database. Similarly, in the PS ....

Maindreville, C. de and Simon, E., A production rule based approach to deductive databases. In Proceedings of the Fourth International Conference on Data Engineering, 1988.

....of the rule system and illustrating how the extensibility features of Starburst facilitated its rapid development. Several other research efforts also consider production rules in database systems. Descriptions of a variety of rule languages and prototype systems appear in [Coh89, DE89, dMS88, Esw76, Han89, MD89, SLR88, SJGP90] among others. The most significant difference between our rule system and others is our focus on set orientation, whereby rules can be triggered by and process arbitrary sets of changes to the database. We believe this approach permits a flexible framework and ....

C. de Maindreville and E. Simon. A production rule based approach to deductive databases. In Proceedings of the Fourth International Conference on Data Engineering, pages 234--241, Los Angeles, California, February 1988.

....the selected rule s action is executed for all instantiations of the rule, rather than for only one instantiation as in the original recognize act cycle given above. Firing the selected rule for all instantiations in each phase rather than only one is sometimes known as firing rules to saturation [12]. The semantic and practical differences between firing single instantiations and firing rules to saturation are explored in RDL1, a production rule implementation of a deductive database system [12, 30] A related modification to the recognize act cycle is setoriented firing, in which the ....

.... instantiations in each phase rather than only one is sometimes known as firing rules to saturation [12] The semantic and practical differences between firing single instantiations and firing rules to saturation are explored in RDL1, a production rule implementation of a deductive database system [12, 30]. A related modification to the recognize act cycle is setoriented firing, in which the selected rule s action is executed once for the entire set of instantiations [21] Ariel and Starburst both use a form of set oriented firing; see Sections 4.1 and 4.5. In active database systems, where ....

C. de Maindreville and E. Simon. A production rule based approach to deductive databases. In Proceedings of the Fourth International Conference on Data Engineering, February 1988.

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