Knowledge Engineering for Hybrid Deductive Databases
Modern knowledge base systems frequently need to combine a collection of databases in different formats: e.g., relational databases, XML databases, rule bases, ontologies, etc. In the deductive database system DDBASE, we can manage these different formats of knowledge and reason about them. Even the file systems on different computers can be part of the knowledge base. Often, it is necessary to handle different versions of a knowledge base. E.g., we might want to find out common parts or differences of two versions of a relational database. We will examine the use of abstractions of rule bases by predicate dependency and rule predicate graphs. Also the proof trees of derived atoms can help to compare different versions of a rule base. Moreover, it might be possible to have derivations joining rules with other formalisms of knowledge representation. Ontologies have shown their benefits in many applications of intelligent systems, and there have been many proposals for rule languages compatible with the semantic web stack, e.g., SWRL, the semantic web rule language. Recently, ontologies are used in hybrid systems for specifying the provenance of the different components.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Enhance Reasoning for Large Language Models in the Game Werewolf
This paper presents an innovative framework that integrates Large Language Models (LLMs) with an external Thinker module to enhance the reasoning capabilities of LLM-based agents. Unlike augmenting LLMs with prompt engin…
Prompt EngineeringImproving the Deductive System DES with Persistence by Using SQL DBMS's
This work presents how persistent predicates have been included in the in-memory deductive system DES by relying on external SQL database management systems. We introduce how persistence is supported from a user-point of…
ManagementA Hybrid Rule Based Fuzzy-Neural Expert System For Passive Network Monitoring
An enhanced approach for network monitoring is to create a network monitoring tool that has artificial intelligence characteristics. There are a number of approaches available. One such approach is by the use of a combin…
Automatic deductive coding in discourse analysis: an application of large language models in learning analytics
Deductive coding is a common discourse analysis method widely used by learning science and learning analytics researchers for understanding teaching and learning interactions. It often requires researchers to manually la…
Feature EngineeringLanguage ModelingLanguage ModellingLarge Language Model+3Software Engineering Methods For AI-Driven Deductive Legal Reasoning
The recent proliferation of generative artificial intelligence (AI) technologies such as pre-trained large language models (LLMs) has opened up new frontiers in computational law. An exciting area of development is the u…
Formal LogicLegal Reasoning