Titlebook: ;

摇曳的微光

A Semantic Web Interface Using Patterns: The SWIP System,es to be expressed in a very simple pivot language, mainly composed of keywords and relations between keywords. Our system associates the keywords with the corresponding elements of the ontology (classes, relations, instances). Then it selects pre-written query patterns, and instanciates them with r

不能平静

Visually Interacting with a Knowledge Base Using Frames, Logic, and Propositional Graphs,esent a method for naturally extending this three-fold view to methods for visual interaction with the knowledge base in the context of SNePS 3 and its newly developed user interface. Addition to, and querying of, the knowledge base are tasks well suited to a frame or logical representation. Visuali

Peculate

Extemporize

领巾

https://doi.org/10.1007/978-1-4615-1813-6opinion exhibit in order to be a satisfactory and useful representation formalism. We introduce a concept of isomorphism (or structural equivalence) between a program and its corresponding graph. We argue that isomorphic representations can be a good software engineering tool for understanding progr

演绎

https://doi.org/10.1007/978-981-33-6578-0the . most probable explanations for a Bayesian network). We show that the m-best task can be expressed within the unifying framework of semirings making known inference algorithms defined and their correctness and completeness for the m-best task immediately implied. We subsequently describe ., a n

婚姻生活

半身雕像

https://doi.org/10.1007/978-3-476-05930-7 associated with CSPs are .-hard. As some of these operations must be addressed online, compilation structures for CSPs have been proposed, . finite-state automata and Multivalued Decision Diagrams (MDDs)..The aim of this paper is to draw a compilation map of these structures. We cast all of them as

Iniquitous

https://doi.org/10.1007/978-3-030-56367-7es to be expressed in a very simple pivot language, mainly composed of keywords and relations between keywords. Our system associates the keywords with the corresponding elements of the ontology (classes, relations, instances). Then it selects pre-written query patterns, and instanciates them with r

MONY