Author:
Diana Gorea
Affiliation:
Faculty of Computer Science, University ”Al. I. Cuza”, Romania
Keyword(s):
Prediction model composition, PMML, online scoring, web services, XML.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Cloud Computing
;
Communication and Software Technologies and Architectures
;
Data Engineering
;
Data Warehouses and Data Mining
;
e-Business
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge Management
;
Knowledge Representation
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Semantic Web Technologies
;
Services Science
;
Society, e-Business and e-Government
;
Software Agents and Internet Computing
;
Symbolic Systems
;
Web Information Systems and Technologies
Abstract:
The paper presents a general context in which composition of prediction models can be achieved within the boundaries of an online scoring system called DeVisa. The system provides its functionality via web services and stores the prediction models represented in PMML in a native XML database. A language called PMQL is defined, whose purpose is to process the PMML models and to express consumers’ goals and the answers to the goals. The composition of prediction models can occur either implicitly within the process of online scoring, or explicitly, in which the consumer builds or trains a new model based on the existing ones in the DeVisa repository. The main scenarios that involve composition are adapted to the types of composition allowed in the PMML specification, i.e sequencing and selection.