Extracting term units and fact units from existing databases using the Knowledge Discovery Metamodel

Normantas, Kestutis; Vasilecas, Olegas

doi:10.1177/0165551514526336

Cited by 4 publications

(4 citation statements)

References 19 publications

(20 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If a model is highly abstract or significantly different from a source text, model extraction typically requires a model-to-model (M2M) transformation to be combined with a text-to-model (T2M) transformation [8] [13]. This is undesirable when designing a model extraction tool to be extensible, because the M2M transformation is an additional code block to modify.…”

Section: Dblmodeller Approachmentioning

confidence: 99%

Towards Platform Independent Database Modelling in Enterprise Systems

Ellison

Călinescu

Paige

2016

Software Technologies: Applications and Foundations

View full text Add to dashboard Cite

Abstract. Enterprise software systems are prevalent in many organisations, typically they are data-intensive and manage customer, sales, or other important data. When an enterprise system needs to be modernised or migrated (e.g. to the cloud) it is necessary to understand the structure of this data and how it is used. We have developed a toolsupported approach to model database structure, query patterns, and growth patterns. Compared to existing work, our tool offers increased system support and extensibility which is vital for use in industry. Standardisation and platform independence is ensured by producing models conforming to the Knowledge Discovery Metamodel and Software Metrics Metamodel.

show abstract

Section: Dblmodeller Approachmentioning

confidence: 99%

Towards Platform Independent Database Modelling in Enterprise Systems

Ellison

Călinescu

Paige

2016

Software Technologies: Applications and Foundations

View full text Add to dashboard Cite

show abstract

“…Other key approaches in the field of database modernisation and migration include Minimal Schema Extraction [62] and the business knowledge discovery framework from Normantas and Vasilecas [63]. The latter is a modelbased framework for discovering terms and facts from a database.…”

Section: Related Workmentioning

confidence: 99%

“…The existing approaches for extracting KDM models from SQL use an intermediate ASTM-based model [10,63]. The Abstract Syntax Tree Metamodel is an ADM metamodel [65] which is used to standardise the syntax tree produced from the source code.…”

Section: Related Workmentioning

confidence: 99%

Evaluating cloud database migration options using workload models

2018

View full text Add to dashboard Cite

A key challenge in porting enterprise software systems to the cloud is the migration of their database. Choosing a cloud provider and service option (e.g., a database-as-a-service or a manually configured set of virtual machines) typically requires the estimation of the cost and migration duration for each considered option. Many organisations also require this information for budgeting and planning purposes. Existing cloud migration research focuses on the software components, and therefore does not address this need. We introduce a two-stage approach which accurately estimates the migration cost, migration duration and cloud running costs of relational databases. The first stage of our approach obtains workload and structure models of the database to be migrated from database logs and the database schema. The second stage performs a discrete-event simulation using these models to obtain the cost and duration estimates. We implemented software tools that automate both stages of our approach. An extensive evaluation compares the estimates from our approach against results from real-world cloud database migrations.

show abstract

“…The basic principle of this approach is: Rules build on facts, and facts build on terms (Ross, 2003, p. 165). The basic terms are first defined, on the basis of which facts are created, followed by business rules (Normantas & Vasilecas, 2014).…”

Section: Business Rulesmentioning

confidence: 99%

Business Rules Mining Using GUHA Method for the Personalization of Commercial Offers

Vojíř¹,

Smutný²

2017

View full text Add to dashboard Cite

A shift from mass to personalized marketing, and thus also to personalized offers, brings firms an advantage for building customer relationships. The article introduces an artefact in the form of a method for creating personalized offers, focused on companies engaged in e-commerce. This method is based on mining association rules using the GUHA method. The association rules are converted into business rules and then combined with other manually defined business rules. The application of the method in practice is illustrated on customers' data from the e-shop of a company doing business in navigation systems, for the purpose of selecting personalized offers for an e-mailing campaign. The practical illustration uses a combination of the data mining system LISp-Miner and the business rule system JBoss Drools, which are freely available tools. The advantages and limitations of the proposed method, in connection with creating personalized marketing strategies in e-commerce, are discussed. The purpose of this practically oriented article is to address marketing and account managers and the issues connected with the personalization of marketing activities.

show abstract

Extracting term units and fact units from existing databases using the Knowledge Discovery Metamodel

Cited by 4 publications

References 19 publications

Towards Platform Independent Database Modelling in Enterprise Systems

Towards Platform Independent Database Modelling in Enterprise Systems

Evaluating cloud database migration options using workload models

Business Rules Mining Using GUHA Method for the Personalization of Commercial Offers

Contact Info

Product

Resources

About