A Methodology to develop process ontology from organizational guidelines written in natural language

2017
Gürbüz, Özge
Integrating ontologies with process modeling improves data representations and makes it easier to query, store and reuse processes at the semantics level. Therefore, in recent years, this topic has become increasingly popular. The studies in the literature have proposed methods for the integration process either to relate domain ontologies to process models or to transform process models to process ontologies. Another way to establish the integration between ontologies and process models is to develop process ontologies from organizational sources. Since most organizations have guidelines in natural language, it requires significant amount of time and effort to extract the roles, activities, information carriers, business rules, and relationships for process ontology development. In this thesis, a new Process Ontology Population (PrOnPo) methodology and tool is proposed that will automatically develop process ontology by extracting process information from organizational guidelines (regulations, procedures, directives and policies written in natural language). This approach will not only minimize the effort and time required for process ontology development, will also address the natural language ambiguity and provide an input for process modeling, hence improve the semantic quality of the business process models and their consistency with process ontology. As a part of this thesis work, two exploratory studies, a multiple case study and an experiment were performed in order to explore, generalize and validate the proposed approach. 

Suggestions

A binomial noised model for cluster validation
Toledano-Kitai, Dvora; Avros, Renata; Volkovich, Zeev; Weber, Gerhard Wilhelm; Yahalom, Orly (IOS Press, 2013-01-01)
Cluster validation is the task of estimating the quality of a given partition of a data set into clusters of similar objects. Normally, a clustering algorithm requires a desired number of clusters as a parameter. We consider the cluster validation problem of determining the optimal ("true") number of clusters. We adopt the stability testing approach, according to which, repeated applications of a given clustering algorithm provide similar results when the specified number of clusters is correct. To implemen...
An indexing technique for similarity-based fuzzy object-oriented data model
Yazıcı, Adnan; Koyuncu, M (2004-01-01)
Fuzzy object-oriented data model is a fuzzy logic-based extension to object-oriented database model, which permits uncertain data to be explicitly represented. One of the proposed fuzzy object-oriented database models based on similarity relations is the FOOD model. Several kinds of fuzziness are dealt with in the FOOD model, including fuzziness between object/class and class/superclass relations. The traditional index structures are inappropriate for the FOOD model for an efficient access to the objects wi...
An intelligent fuzzy object-oriented database framework for video database applications
Ozgur, Nezihe Burcu; KOYUNCU, Murat; Yazıcı, Adnan (Elsevier BV, 2009-08-01)
Video database applications call for flexible and powerful modeling and querying facilities, which require an integration or interaction between database and knowledge-based technologies. It is also necessary for many real life video database applications to incorporate uncertainty, which naturally occurs due to the complex and subjective semantic content of video data. In this study, firstly, we introduce a fuzzy conceptual data model to represent the semantic content of video data. For that purpose, UML (...
Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition
Buyuksahin, Umit Cavus; Ertekin Bolelli, Şeyda (Elsevier BV, 2019-10-07)
Many applications in different domains produce large amount of time series data. Making accurate forecasting is critical for many decision makers. Various time series forecasting methods exist that use linear and nonlinear models separately or combination of both. Studies show that combining of linear and nonlinear models can be effective to improve forecasting performance. However, some assumptions that those existing methods make, might restrict their performance in certain situations. We provide a new Au...
AN EFFICIENT DATABASE TRANSITIVE CLOSURE ALGORITHM
Toroslu, İsmail Hakkı; HENSCHEN, L (Springer Science and Business Media LLC, 1994-05-01)
The integration of logic rules and relational databases has recently emerged as an important technique for developing knowledge management systems. An important class of logic rules utilized by these systems is the so-called transitive closure rules, the processing of which requires the computation of the transitive closure of database relations referenced by these rules. This article presents a new algorithm suitable for computing the transitive closure of very large database relations. This algorithm proc...
Citation Formats
Ö. Gürbüz, “A Methodology to develop process ontology from organizational guidelines written in natural language,” Ph.D. - Doctoral Program, Middle East Technical University, 2017.