Joint Usage of Frames and the Topological Functioning Model for Domain Knowledge Presentation and Analysis

Nazaruks, Vladislavs; Osis, Jānis

doi:10.5220/0006388903790390

Cited by 7 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The final step of the transformations is generation of source code for selected platforms. The TFM is embedded into a knowledge frame system [3], [4] for keeping and managing results of the text processing. The aim is to gain from an inferring mechanism and flexibility of the knowledge base as well as to discover conflicts in knowledge, manage synonyms, and infer new knowledge from the existing one.…”

Section: Introductionmentioning

confidence: 99%

Extracting TFM Core Elements From Use Case Scenarios by Processing Structure and Text in Natural Language

Nazaruka

Osis

Gribermane

2019

Applied Computer Systems

Self Cite

View full text Add to dashboard Cite

Extracting core elements of Topological Functioning Model (TFM) from use case scenarios requires processing of both structure and natural language constructs in use case step descriptions. The processing steps are discussed in the present paper. Analysis of natural language constructs is based on outcomes provided by Stanford CoreNLP. Stanford CoreNLP is the Natural Language Processing pipeline that allows analysing text at paragraph, sentence and word levels. The proposed technique allows extracting actions, objects, results, preconditions, post-conditions and executors of the functional features, as well as cause-effect relations between them. However, accuracy of it is dependent on the used language constructs and accuracy of specification of event flows. The analysis of the results allows concluding that even use case specifications require the use of rigor, or even uniform, structure of paths and sentences as well as awareness of the possible parsing errors.

show abstract

Section: Introductionmentioning

confidence: 99%

Extracting TFM Core Elements From Use Case Scenarios by Processing Structure and Text in Natural Language

Nazaruka

Osis

Gribermane

2019

Applied Computer Systems

Self Cite

View full text Add to dashboard Cite

show abstract

“…Other elements may be generated from these ones. Artefacts, i.e., analytical diagrams, use all the elements presented [7].…”

Section: Refinement Of Tfm Element Definitionsmentioning

confidence: 99%

“…The paper is a revised and extended version of [7] focused on a more exhaustive explanation of a decision on choosing the knowledge representation format and demonstration of manually filled in and generated information in frame instances.…”

mentioning

confidence: 99%

The Knowledge Frame System based on Principles of Topological Functioning Model

Nazaruks

2017

Applied Computer Systems

Self Cite

View full text Add to dashboard Cite

-Understanding of domain phenomena and their interrelations is necessary for successful software development. The knowledge frame system based on principles of Topological Functioning Modelling (TFM) can be used for this purpose at the Computation Independent level within Model Driven Development. Research on knowledge formats showed that inferring in the closed world paradigm and similarity to the object-oriented paradigm made frames an attractive candidate to the knowledge representation format. Frames can hold information necessary for generation of the TFM. The knowledge system based on the principles of the TFM does not allow inferring ambiguous facts and leads to the more complete discovery of knowledge.

show abstract

Using Stanford CoreNLP Capabilities for Semantic Information Extraction from Textual Descriptions

Nazaruka

Osis

Griberman

2020

Communications in Computer and Information Science

View full text Add to dashboard Cite

Joint Usage of Frames and the Topological Functioning Model for Domain Knowledge Presentation and Analysis

Cited by 7 publications

References 0 publications

Extracting TFM Core Elements From Use Case Scenarios by Processing Structure and Text in Natural Language

Extracting TFM Core Elements From Use Case Scenarios by Processing Structure and Text in Natural Language

The Knowledge Frame System based on Principles of Topological Functioning Model

Using Stanford CoreNLP Capabilities for Semantic Information Extraction from Textual Descriptions

Contact Info

Product

Resources

About