@inproceedings{,
    author = {Gidey, Habtom Kahsay; Kesseler, Mario; Stangl, Patrick; Hillmann, Peter; Karcher, Andreas},
    title = {A Document-based Knowledge Discovery with Microservices Architecture},
    editor = {},
    booktitle = {International Symposium for Production Research},
    series = {},
    journal = {},
    address = {},
    publisher = {},
    edition = {},
    year = {2022},
    isbn = {},
    volume = {},
    number =  {},
    pages = {},
    url = {},
    doi = {},
    keywords = {knowledge discovery ; ontology ; microservices ; servitization},
    abstract = {The first step towards digitalization within organizations lies
in digitization - the conversion of analog data into digitally stored data.
This basic step is the prerequisite for all following activities like the digi-
talization of processes or the servitization of products or offerings. How-
ever, digitization itself often leads to “data-rich” but “knowledge-poor”
material. Knowledge discovery and knowledge extraction as approaches
try to increase the usefulness of digitized data.
In this paper, we point out the key challenges in the context of knowledge
discovery and present an approach to addressing these using a microser-
vices architecture. Our solution led to a conceptual design focusing on
keyword extraction, similarity calculation of documents, database queries
in natural language, and programming language independent provision
of the extracted information. In addition, the conceptual design provides
referential design guidelines for integrating processes and applications
for semi-automatic learning, editing, and visualization of ontologies. The
concept also uses a microservices architecture to address non-functional
requirements, such as scalability and resilience. The evaluation of the
specified requirements is performed using a demonstrator that imple-
ments the concept. Furthermore, this modern approach is used in the
German patent office in an extended version.},
    note = {},
    institution = {Universität der Bundeswehr München, Fakultät für Informatik, INF 4 - Institut für Angewandte Informatik, Professur: Karcher, Andreas},
    
    
}