Linguistic Summaries of Graph Databases in Customer Relationship Management (CRM)
Ładowanie...
Data
2019
Autorzy
Tytuł czasopisma
ISSN czasopisma
Tytuł tomu
Wydawca
Wydawnictwo Politechniki Łódzkiej
Lodz University of Technology Press
Lodz University of Technology Press
Abstrakt
The paper concentrates on data models that differ from the traditional relational one by Codd (1970). In particular, we are interested in processing graph databases (graph datasets) without any pre-configured structure, in which graph nodes may represent different objects and graph edges – relations between them. In this approach, the linguistic summarization methods for graph datasets are introduced, and differences for these methods with respect to traditional relational approach are
shown, commented and improved in comparison to the preceding proposition (Strobin, Niewiadomski, 2016). The novelty of the paper is mostly the new form for summaries: Multi-Subject linguistic summaries of graph databases, previously introduced for relational databases (Superson, 2018).
Opis
Słowa kluczowe
graph data model, graph databases, linguistic summarization of graph datasets, customer relationship management, Neo4j, data mining, data, fuzzy representations of data, wykres modelu danych, grafowe bazy danych, lingwistyczne podsumowanie grafowych zbiorów danych, menedżer ds. relacji z klientam, Neo4j, eksploracja danych, dane, rozmyte reprezentacje danych
Cytowanie
Bartczak, M., & Niewiadomski, A. (2019). Linguistic Summaries of Graph Databases in Customer Relationship Management (CRM). Journal of Applied Computer
Science, 27(1), 7-26. https://doi.org/10.34658/jacs.2019.27.1