Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "Frequent pattern mining" wg kryterium: Temat


Wyświetlanie 1-3 z 3
Tytuł:
A Survey on Privacy Preserving Data Mining
Autorzy:
Bharanya, S.
Amudha, P.
Powiązania:
https://bibliotekanauki.pl/articles/1193548.pdf
Data publikacji:
2016
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
Data mining
Frequent pattern mining
Perturbation
Privacy-preserving data mining
Opis:
Privacy-preserving data mining has been considered widely because of the wide propagation of sensitive information over internet. A number of algorithmic techniques have been designed for privacy-preserving data mining that includes the state-of-the-art method. Privacy preserving data mining has become progressively popular because it allows sharing of confidential sensitive data for analysis purposes. It is important to maintain a ratio between privacy protection and knowledge discovery. To solve such problems many algorithms are proposed by various authors across the world. The main objective of this paper is to study various Privacy preserving data mining techniques and algorithms used for mining the item sets.
Źródło:
World Scientific News; 2016, 41; 68-75
2392-2192
Pojawia się w:
World Scientific News
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Customer’s Purchase Prediction Using Customer Segmentation Approach for Clustering of Categorical Data
Autorzy:
Singh, Juhi
Mittal, Mandeep
Powiązania:
https://bibliotekanauki.pl/articles/1841413.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
categorical data
clustering algorithm
frequent pattern mining
association rules
customer relationship management
Opis:
Traditional clustering algorithms which use distance between a pair of data points to calculate their similarity are not suitable for clustering of boolean and categorical attributes. In this paper, a modified clustering algorithm for categorical attributes is used for segmentation of customers. Each segment is then mined using frequent pattern mining algorithm in order to infer rules that helps in predicting customer’s next purchase. Generally, purchases of items are related to each other, for example, grocery items are frequently purchased together while electronic items are purchased together. Therefore, if the knowledge of purchase dependencies is available, then those items can be grouped together and attractive offers can be made for the customers which, in turn, increase overall profit of the organization. This work focuses on grouping of such items. Various experiments on real time database are implemented to evaluate the performance of proposed approach.
Źródło:
Management and Production Engineering Review; 2021, 12, 2; 57-64
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Negative feature selection algorithm for anomaly detection in real time
Autorzy:
Hryniów, K.
Dzieliński, A.
Powiązania:
https://bibliotekanauki.pl/articles/92969.pdf
Data publikacji:
2011
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
anomaly detection
feature selection
frequent pattern mining
neural networks
rule-based systems
Opis:
Anomaly detection methods are of common use in many fields, including databases and large computer systems. This article presents new algorithm based on negative feature selection, which can be used to find anomalies in real time. Proposed algorithm, called Negative Feature Selection algorithm (NegFS) can be also used as first step for preprocessing data analyzed by neural networks, rule-based systems or other anomaly detection tools, to speed up the process for large and very large datasets of different types.
Źródło:
Studia Informatica : systems and information technology; 2011, 1-2(15); 15-23
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies