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Jul 23, 2021 · This paper is concentrated on the applications of main data mining tools, methods, models and technologies for solving the basic tasks of data processing for telecommunication industry.
- Nataliia Kuznietsova, Peter Bidyuk, Maryna Kuznietsova
- 2021
This paper focuses on facilitating state-of-the-art applications of big data analytics (BDA) architectures and infrastructures to telecommunications (telecom) industrial sector. Telecom companies are dealing with terabytes to petabytes of data on a daily basis.
Thus, the scalability of data mining methods is a key concern. A second issue is that telecommunication data is often in the form of transactions/events and is not at the proper semantic level for data mining. For example, one typically wants to mine call detail data at the customer (i.e., phone-
- 337KB
- 6
Oct 20, 2023 · For this reason, companies need to invest in robust and scalable data integration solutions. It enables to standardize data and make it more accessible and analytics-friendly. Disparate and siloed data sources. The telecom industry operates extensively, encompassing various regions and countries.
Jul 24, 2023 · In this article, we want to share our piece of knowledge about data mining in the telecom industry. We'll also explore how adopting data mining can benefit your business and empower you with valuable information, so keep reading to learn more. Three main types of data in telecom and why mining them. Let’s start with data types.
Aug 30, 2015 · Scalable clustering research faces scalability problems for computing time and memory requirements, including DIGNET [70] and BIRCH [71]. (v) High dimensionality data clustering methods are designed to handle data with hundreds of attributes, including DFT [72] and MAFIA [73].
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Jan 28, 2016 · Mining big data faces a lot of challenges including scalability, speed, heterogeneity, accuracy, provenance and privacy. In telecommunication industry, mining big data is like a mining for...
