Naslov
A Different Approach for Clique and Household Analysis in Synthetic Telecom Data Using Propositional Logic

Autori
Skansi, Sandro ; Šekrst, Kristina ; Kardum, Marko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO) / Koričić, Marko et al. - Opatija : Rijeka : Zagreb : IEEE Explore, 2020, 1286-1289

Skup
43rd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2020)

Mjesto i datum
Opatija, Hrvatska, 28.09.2020. - 02.10.2020

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Clique Detection ; SAT Solving ; DPLL ; Household Identification ; SAT encodings ; Telecom Data Analysis

Sažetak
In this paper we propose an non-machine learning artificial intelligence (AI) based approach for telecom data analysis, with a special focus on clique detection. Clique detection can be used to identify households, which is a major challenge in telecom data analysis and predictive analytics. Our approach does not use any form of machine learning, but another type of algorithm: satisfiability for propositional logic. This is a neglected approach in modern AI, and we aim to demonstrate that for certain tasks, it may be a good alternative to machine learning-based approaches. We have used a simple DPLL satisfiability solver over an artificially generated telecom dataset (due to GDPR regulations), but our approach can be implemented on any telecom data by following the SAT encoding we have developed, and the DPLL solver can be substituted by a more advanced alternative such as CDCL. This paper extends the method presented in [1] for banking logs to data containing caller information, and proposes a more efficient encoding.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Filozofija

POVEZANOST RADA