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doctoral thesis
User profile for provisioning information and communication services based on user influence
Smailović, Vanja (2016)
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Telecommunications

Cite this document

Smailović, V. (2016). User profile for provisioning information and communication services based on user influence (Doctoral thesis). Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:595948

Smailović, Vanja. "User profile for provisioning information and communication services based on user influence." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. https://urn.nsk.hr/urn:nbn:hr:168:595948

Smailović, Vanja. "User profile for provisioning information and communication services based on user influence." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. https://urn.nsk.hr/urn:nbn:hr:168:595948

Smailović, V. (2016). 'User profile for provisioning information and communication services based on user influence', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 04 July 2020, https://urn.nsk.hr/urn:nbn:hr:168:595948

Smailović V. User profile for provisioning information and communication services based on user influence [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2016 [cited 2020 July 04] Available at: https://urn.nsk.hr/urn:nbn:hr:168:595948

V. Smailović, "User profile for provisioning information and communication services based on user influence", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2016. Available at: https://urn.nsk.hr/urn:nbn:hr:168:595948

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Metadata
TitleUser profile for provisioning information and communication services based on user influence
Title (croatian)Korisnički profič za pružanje informacijskih i komunikacijskih usluga zasnovanih na utjecajnosti korisnika
AuthorVanja Smailović
MentorVedran Podobnik (mentor)
Committee memberVedran Podobnik (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Telecommunications)
Zagreb
Defense date and country2016, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Telecommunications and Informatics
Universal decimal classification
(UDC)		621.3
APPLIED SCIENCES. MEDICINE. TECHNOLOGY
Electrical engineering
Abstract
User profile enables collection, storage and interpretation of user data, which in turn enables analysis and reasoning upon such data. It is an ongoing research challenge to utilize vast amounts of available multi-source, heterogeneous user data with the goal of identifying key, socially influential actors for provisioning information and communication services. Novel approach to solving this challenge includes several steps, as proposed in this thesis. First, a novel user profiling method is proposed in order to efficiently acquire, aggregate and consolidate user data from two data-sources – the telecom-operator's network and Interned-based social networks. Second, a novel user profile model is developed for inference upon such user data. Third, improved algorithms for reasoning upon profile data are proposed, resulting in new knowledge about each user – their social influence. The proposed algorithm improvements in calculating social influence are statistically validated and evaluated through a real-world experiment. Substantial difference in results between the two data-sources is statistically proven, explaining their synergy once utilized together. Finally, out of several algorithm proposals stemming from the Limited Recursive Algorithm (LRA), the variant with Sample-Literature-Optimal Posting Frequency factor (SLOF) demonstrates significant improvement. For example, churn-prevention, prioritizing customer care, digital advertising and disease-tracking algorithms could all benefit from the SLOF algorithm as exemplified in the thesis.
Abstract (croatian)
Korisnički profil omogućava prikupljanje, pohranu i interpretaciju korisničkih podataka, što zauzvrat omogućava analizu i zaključivanje iz tih podataka. Iskoristiti veliku količinu heterogenih podataka iz više izvora, s ciljem određivanja ključnih, društveno utjecajnih pojedinaca u informacijskim i komunikacijskim uslugama, aktualan je istraživački izazov. Nov pristup rješavanju ovog izazova, predložen u disertaciji, sastoji se od nekoliko koraka. Prvo, predložena metoda za profiliranje korisnika omogućuje učinkovito dohvaćanje, agregaciju i konsolidaciju korisničkih podataka iz dva izvora – telekom-operatorske mreže i usluga za društveno umrežavanje. Drugo, razvijen je model korisničkog profila za automatsko zaključivanje iz tih korisničkih podataka. Treće, predložen je nadograđeni algoritam za zaključivanje iz korisničkih podataka koji rezultira novim znanjem o svakom korisniku – društvenom utjecajnošću tog korisnika. Predložene algoritamske nadogradnje u izračunu društvene utjecajnosti statistički su validirane i ocjenjene kroz eksperiment sa stvarnim korisničkim podacima. Značajna razlika u rezultatima iz dva izvora podataka statistički je dokazana te objašnjena njihovom sinergijom kada se koriste istovremeno. Među predloženim algoritamskim nadogradnjama zasnovanim na "Limited Recursive Algorithm" (LRA), algoritam "Sample-Literature-Optimal Posting Frequency factor" (SLOF) pokazuje značajno poboljšanje. Primjerice, SLOF ima primjenu u poboljšanom sprječavanju odljeva pretplatnika, prioretizaciji usluge, digitalnom oglašavanju i algoritamskom praćenju zaraza.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:168:595948
Study programmeTitle: Electrical Engineering and Computing
Study programme type: university
Study level: postgraduate
Academic / professional title: Doktor znanosti elektrotehnike i računarstva (Doktor znanosti elektrotehnike i računarstva)
Type of resourceText
Extent153 str. ; 30 cm.
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
RepositoryFER Repository
Created on2019-04-11 15:49:02

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