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Situation Awareness in Telecommunication Networks Using Topic Modeling
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Skövde Artificial Intelligence Lab (SAIL))ORCID-id: 0000-0001-6245-5850
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Skövde Artificial Intelligence Lab (SAIL))ORCID-id: 0000-0003-2949-4123
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Skövde Artificial Intelligence Lab (SAIL))ORCID-id: 0000-0003-2973-3112
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi. (Skövde Artificial Intelligence Lab (SAIL))ORCID-id: 0000-0001-7106-0025
2018 (engelsk)Inngår i: 2018 21st International Conference on Information Fusion, FUSION 2018, IEEE, 2018, s. 549-556Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

For an operator of wireless telecommunication networks to make timely interventions in the network before minor faults escalate into issues that can lead to substandard system performance, good situation awareness is of high importance. Due to the increasing complexity of such networks, as well as the explosion of traffic load, it has become necessary to aid human operators to reach a good level of situation awareness through the use of exploratory data analysis and information fusion techniques. However, to understand the results of such techniques is often cognitively challenging and time consuming. In this paper, we present how telecommunication operators can be aided in their data analysis and sense-making processes through the usage and visualization of topic modeling results. We present how topic modeling can be used to extract knowledge from base station counter readings and make design suggestions for how to visualize the analysis results to a telecommunication operator.

sted, utgiver, år, opplag, sider
IEEE, 2018. s. 549-556
Emneord [en]
Data handling, Data visualization, Information fusion, Design suggestions, Exploratory data analysis, Human operator, Information fusion techniques, Situation awareness, Telecommunication operators, Topic Modeling, Wireless telecommunications, Data mining
HSV kategori
Forskningsprogram
Skövde Artificial Intelligence Lab (SAIL); INF301 Data Science
Identifikatorer
URN: urn:nbn:se:his:diva-16297DOI: 10.23919/ICIF.2018.8455529Scopus ID: 2-s2.0-85054066646ISBN: 978-0-9964527-6-2 (digital)ISBN: 978-0-9964527-7-9 (digital)ISBN: 978-1-5386-4330-3 (tryckt)OAI: oai:DiVA.org:his-16297DiVA, id: diva2:1256012
Konferanse
FUSION 2018 21st International Conference on Information Fusion, 10-13 July 2018, Cambridge, United Kingdom
Tilgjengelig fra: 2018-10-15 Laget: 2018-10-15 Sist oppdatert: 2019-02-08bibliografisk kontrollert

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