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Books and Theses
- 2014
[b1]Anton Borg:
On Descriptive and Predictive Models for Serial Crime Analysis. Blekinge Institute of Technology, Sweden, 2014
Journal Articles
- 2022
- [j12]Christoffer Åleskog
, Håkan Grahn, Anton Borg:
Recent Developments in Low-Power AI Accelerators: A Survey. Algorithms 15(11): 419 (2022) - [j11]Mahwish Anwar, Lars Lundberg, Anton Borg:
Improving anomaly detection in SCADA network communication with attribute extension. Energy Inform. 5 (2022) - [j10]Anton Borg, Martin Svensson:
All Burglaries Are Not the Same: Predicting Near-Repeat Burglaries in Cities Using Modus Operandi. ISPRS Int. J. Geo Inf. 11(3): 160 (2022) - 2021
- [j9]Anton Borg, Martin Boldt, Oliver Rosander, Jim Ahlstrand:
E-mail classification with machine learning and word embeddings for improved customer support. Neural Comput. Appl. 33(6): 1881-1902 (2021) - [j8]Martin Boldt, Selim Ickin, Anton Borg, Valentin Kulyk, Jörgen Gustafsson:
Alarm Prediction in Cellular Base Stations Using Data-Driven Methods. IEEE Trans. Netw. Serv. Manag. 18(2): 1925-1933 (2021) - 2020
- [j7]Anton Borg, Martin Boldt:
Using VADER sentiment and SVM for predicting customer response sentiment. Expert Syst. Appl. 162: 113746 (2020) - [j6]Martin Boldt, Anton Borg, Selim Ickin, Jörgen Gustafsson:
Anomaly detection of event sequences using multiple temporal resolutions and Markov chains. Knowl. Inf. Syst. 62(2): 669-686 (2020) - 2018
- [j5]Martin Boldt, Anton Borg, Martin Svensson, Jonas Hildeby:
Predicting burglars' risk exposure and level of pre-crime preparation using crime scene data. Intell. Data Anal. 22(1): 167-190 (2018) - 2016
- [j4]Fredrik Erlandsson, Piotr Bródka, Anton Borg, Henric Johnson:
Finding Influential Users in Social Media Using Association Rule Learning. Entropy 18(5): 164 (2016) - [j3]Martin Boldt, Anton Borg:
Evaluating Temporal Analysis Methods Using Residential Burglary Data. ISPRS Int. J. Geo Inf. 5(9): 148 (2016) - [j2]Anton Borg, Martin Boldt:
Clustering Residential Burglaries Using Modus Operandi and Spatiotemporal Information. Int. J. Inf. Technol. Decis. Mak. 15(1): 23-42 (2016) - 2014
- [j1]Anton Borg, Martin Boldt, Niklas Lavesson, Ulf Melander, Veselka Boeva:
Detecting serial residential burglaries using clustering. Expert Syst. Appl. 41(11): 5252-5266 (2014)
Conference and Workshop Papers
- 2024
- [c20]Christoffer Åleskog, Håkan Grahn, Anton Borg:
A Comparative Study on Simulation Frameworks for AI Accelerator Evaluation. IPDPS (Workshops) 2024: 321-328 - [c19]Kenneth Lewenhagen, Martin Boldt, Anton Borg:
Automated Generation of CCTV Camera Coverage Areas for Smart Cities Using Line-of-Sight Analysis. ISCC 2024: 1-6 - 2023
- [c18]Jim Ahlstrand, Martin Boldt, Anton Borg, Håkan Grahn:
Preliminary Results on the use of Artificial Intelligence for Managing Customer Life Cycles. SAIS 2023: 68-76 - 2021
- [c17]Anton Borg, Jim Ahlstrand:
Detecting Non-routine Customer Support E-Mails. ICEIS (1) 2021: 387-394 - [c16]Mahwish Anwar, Anton Borg, Lars Lundberg:
A Comparison of Unsupervised Learning Algorithms for Intrusion Detection in IEC 104 SCADA Protocol. ICMLC 2021: 1-8 - 2020
- [c15]Anton Borg, Jim Ahlstrand, Martin Boldt:
Improving Corporate Support by Predicting Customer e-Mail Response Time: Experimental Evaluation and a Practical Use Case. ICEIS (Revised Selected Papers) 2020: 100-121 - [c14]Anton Borg, Jim Ahlstrand, Martin Boldt:
Predicting e-Mail Response Time in Corporate Customer Support. ICEIS (1) 2020: 305-314 - 2019
- [c13]Anton Borg, Martin Boldt, Johan Svensson:
Using Conformal Prediction for Multi-label Document Classification in e-Mail Support Systems. IEA/AIE 2019: 308-322 - 2018
- [c12]Martin Boldt, Veselka Boeva, Anton Borg:
Multi-Expert Estimations of Burglars' Risk Exposure and Level of Pre-Crime Preparation Using Coded Crime Scene Data: Work in Progress. EISIC 2018: 77-80 - 2017
- [c11]Fredrik Erlandsson, Piotr Bródka, Anton Borg:
Seed Selection for Information Cascade in Multilayer Networks. COMPLEX NETWORKS 2017: 426-436 - [c10]Anton Borg, Martin Boldt, Johan Eliasson:
Detecting Crime Series Based on Route Estimation and Behavioral Similarity. EISIC 2017: 1-8 - [c9]Martin Boldt, Anton Borg:
A Statistical Method for Detecting Significant Temporal Hotspots Using LISA Statistics. EISIC 2017: 123-126 - [c8]Martin Boldt, Veselka Boeva, Anton Borg:
Multi-expert estimations of burglars' risk exposure and level of pre-crime preparation based on crime scene data. SAIS 2017: 137:004 - 2016
- [c7]Fredrik Erlandsson, Anton Borg, Henric Johnson, Piotr Bródka:
Predicting User Participation in Social Media. NetSci-X 2016: 126-135 - 2015
- [c6]Erik Johansson, Christoffer Gahlin, Anton Borg:
Crime Hotspots: An Evaluation of the KDE Spatial Mapping Technique. EISIC 2015: 69-74 - 2013
- [c5]Anton Borg, Niklas Lavesson, Veselka Boeva:
Comparison of Clustering Approaches for Gene Expression Data. SCAI 2013: 55-64 - 2012
- [c4]Anton Borg, Niklas Lavesson:
E-mail Classification Using Social Network Information. ARES 2012: 168-173 - 2011
- [c3]Anton Borg, Martin Boldt, Niklas Lavesson:
Informed Software Installation Through License Agreement Categorization. ISSA 2011 - [c2]Anton Borg, Martin Boldt, Bengt Carlsson:
Simulating Malicious Users in a Software Reputation System. STA 2011: 147-156 - 2010
- [c1]Martin Boldt, Anton Borg, Bengt Carlsson:
On the Simulation of a Software Reputation System. ARES 2010: 333-340
Editorship
- 2023
- [e1]Håkan Grahn, Anton Borg, Martin Boldt:
35th Annual Workshop of the Swedish Artificial Intelligence Society, SAIS 2023, Karlskrona, Sweden, June 12-13, 2023. Linköping Electronic Conference Proceedings 199, Linköping University Electronic Press 2023, ISBN 978-91-8075-274-9 [contents]
Informal and Other Publications
- 2024
- [i3]Anton Borg, Per Lingvall, Martin Svensson:
Hierarchical Delay Attribution Classification using Unstructured Text in Train Management Systems. CoRR abs/2402.04108 (2024) - 2017
- [i2]Fredrik Erlandsson, Piotr Bródka, Anton Borg:
Seed selection for information cascade in multilayer networks. CoRR abs/1710.04391 (2017) - 2016
- [i1]Fredrik Erlandsson, Piotr Bródka, Anton Borg, Henric Johnson:
Finding Influential Users in Social Media Using Association Rule Learning. CoRR abs/1604.08075 (2016)
Coauthor Index
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