| 1. |
- Abghari, Shahrooz, et al.
(författare)
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A Minimum Spanning Tree Clustering Approach for Outlier Detection in Event Sequences
- 2018
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Ingår i: The 17th IEEE International Conference on Machine Learning and Applications Special Session on Machine Learning Algorithms, Systems and Applications. - : IEEE. ; , s. 1123-1130
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Konferensbidrag (refereegranskat)abstract
- Outlier detection has been studied in many domains. Outliers arise due to different reasons such as mechanical issues, fraudulent behavior, and human error. In this paper, we propose an unsupervised approach for outlier detection in a sequence dataset. The proposed approach combines sequential pattern mining, cluster analysis, and a minimum spanning tree algorithm in order to identify clusters of outliers. Initially, the sequential pattern mining is used to extract frequent sequential patterns. Next, the extracted patterns are clustered into groups of similar patterns. Finally, the minimum spanning tree algorithm is used to find groups of outliers. The proposed approach has been evaluated on two different real datasets, i.e., smart meter data and video session data. The obtained results have shown that our approach can be applied to narrow down the space of events to a set of potential outliers and facilitate domain experts in further analysis and identification of system level issues.
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| 2. |
- Abghari, Shahrooz, et al.
(författare)
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Higher order mining for monitoring district heating substations
- 2019
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Ingår i: Proceedings - 2019 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2019. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781728144931 ; , s. 382-391
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Konferensbidrag (refereegranskat)abstract
- We propose a higher order mining (HOM) approach for modelling, monitoring and analyzing district heating (DH) substations' operational behaviour and performance. HOM is concerned with mining over patterns rather than primary or raw data. The proposed approach uses a combination of different data analysis techniques such as sequential pattern mining, clustering analysis, consensus clustering and minimum spanning tree (MST). Initially, a substation's operational behaviour is modeled by extracting weekly patterns and performing clustering analysis. The substation's performance is monitored by assessing its modeled behaviour for every two consecutive weeks. In case some significant difference is observed, further analysis is performed by integrating the built models into a consensus clustering and applying an MST for identifying deviating behaviours. The results of the study show that our method is robust for detecting deviating and sub-optimal behaviours of DH substations. In addition, the proposed method can facilitate domain experts in the interpretation and understanding of the substations' behaviour and performance by providing different data analysis and visualization techniques.
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| 3. |
- Abghari, Shahrooz, et al.
(författare)
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Outlier Detection for Video Session Data Using Sequential Pattern Mining
- 2018
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Ingår i: ACM SIGKDD Workshop On Outlier Detection De-constructed.
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Konferensbidrag (refereegranskat)abstract
- The growth of Internet video and over-the-top transmission techniqueshas enabled online video service providers to deliver highquality video content to viewers. To maintain and improve thequality of experience, video providers need to detect unexpectedissues that can highly affect the viewers’ experience. This requiresanalyzing massive amounts of video session data in order to findunexpected sequences of events. In this paper we combine sequentialpattern mining and clustering to discover such event sequences.The proposed approach applies sequential pattern mining to findfrequent patterns by considering contextual and collective outliers.In order to distinguish between the normal and abnormal behaviorof the system, we initially identify the most frequent patterns. Thena clustering algorithm is applied on the most frequent patterns.The generated clustering model together with Silhouette Index areused for further analysis of less frequent patterns and detectionof potential outliers. Our results show that the proposed approachcan detect outliers at the system level.
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| 4. |
- Abghari, Shahrooz, et al.
(författare)
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Trend analysis to automatically identify heat program changes
- 2017
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Ingår i: Energy Procedia. - : Elsevier. ; , s. 407-415
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Konferensbidrag (refereegranskat)abstract
- The aim of this study is to improve the monitoring and controlling of heating systems located at customer buildings through the use of a decision support system. To achieve this, the proposed system applies a two-step classifier to detect manual changes of the temperature of the heating system. We apply data from the Swedish company NODA, active in energy optimization and services for energy efficiency, to train and test the suggested system. The decision support system is evaluated through an experiment and the results are validated by experts at NODA. The results show that the decision support system can detect changes within three days after their occurrence and only by considering daily average measurements.
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| 5. |
- Acs, Zoltan J., et al.
(författare)
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Philippe Aghion : recipient of the 2016 Global Award for Entrepreneurship Research
- 2017
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Ingår i: Small Business Economics. - : Springer. - 0921-898X .- 1573-0913. ; 48:1, s. 1-8
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Tidskriftsartikel (refereegranskat)abstract
- Professor Philippe Aghion is the 2016 recipient of the Global Award for Entrepreneurship Research, consisting of 100,000 Euros and a statuette designed by the internationally renowned Swedish sculptor Carl Milles. He is one of the most influential researchers worldwide in economics in the last couple of decades. His research has advanced our understanding of the relationship between firm-level innovation, entry and exit on the one hand, and productivity and growth on the other. Aghion has thus accomplished to bridge theoretical macroeconomic growth models with a more complete and consistent microeconomic setting. He is one of the founding fathers of the pioneering and original contribution referred to as Schumpeterian growth theory. Philippe Aghion has not only contributed with more sophisticated theoretical models, but also provided empirical evidence regarding the importance of entrepreneurial endeavours for societal prosperity, thereby initiating a more nuanced policy discussion concerning the interdependencies between entrepreneurship, competition, wealth and growth.
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| 6. |
- Allahyari, Hiva, et al.
(författare)
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User-oriented Assessment of Classification Model Understandability
- 2011
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Konferensbidrag (refereegranskat)abstract
- This paper reviews methods for evaluating and analyzing the understandability of classification models in the context of data mining. The motivation for this study is the fact that the majority of previous work has focused on increasing the accuracy of models, ignoring user-oriented properties such as comprehensibility and understandability. Approaches for analyzing the understandability of data mining models have been discussed on two different levels: one is regarding the type of the models’ presentation and the other is considering the structure of the models. In this study, we present a summary of existing assumptions regarding both approaches followed by an empirical work to examine the understandability from the user’s point of view through a survey. The results indicate that decision tree models are more understandable than rule-based models. Using the survey results regarding understandability of a number of models in conjunction with quantitative measurements of the complexity of the models, we are able to establish correlation between complexity and understandability of the models.
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| 7. |
- Andersson, Ewa K., 1972-, et al.
(författare)
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Self-Reported eHealth literacy among nursing students in Sweden and Poland : The eNursEd cross-sectional multicentre study
- 2023
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Ingår i: Health Informatics Journal. - : Sage Publications. - 1460-4582 .- 1741-2811. ; 29:4
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Tidskriftsartikel (refereegranskat)abstract
- This study aimed to provide an understanding of nursing students’ self-reported eHealth literacy in Sweden and Poland. This cross-sectional multicentre study collected data via a questionnaire in three universities in Sweden and Poland. Descriptive statistics, the Spearman’s Rank Correlation Coefficient, Mann–Whitney U, and Kruskal–Wallis tests were used to analyse different data types. Age (in the Polish sample), semester, perceived computer or laptop skills, and frequency of health-related Internet searches were associated with eHealth literacy. No gender differences were evidenced in regard to the eHealth literacy. Regarding attitudes about eHealth, students generally agreed on the importance of eHealth and technical aspects of their education. The importance of integrating eHealth literacy skills in the curricula and the need to encourage the improvement of these skills for both students and personnel are highlighted, as is the importance of identifying students with lacking computer skills.
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| 8. |
- Andersson, Martin, et al.
(författare)
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External Trade and Internal Geography: Local Export Spillovers by Industry Characteristics and Firm Size
- 2012
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Ingår i: Spatial Economic Analysis. - : Informa UK Limited. - 1742-1772 .- 1742-1780. ; 7:4, s. 420-445
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Tidskriftsartikel (refereegranskat)abstract
- Exporting firms in a region may reduce export entry costs for other local firms either through market or non-market interactions. This paper tests this proposition by analyzing whether the probability of exporting among Swedish firms is positively associated with the local presence of exporters in their region and industry. Our results support this conjecture, while also providing some support for such export spillovers being more important in contract-intensive industries and small firms. The results for different industries and size-classes of firms are also sensitive to whether we focus on firms' export status or restrict the sample to export starters.
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| 9. |
- Andersson, Martin, et al.
(författare)
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Historical local industry structure, voting patterns and the long-run entrepreneurial character of regions : Swedish examples
- 2022
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Ingår i: The annals of regional science. - : Springer. - 0570-1864 .- 1432-0592. ; 69:3, s. 611-631
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Tidskriftsartikel (refereegranskat)abstract
- Spatial variations in rates of new firm formation are large and spatially persistent over long periods of time. A common explanation of this empirical regularity is so-called local entrepreneurship cultures, which refer to spatially embedded social characteristics that change in slow processes. This paper discusses perspectives on the development of such cultures and focuses on the role of historical industry structures in forming the long-run entrepreneurial character of regions. To illustrate the empirical relevance of arguments and findings in the literature, we use historical data on voting patterns in municipalities in Sweden, as well as indications of their early industrial concentrations, and assess their correlations with present-day entrepreneurial activity. We show that places with a high share of left-wing votes in the period 1917-1948 and early historical presence of heavy industry have lower rates of new firm formation, less positive public attitudes toward entrepreneurship as well as larger average establishment sizes in the twenty-first century. The empirical patterns are consistent with the argument that regions' historical industry structure is one factor that influences the development of local entrepreneurship cultures.
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| 10. |
- Andersson, Martin, et al.
(författare)
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How Local are Spatial Density Externalities? Neighbourhood Effects in Agglomeration Economies
- 2016
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Ingår i: Regional Studies. - : Informa UK Limited. - 0034-3404 .- 1360-0591. ; 50:6, s. 1082-1095
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Tidskriftsartikel (refereegranskat)abstract
- Andersson M., Klaesson J. and Larsson J. P. How local are spatial density externalities? Neighbourhood effects in agglomeration economies, Regional Studies. The geographic scale at which density externalities operate is analysed in this paper. Using geocoded high-resolution data, the analysis is focused on exogenously determined within-city squares (‘neighbourhoods’) of 1 km2. The analysis confirms a city-wide employment density–wage elasticity and an economically significant density–wage elasticity at the neighbourhood level that attenuate sharply with distance. Panel estimates over 20 years suggest a neighbourhood density–wage elasticity of about 3%, while the city-wide elasticity is about 1%. It is argued that the neighbourhood level is more prone to capture learning, e.g. through knowledge and information spillovers. This interpretation is supported by (1) significantly larger neighbourhood elasticities for university educated workers and (2) sharper attenuation with distance of the effect for such workers.
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