Dr Katarzyna Musial-Gabrys
- 01202 961109
- kmusialgabrys at bournemouth dot ac dot uk
- Associate Professor in Computing
- Poole House P256d, Talbot Campus, Fern Barrow, Poole, BH12 5BB
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Modelling of complex adaptive software systems – the main challenge of the current software systems is to build the systems that will be able to adapt to the changing external environment. The research conducted within the Advanced Software Engineering task within INFER project was focused on developing architectures for complex adaptive systems. I worked on that task when I was employed at BU.
Evaluation of a user position in a social network – during my PhD I conduct research on assessing a position of individuals in networked systems. The position is calculated based on the users activities and their interactions. The method and appropriate algorithms were developed and number of experiments on real-world networks was carried out. The research on evaluating user position was supported by the individual grant that I obtained from the Polish Ministry of Science and Higher Education (06/2008 – 12/2009).
Multirelational social networks – these are the networks in which more than one type of relationship exists. Different types of relationships can emerge from various communication channels, i.e. based on each communication channel separate relation that can be also called a layer of a network is created. The relationships are extracted from the users activities and if in the system the knowledge about more than one kind of activity is gathered then more than one type of connection can be defined. Different layers can be also built upon various nature of the connections between users, e.g. co-workers, family members, friends. The systems that can be used in such analysis are the multimedia sharing systems such as Flickr or YouTube, which are typical examples of Web 2.0 systems. In my research I have investigated such systems as Flickr, Vimeo, ExtraDom, and recently Badoo.
Network motifs method in social networks – Network motifs are small subgraphs that reflect local network topology and were shown to be useful for creating profiles that reveal several properties of the network. The outcomes of my research have revealed that motif analysis enables the effective investigation of both network structure and patterns of interactions between nodes within the network. In addition, the analysis of network motifs dynamics can be utilized in detecting and exploration of changes in complex network structures.
Dynamics and predictive modelling of complex networked systems – this is area that currently becomes the main field of my research efforts. The conducted research is concerned with discovering patterns in nodes’ behaviours and the interactions between them. The analysis of these patterns and their changes in time allows prediction of the future behaviour of nodes and their relations. One of the ways to model the network dynamics is the application of methods based on the molecular modelling concept and other physically-inspired methods. Another approach that I investigate is the application of machine learning methods to infer and predict the future structure and characteristics of network.
Intelligent analysis of large complex networks – the networks that are in the area of my interest are extracted from large datasets obtained from telecommunication companies (British Telecom plc – BT), e-mail servers (WUT, Enron), multimedia sharing systems (Flickr), etc. The first research on investigating and analysing social networks was conducted as part of the EU FP6 Coordination Action project on Nature-inspired Smart Information Systems (11/2005 – 01/2008) where I acted as a member of the Nature-inspired Data Technology focus group. I presented the research results at the NiSIS symposia at Majorca (06/2006), Tenerife (11/2006), and Malta (11/2007).
Complex Adaptive Systems -
- Musial-Gabrys, K., McBurney, P. and Zhang, J., 2017. Convergence of trading strategies in continuous double auction markets with boundedly-rational networked traders. Review of Quantitative Finance and Accounting.
- Musial-Gabrys, K., McBurney, P. and Zhang, J., 2017. Influence of individual rationality on continuous double auction markets with networked traders. Theory and Decision: an international journal for multidisciplinary advances in decision sciences.
- Musial-Gabrys, K., Aroyo, L., De Meo, P., Rosaci, D. and Sarne, G.M.L., 2016. Computing User Reputation in Large Online Social Networks by Means of Different Centrality Indices. ACM Transactions on Internet Technology.
- Musial, K., Brodka, P. and Magnani, M., 2016. Social Network Analysis in Applications. AI COMMUNICATIONS, 29 (1), 55-56.
- Gao, F., Musial, K., Cooper, C. and Tsoka, S., 2015. Link prediction methods and their accuracy for different social networks and network metrics. Scientific Programming, 2015.
- Musial, K., Bródka, P., Kazienko, P. and Gaworecki, J., 2014. Extraction of multilayered social networks from activity data. Scientific World Journal, 2014.
- Bródka, P., Magnani, M. and Musial, K., 2014. Message from SNAA 2014 program chairs. ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, xxxiv.
- Musial, K., Budka, M. and Juszczyszyn, K., 2013. Creation and growth of online social network: How do social networks evolve? World Wide Web, 16 (4), 421-447.
- Musial, K., Budka, M. and Juszczyszyn, K., 2013. Creation and growth of online social network How do social networks evolve? WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 16 (4), 421-447.
- Budka, M., Juszczyszyn, K., Musial, K. and Musial, A., 2013. Molecular model of dynamic social network based on e-mail communication. Social Network Analysis and Mining, 3 (3), 543-563.
- Musiał, K. and Kazienko, P., 2013. Social networks on the Internet. World Wide Web, 16 (1), 31-72.
- Musial-Gabrys, K., Budka, M. and Juszczyszyn, K., 2012. Triad transition probabilities characterize complex networks. Awarness Magazine.
- Bródka, P., Kazienko, P., Musiał, K. and Skibicki, K., 2012. Analysis of Neighbourhoods in Multi-layered Dynamic Social Networks. International Journal of Computational Intelligence Systems, 5 (3), 582-596.
- Zliobaite, I., Bifet, A., Gaber, M., Gabrys, B., Gama, J., Minku, L. and Musial, K., 2012. Next challenges for adaptive learning systems. SIGKDD Explorations, in press.
- Zliobaite, I., Bifet, A., Gaber, M.M., Gabrys, B., Gama, J., Minku, L.L. and Musial, K., 2012. Next challenges for adaptive learning systems. SIGKDD Explorations, 14, 48-55.
- Budka, M., Gabrys, B. and Musial, K., 2011. On Accuracy of PDF Divergence Estimators and Their Applicability to Representative Data Sampling. ENTROPY, 13 (7), 1229-1266.
- Kazienko, P., Musial, K. and Kajdanowicz, T., 2011. Multidimensional Social Network in the Social Recommender System. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 41 (4), 746-759.
- Juszczyszyn, K., Kazienko, P. and Musiał, K., 2010. Personalized ontology-based recommender systems for multimedia objects. Studies in Computational Intelligence, 289, 275-292.
- Kazienko, P., Musiał, K. and Zgrzywa, A., 2009. Evaluation of node position based on email communication. Control and Cybernetics, 38 (1), 67-86.
- Juszczyszyn, K., Musial, K., Kazienko, P. and Gabrys, B., 2009. TEMPORAL CHANGES IN LOCAL TOPOLOGY OF AN EMAIL-BASED SOCIAL NETWORK. COMPUTING AND INFORMATICS, 28 (6), 763-779.
- Musial, K. and Juszczyszyn, K., 2009. Motif Analysis and the Periodic Structural Changes in an Organizational Email-Based Social Network. International Journal of Virtual Communities and Social Networking, 1, 22-36.
- Kazienko, P., Musiał, K. and Juszczyszyn, K., 2008. Recommendation of multimedia objects based on similarity of ontologies. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5177 LNAI (PART 1), 194-201.
- Musiał, K., Juszczyszyn, K. and Kazienko, P., 2008. Ontology-based recommendation in multimedia sharing systems. Systems Science, 34 (1), 97-106.
- Musial, K. and Juszczyszyn, K., 2008. A method for evaluating organizational structure on the basis of social network analysis. Foundations of Control and Management Sciences, 9, 97-108.
- Kazienko, P. and Musial, K., 2007. On utilising social networks to discover representatives of human communities. International Journal of Intelligent Information and Database Systems, 1 (3-4), 293-310.
- Kajdanowicz, T., Michalski, R., Musiał, K. and Kazienko, P.. Learning in Unlabeled Networks - An Active Learning and Inference Approach. AI Communications, 29, 1.
- Howlett, R.J., Gabrys, B., Musial-Gabrys, K. and Roach, J., 2013. Innovation through Knowledge Transfer 2012.
- Abdullaev, S., McBurney, P. and Musial, K., 2016. Pricing Options with Portfolio-Holding Trading Agents in Direct Double Auction. 1754-1755.
- Musial-Gabrys, K., 2014. Research designs for social network analysis. In: Alhajj, R. and Ronke, J., eds. Encyclopedia of Social Network Analysis and Mining. Springer.
- Musial, K., Budka, M. and Blysz, W., 2013. Understanding the Other Side - The Inside Story of the INFER Project. 1-9.
- Brodka, P., Musial, K. and Kazienko, P., 2009. Efficiency of node position calculation in social networks. 455-463.
- Musiał, K., Kazienko, P. and Bródka, P., 2009. User position measures in social networks.
- Musiał, K. and Juszczyszyn, K., 2009. Properties of bridge nodes in social networks. 357-364.
- Brodka, P., Musial, K. and Kazienko, P., 2009. A performance of centrality calculation in social networks. 24-31.
- Musial, K. and Juszczyszyn, K., 2009. Motif-based analysis of social position influence on interconnection patterns in complex social network. 34-39.
- Juszczyszyn, K. and Musiał, K., 2009. Structural changes in an email-based social network. 40-49.
- Musiał, K., Kazienko, P. and Kajdanowicz, T., 2008. Social recommendations within the multimedia sharing systems. 364-372.
- Kazienko, P. and Musiał, K., 2008. Mining personal social features in the community of email users. 708-719.
- Kazienko, P. and Musiał, K., 2007. Assessment of personal importance based on social networks. 529-539.
- Kazienko, P. and Musiał, K., 2006. Social capital in online social networks. 417-424.
- Zhang, J., McBurney, P. and Musial, K., 2017. Convergence of trading strategies in continuous double auction markets with boundedly-rational networked traders. 1-52.
- Musial-Gabrys, K. and Gao, F., 2016. Hybrid Link Prediction Model. In: The Sixth Workshop on Social Network Analysis in Applications (SNAA 2016) co-located with International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2016) 18-21 August 2016 San Francisco, USA.
- Kajdanowicz, T., Michalski, R., Musial, K. and Kazienko, P., 2016. Learning in unlabeled networks - An active learning and inference approach. 123-148.
- Venkata, S.K., Keppens, J. and Musial, K., 2016. Agent based simulation to evaluate adaptive caching in distributed databases. 455-462.
- Guo, M., Musial-Gabrys, K. et al., 2015. Message from the MSNCom 2015 workshop chairs. lvi.
- Musial-Gabrys, K. and Venkata, S.K., 2015. Adaptive Caching Using Sub-query Fragmentation for Reduction in Data Transfers from Distributed Databases. In: 2015 Astronomical Data Analysis Systems And Software Conference 25-29 October 2015 Australia.
- Abdullaev, S., Mcburney, P. and Musial, K., 2015. Direct exchange mechanisms for option pricing. 269-284.
- Krol, D., Budka, M., Musial, K. and IEEE, 2014. Simulating the information diffusion process in complex networks using push and pull strategies. 1-8.
- Musial, K., Gabrys, B. and Buczko, M., 2013. What kind of network are you? - Using local and global characteristics in network categorisation tasks. 1366-1373.
- Kajdanowicz, T., Michalski, R., Musial, K. and Kazienko, P., 2013. Active learning and inference method for within network classification. 1299-1306.
- Musial, K. and Sastry, N., 2012. Social media - Are they underpinned by social or interest-based interactions? 1-6.
- Juszczyszyn, K., Gonczarek, A., Tomczak, J.M., Musial, K., Budka, M. and IEEE, 2012. A Probabilistic Approach to Structural Change Prediction in Evolving Social Networks. 996-1001.
- Budka, M., Musial, K., Juszczyszyn, K. and IEEE, 2012. Predicting the Evolution of Social Networks: Optimal Time Window Size for Increased Accuracy. 21-30.
- Bródka, P., Skibicki, K., Kazienko, P. and Musiał, K., 2011. A degree centrality in multi-layered social network. 237-242.
- Juszczyszyn, K., Musiał, K. and Budka, M., 2011. Link prediction based on Subgraph evolution in dynamic social networks. 27-34.
- Kazienko, P., Musial, K., Kukla, E., Kajdanowicz, T. and Bródka, P., 2011. Multidimensional social network: Model and analysis. 378-387.
- Juszczyszyn, K., Budka, M., Musial, K. and IEEE, 2011. The Dynamic Structural Patterns of Social Networks Based on Triad Transitions. 581-586.
- Kazienko, P., Kukla, E., Musial, K., Kajdanowicz, T., Brodka, P. and Gaworecki, J., 2011. A Generic Model for a Multidimensional Temporal Social Network. 1-14.
- Juszczyszyn, K., Musiał, A., Musiał, K. and Bródka, P., 2010. Utilizing dynamic molecular modelling technique for predicting changes in complex social networks. 1-4.
- Bródka, P., Musial, K. and Kazienko, P., 2010. A method for group extraction in complex social networks. 238-247.
- Kazienko, P., Brodka, P. and Musial, K., 2010. Individual neighbourhood exploration in complex multi-layered social network. 5-8.
- Kazienko, P., Bródka, P., Musial, K. and Gaworecki, J., 2010. Multi-layered social network creation based on bibliographic data. 407-412.
- Musial, K., Juszczyszyn, K., Gabrys, B. and Kazienko, P., 2009. Patterns of Interactions in Complex Social Networks Based on Coloured Motifs Analysis. 607-+.
- Juszczyszyn, K., Kazienko, P. and Musiał, K., 2008. Local topology of social network based on motif analysis. 97-105.
- Kazienko, P., Musiał, K. and Kajdanowicz, T., 2008. Profile of the social network in photo sharing systems. 2815-2826.
- Kazienko, P. and Musiał, K., 2006. Recommendation framework for online social networks. 111-120.
- Santhilata Kuppili Venkata (E ective Data Search in Distributed Databases)
- Fei Gao (Link Prediction Problem For The Online Social Networks)