Zidrina Pabarskaite

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This paper presents a comprehensive survey of web log/usage mining based on over 100 research papers. This is the first survey dedicated exclusively to web log/usage mining. The paper identifies several web log mining sub-topics including specific ones such as data cleaning, user and session identification. Each sub-topic is explained, weaknesses and strong(More)
Due to huge, unstructured and scattered amount of data available on web, it is very tough for users to get relevant information in less time. To achieve this, improvement in design of web site, personalization of contents, prefetching and caching activities are done according to user's behavior analysis. User's activities can be captured into a(More)
We analyze portfolio creation techniques in a high frequency trading domain and randomly changing environments. We aim to create the best risk/reward portfolio based on thousands of profit histories of automated trading robots. We show that the effectiveness of standard portfolio weight calculation rules depends on the dimensionality, N, and the sample(More)
Markowitz's mean-variance portfolio optimisation is not suitable for a large number of assets due to the unacceptably slow quadratic optimisation procedure involved. This is particularly important in systematic/algorithmic/automated trading applications where instead of assets, automated trading systems are used. We propose a much faster heuristic approach(More)
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