We study ensemble-based graph-theoretical methods aiming to approximate the size of the minimum dominating set (MDS) in scale-free networks. We analyze both analytical upper bounds of dominating sets and numerical realizations for applications. We propose two novel probabilistic dominating set selection strategies that are applicable to heterogeneous networks. One of them obtains the smallest p...

We address the problem of analysing how users actually interact with software. Users are heterogeneous: they adopt different usage styles and each individual user may move between different styles, from one interaction session to another, or even during an interaction session. For analysis, we require new techniques to model and analyse temporal data sets of logged interactions with the purpose...

We address the problem of analysing how users actually interact with software. Users are heterogeneous: they adopt different usage styles and each individual user may move between different styles, from one interaction session to another, or even during an interaction session. For analysis, we require new temporal analytics: techniques to model and analyse temporal data sets of logged interacti...

P2PShare is a P2P system for large-scale probabilistic data sharing that leverages content-based and expert-based recommendation. It is designed to manage probabilistic and deterministic data in P2P environments. It provides a flexible environment for integration of heterogeneous sources, and takes into account the social based aspects to discover high quality results for queries by privileging...

Evaluation and redesign of user-intensive mobile applications is challenging because users are often heterogeneous, adopting different patterns of activity, at different times. We set out a process of integrating statistical, longitudinal analysis of actual logged behaviours, formal, probabilistic discrete state models of activity patterns, and hypotheses over those models expressed as probabil...

The Integrated Data Analysis (IDA) concept allows one to combine data from different experiments to obtain improved results. Heterogeneous and complementary experimental data as well as various kinds of physical prior information are easily integrated employing Bayesian probability theory. The concepts of IDA are compared to the traditional approach for data analysis where sequential analysis a...

Describing the information retrieval task as computing the probability P (d! q) that a document d implies a query q has become a key issue of theoretical information retrieval research work. We introduce HySpirit as a flexible system for describing the retrieval process as probabilistic implication and for representing the diverse knowledge dimensions of multimedia documents. HySpirit supports ...

the current study investigated and compared data generation methods for groundwater modeling. thesemethods can be divided into two classes; geostatistic and probabilistic. by comparing geostatistic methods,the best method was chosen and the hydraulic conductivity of the aquifer was generated for a study area ina grid (9-cell) format. after observing weak spatial correlation between the data, th...

Determining the best location to be profitable for the facility’s lifetime is the important decision of public and private firms, so this is why discussion about dynamic location problems (DLPs) is a critical significance. This paper presented a comprehensive review from 1968 up to most recent on published researches about DLPs and classified them into two parts. First, mathematical models deve...

Instant messaging (IM) systems allow users to spontaneously communicate over distance, yet they bear the risk for disruption of the recipient. In order to reduce disruption, novel approaches for detecting and presenting mutual availability are needed. In this paper we show how fine-grained IM availability predictions can be made for nomadic users solely based on sensors installed on a laptop co...