Open Information Extraction (OIE) systems like Nell and ReVerb have achieved impressive results by harvesting massive amounts of machine-readable knowledge with minimal supervision. However, the knowledge bases they produce still lack a clean, explicit semantic data model. This, on the other hand, could be provided by full-fledged semantic networks like DBpedia or Yago, which, in turn, could be...

In this paper, we study decentralized probabilistic job dispatching and load balancing strategies which optimize the performance of heterogeneous multiple computer systems. We present a model to study a heterogeneous multiple computer system with a decentralized stochastic job dispatching mechanism, where nodes are treated as M/G/1 servers. We discuss a way to implement a virtual centralized jo...

We analyse financial market models in which agents form their demand for an asset on the basis of their forecasts of future prices and where their forecasting rules may change over time, as a result of the influence of other traders. Agents will switch from one rule to another stochastically, and the price and profits process will reflect these switches. Among the possible rules are “chartist” ...

This paper introduces a new approach for the automated discovery of heterogeneous network topologies. The algorithm uses only information that is stored in the Address Forwarding Tables (AFTs) of the network devices. There have been different efforts to find an algorithmic solution using only AFTs. This has always involved the problem that AFTs contain incomplete information, which made it diff...

The problem of finding efficient workload distribution techniques is becoming increasingly important today for heterogeneous distributed systems where the availability of compute nodes may change spontaneously over time. Resource-allocation policies designed for such systems should maximize the performance and, at the same time, be robust against failure and recovery of compute nodes. Such a po...

This thesis describes a probabilistic model for optimum information retrieval in a distributed heterogeneous environment. The model assumes the collection of documents o ered by the environment to be hierarchically partitioned into subcollections. Documents as well as subcollections have to be indexed. At this, indexing methods using di erent indexing vocabularies can be employed. A query provi...

As we are moving toward next generation wireless networks, we are facing the integration of heterogeneous access networks. The main challenge is to provide mobile users moving freely across different radio access technologies with satisfactory quality of services for a variety of applications. Consequently, the seamless roaming over heterogeneous networks is an important concern. To minimize th...

MOTIVATION Tissue heterogeneity, arising from multiple cell types, is a major confounding factor in experiments that focus on studying cell types, e.g. their expression profiles, in isolation. Although sample heterogeneity can be addressed by manual microdissection, prior to conducting experiments, computational treatment on heterogeneous measurements have become a reliable alternative to perfo...

Despite recent molecular technique improvements, biological knowledge remains incomplete. Reasoning on living systems hence implies to integrate heterogeneous and partial informations. Although current investigations successfully focus on qualitative behaviors of macromolecular networks, others approaches show partial quantitative informations like protein concentration variations over times. W...

Probabilistic diagnosis aims at making the system-level fault diagnostic problem both easier to solve and the resulting algorithms more generally applicable. The price to pay for these advantages is that the diagnostic result is no longer guaranteed to be correct and complete in every fault situation. This paper presents a novel approach, called local information diagnosis (LID), and applies th...