Publications de Karl Aberer | EPFL Graph Search

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As the volumes of shared datasets are likely to soar, there is high demand of establishing the interlinking between these public datasets. To achieve this, we need to match their schemas altogether. Moreover, to extract useful pieces of information, ones m ...

The dramatic rise of time-series data produced in a variety of contexts, such as stock markets, mobile sensing, sensor networks, data centre monitoring, etc., has fuelled the development of large-scale distributed real-time computation systems (e.g., Apach ...

Diabetic patients are dependent on external substances to balance their blood glucose level. In order to control this level, they historically needed to sample a drop a blood from their hand and have it analyzed. Recently, other directions emerged to offer ...

To find a configuration of a distributed system satisfying performance goals is a complex search problem that involves many design parameters, like hardware selection, job distribution and process configuration. Performance models are a powerful tools to analyse potential system configurations, however, their evaluation is expensive, such that only a limited number of possible configurations can be evaluated. In this paper we present a systematic method to find a satisfactory configuration with feasible eff

QoS-based service selection mechanisms will play an essential role in service-oriented architectures, as e-Business applications want to use services that most accurately meet their requirements. Standard approaches in this field typically are based on the ...

Wireless Sensor Networks (WSNs) rely on in-network aggregation for efficiency, however, this comes at a price: A single adversary can severely influence the outcome by contributing an arbitrary partial aggregate value. Secure in-network aggregation can det ...

The P-Grid approach enables distributed search and replication. Gridella, a P2P system based on P-Grid, improves on Gnutella’s search performance while reducing bandwidth requirements. Fu ...

Crowdsensing applications are increasing at a tremendous rate. In crowdsensing, mobile sensors (humans, vehicle-mounted sensors, etc.) generate streams of information that is used for inferring high-level phenomena of interest (e.g, traffic jams, air pollu ...

Live-streaming platforms broadcast user-generated video in real-time. Recommendation on these platforms shares similarities with traditional settings, such as a large volume of heterogeneous content and highly skewed interaction distributions. However, sev ...

With new standards like RDF or OWL paving the way for the much anticipated semantic web, a new breed of large scale semantic systems is about to appear. Even if research on semantic reconciliation methods is abundant, it is not clear how interoperable very large scale semantic systems can be. This paper represents a first effort towards analytically analyzing semantic interoperability in the large: By adapting a recent graph-theoretic framework, we examine the dynamics of large scale semantic systems and de

We present ProtoPeer, a peer-to-peer systems prototyping toolkit that allows for switching between the event driven simulation and live network deployment without changing any of the application code. ProtoPeer exports a set of APIs for message passing, me ...

The International Workshop on Semantic Data Management (SemData) was held in Singapore co-located with the VLDB Conference 2010, with the goal of serving as a platform for the discussion and investigation of various aspects related to semantic databases and data management in the large. The workshop was a full-day event featuring two research sessions, one industry session and a panel discussion, and attracted over 25 attendees. This report summarizes the key topics presented, interesting ideas discussed an

We propose a novel, semi-supervised approach towards domain taxonomy induction from an input vocabulary of seed terms. Unlike all previous approaches, which typically extract direct hypernym edges for terms, our approach utilizes a novel probabilistic framework to extract hypernym subsequences. Taxonomy induction from extracted subsequences is cast as an instance of the minimumcost flow problem on a carefully designed directed graph. Through experiments, we demonstrate that our approach outperforms stateof-

Karl Aberer

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On Leveraging Crowdsourcing Techniques for Schema Matching Networks

Personalized Point-of-Interest Recommendation by Mining Users' Preference Transition

Handling Very Large Numbers of Messages in Distributed Hash Tables

SigCO: Mining Significant Correlations via a Distributed Real-time Computation Engine

Detection of hypoglycemic events through wearable sensors

Configuration of Distributed Message Converter Systems using Performance Modeling

SoCo: A Social Network Aided Context-Aware Recommender System

QoS-based Service Selection and Ranking with Trust and Reputation Management

Efficient and Robust Secure Aggregation for Sensor Networks

Improving Data Access in P2P Systems

Query Optimization in XML Structured Document Databases

Defending Imitating Attacks in Web Credibility Evaluation Systems

On crowdsensed data acquisition using multi-dimensional point processes

Semantic and Sensitivity Aware Location-Privacy Protection for the Internet of Things

Recommendation on Live-Streaming Platforms: Dynamic Availability and Repeat Consumption

A Necessary Condition for Semantic Interoperability in the Large

ProtoPeer: from Simulation to Live Deployment in One Step

A Cost-Benefit Analysis of Data Processing Architectures for the Smart Grid

Workshop on Semantic Data Management: A Summary Report

Taxonomy Induction using Hypernym Subsequences