Person

Sebastian Michel

This person is no longer with EPFL

Related publications (18)

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Efficient monitoring of personalized hot news over Web 2.0 streams

Karl Aberer, Sebastian Michel, Parisa Haghani

Web 2.0 streams, like blog postings, microblogging tweets, or RSS feeds from online communities, offer a wealth of latest news about real-world events and societal discussion. From a user’s perspective, it becomes harder and harder to get a decent overview ...

2012

Efficiently Maintaining Distributed Model-Based Views on Real-Time Data Streams

Karl Aberer, Sebastian Michel, Ho Young Jeung, Petre Alexandru Arion

Minimizing communication cost is a fundamental problem in large-scale federated sensor networks. Existing solutions applicable for the problem are often ad-hoc for specific query types, or they are inefficient when query results contain large volumes of da ...

2011

Tracking Hot-k Items over Web 2.0 Streams

Karl Aberer, Sebastian Michel, Parisa Haghani

The rise of the Web 2.0 has made content publishing easier than ever. Yesterday’s passive consumers are now active users who generate and contribute new data to the web at an immense rate. We consider evaluating data driven aggregation queries which arise ...

2011

Continuous Query Evaluation over Distributed Sensor Networks

Karl Aberer, Sebastian Michel, Oana Anca Jurca, Alexandre Herrmann

In this paper we address the problem of processing continuous multi-join queries, over distributed data streams. Our approach makes use of existing work in the field of publish/subscribe systems. We show how these principles can be ported to our envisioned ...

IEEE2010

The gist of everything new: personalized top-k processing over web 2.0 streams

Karl Aberer, Sebastian Michel, Parisa Haghani

Web 2.0 portals have made content generation easier than ever with millions of users contributing news stories in form of posts in weblogs or short textual snippets as in Twitter. Efficient and effective filtering solutions are key to allow users stay tune ...

ACM2010

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A sensor network data gathering and visualization infrastructure is demonstrated, comprising of Global Sensor Networks (GSN) middleware and Microsoft SensorMap. Users are invited to actively participate in the process of monitoring real-world deployments a ...

ICDE2009

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In this paper we consider distributed K-Nearest Neighbor (KNN) search and range query processing in high dimensional data. Our approach is based on Locality Sensitive Hashing (LSH) which has proven very efficient in answering KNN queries in centralized set ...

2009

GSN, Middleware for Streaming World (Best Demo Award)

Karl Aberer, Sebastian Michel, Ali Salehi, Mehdi Riahi

In this paper we present the Global Sensor Networks (gsn.sf.net) and the NexTick (nextick.org) projects. ...

2009

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We study the problem of continuous monitoring of top-k queries over multiple non-synchronized streams. Assuming a sliding window model, this general problem has been a well addressed research topic in recent years. However, most approaches assume the strea ...

2009

Top-k query processing is a fundamental building block for efficient ranking in a large number of applications. Efficiency is a central issue, especially for distributed settings, when the data is spread across different nodes in a network. This paper intr ...

2009