Publications by Sebastian Michel

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

Tracking Hot-k Items over Web 2.0 Streams

Karl Aberer, Parisa Haghani, Sebastian Michel

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

Efficient Interest Group Discovery in Social Networks using an Integrated Structure/Quality Index

Karl Aberer, Adriana Budura, Sebastian Michel

2011

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

Karl Aberer, Parisa Haghani, Sebastian Michel

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

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

Distributed top-k aggregation queries at large

Sebastian Michel

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

Evaluating Top-k Queries over Incomplete Data Streams

Karl Aberer, Parisa Haghani, Sebastian Michel

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

Distributed Similarity Search in High Dimensions Using Locality Sensitive Hashing

Karl Aberer, Parisa Haghani, Sebastian Michel

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

Knowing When to Slide: Efficient Scheduling for Sliding Window Processing

Karl Aberer, Sebastian Michel, Mehdi Riahi, Ali Salehi

We consider sliding window query execution scheduling in stream processing engines. Sliding windows are an essential building block to limit the query focus at a particular part of the stream, based either on value count or time ranges. These so called sli ...

IEEE Computer Society2009

Environmental Monitoring 2.0

Karl Aberer, Marc Parlange, Guillermo Barrenetxea Kobas, Mathias Thierry Pierre Bavay, Sebastian Michel, Ali Salehi

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