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Related publications (19)

Query Refinement Using Conversational Context: A Method and an Evaluation Resource

This paper introduces a query refinement method applied to queries asked by users during a meeting or a conversation. The proposed method does not require further clarifications from users, to avoid distracting them from their conversation, but leverages i ...

Springer-Verlag Berlin2015

Combine and Conquer

Vincent Etter

In this thesis, we explore the application of data mining and machine learning techniques to several practical problems. These problems have roots in various fields such as social science, economics, and political science. We show that computer science tec ...

EPFL2015

Solid-State Storage and Work Sharing for Efficient Scaleup Data Analytics

Manoussos Gavriil Athanassoulis

Today, managing, storing and analyzing data continuously in order to gain additional insight is becoming commonplace. Data analytics engines have been traditionally optimized for read-only queries assuming that the main data reside on mechanical disks. The ...

EPFL2014

Quality-aware similarity assessment for entity matching in Web data

Karl Aberer, Zoltán Miklós, Surender Reddy Yerva

One of the key challenges to realize automated processing of the information on the Web, which is the central goal of the Semantic Web, is related to the entity matching problem. There are a number of tools that reliably recognize named entities, such as p ...

Wiley-Blackwell2012

An Agent-Based Focused Crawling Framework for Topic- and Genre-Related Web Document Discovery

Nikolaos Pappas

The discovery of web documents about certain topics is an important task for web-based applications including web document retrieval, opinion mining and knowledge extraction. In this paper, we propose an agent-based focused crawling framework able to retri ...

IEEE2012

Semantic Sensor Data Search in a Large-Scale Federated Sensor Network

Karl Aberer, Jean Paul Calbimonte Perez, Ho Young Jeung

Sensor network deployments are a primary source of massive amounts of data about the real world that surrounds us, measuring a wide range of physical properties in real time. However, in large-scale deployments it becomes hard to eectively exploit the data ...

CEUR-WS2011

Tools and Frameworks for Big Learning in Scala: Leveraging the Language for High Productivity and Performance

Martin Odersky, Philipp Haller

Implementing machine learning algorithms for large data, such as the Web graph and social networks, is challenging. Even though much research has focused on making sequential algorithms more scalable, their running times continue to be prohibitively long. ...

2011

Leveraging User-Generated Content for Information Discovery on the Web

Adriana Budura

The large-scale adoption of the Web 2.0 paradigm has revolutionized the way we interact with the Web today. End-users, so far mainly passive consumers of information are now becoming active information producers, creating, uploading, and commenting on all ...

EPFL2010

TOQL: Temporal Ontology Querying Language

Nikolaos Maris

We introduce TOQL, a query language for querying time information in ontologies. TOQL is a high level query language that handles ontologies almost like relational databases. Queries are issued as SQL-like statements involving time (i.e., time points or in ...

2009

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