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Using Highly Discriminative Keys for Indexing in a Peer-to-Peer Full-Text Retrieval System

Publications associées (32)

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Machine learning for information retrieval

David Grangier

In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...

EPFL2008

Machine Learning for Information Retrieval

David Grangier

École Polytechnique Fédérale de Lausanne2008

Machine Learning for Information Retrieval

David Grangier

IDIAP2008

Machine learning approaches to text representation using unlabeled data

Mikaela Keller

With the rapid expansion in the use of computers for producing digitalized textual documents, the need of automatic systems for organizing and retrieving the information contained in large databases has become essential. In general, information retrieval s ...

EPFL2008

Using Bibliographic Knowledge for Ranking in Scientific Publication Databases

Martin Rajman, Martin Veselý

Document ranking for scientific publications involves a variety of specialized resources (e.g. author or citation indexes) that are usually difficult to use within standard general purpose search engines that usually operate on large-scale heterogeneous do ...

IOS2008

A Discriminative Kernel-based Model to Rank Images from Text Queries

Samy Bengio, David Grangier

This paper introduces a discriminative model for the retrieval of images from text queries. Our approach formalizes the retrieval task as a ranking problem, and introduces a learning procedure optimizing a criterion related to the ranking performance. The ...

IDIAP2007

Query-Driven Indexing for Peer-to-Peer Text Retrieval

Karl Aberer, Martin Rajman, Vinh Toan Luu, Ivana Podnar, Gleb Skobeltsyn

We describe a query-driven indexing framework for scalable text retrieval over structured P2P networks. To cope with the bandwidth consumption problem that has been identified as the major obstacle for full-text retrieval in P2P networks, we truncate posti ...

2007

Scalable peer-to-peer Web search using highly discriminative keys

Vinh Toan Luu

Standard general-purpose Web retrieval relies on centralized search engines that do not realistically scale when applied to the exponentially growing number of documents available on the Web. By taking advantage of the resource sharing principle, Peer-to-P ...

EPFL2007

Web Text Retrieval with a P2P Query-Driven Index

Karl Aberer, Martin Rajman, Vinh Toan Luu, Ivana Podnar, Gleb Skobeltsyn

In this paper, we present a query-driven indexing/retrieval strategy for efficient full text retrieval from large document collections distributed within a structured P2P network. Our indexing strategy is based on two important properties: (1) the generate ...

2007

Scalable Peer-to-Peer Web Retrieval with Highly Discriminative Keys

Karl Aberer, Martin Rajman, Vinh Toan Luu, Ivana Podnar, Fabius Klemm

The suitability of peer-to-peer (P2P) approaches for full-text Web retrieval has recently been questioned because of the claimed unacceptable bandwidth consumption induced by retrieval from very large document collections. In this contribution we formalize ...

IEEE2007