Publication

Information Retrieval on Noisy Text

Related publications (38)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Noisy Text Categorization

Alessandro Vinciarelli

This work presents categorization experiments performed over noisy texts. By noisy it is meant any text obtained through an extraction process (affected by errors) from media other than digital texts (e.g. transcriptions of speech recordings extracted with ...

2005

Exploiting Hyperlinks to Learn a Retrieval Model

Samy Bengio, David Grangier

Information Retrieval (IR) aims at solving a ranking problem: given a query

q

and a corpus

C

, the documents of

C

should be ranked such that the documents relevant to

q

appear above the others. This task is generally performed by ranking the documen ...

2005

Inferring Document Similarity from Hyperlinks

Samy Bengio, David Grangier

Assessing semantic similarity between text documents is a crucial aspect in Information Retrieval systems. In this work, we propose to use hyperlink information to derive a similarity measure that can then be applied to compare any text documents, with or ...

2005

Inferring Document Similarity from Hyper-links

Samy Bengio, David Grangier

Assessing semantic similarity between text documents is a crucial aspect in Information Retrieval systems. In this paper, we propose a technique to derive a similarity measure from hyper-link information. As linked documents are generally semantically clos ...

IDIAP2005

Application of Information Retrieval Technologies to Presentation Slides

Jean-Marc Odobez, Alessandro Vinciarelli

Presentations are becoming an increasingly more common means of communication in working environments, and slides are often the necessary supporting material on which the presentations rely. In this paper, we describe a slide indexing and retrieval system ...

IDIAP2005

On the Use of Information Retrieval Measures for Speech Recognition Evaluation

Hervé Bourlard, Daniel Gatica-Perez, John David Scott Dines, Darren Moore

This paper discusses the evaluation of automatic speech recognition (ASR) systems developed for practical applications, suggesting a set of criteria for application-oriented performance measures. The commonly used word error rate (WER), which poses ASR eva ...

IDIAP2004

Application of Information Retrieval Techniques to Single Writer Documents

Alessandro Vinciarelli

This work shows Information Retrieval experiments performed over handwritten documents produced by a single writer. The same retrieval task has been performed over both manual (no errors) and automatic (Word Error Rate around 45%) transcriptions of 200 han ...

IDIAP2004

Noisy Text Categorization

Alessandro Vinciarelli

IDIAP2004

Noisy Text Clustering

David Grangier, Alessandro Vinciarelli

This work presents document clustering experiments performed over noisy texts (i.e. text that have been extracted through an automatic process like speech or character recognition). The effect of recognition errors on different clustering techniques is mea ...

IDIAP2004

Text Detection and Recognition in Images and Videos

Hervé Bourlard, Jean-Marc Odobez, Datong Chen

Text embedded in images and videos represents a rich source of information for content-based indexing and retrieval applications. In this paper, we present a new method for localizing and recognizing text in complex images and videos. Text localization is ...

2004

Exploiting Hyperlinks to Learn a Retrieval Model

Samy Bengio, David Grangier

Information Retrieval (IR) aims at solving a ranking problem: given a query

q

and a corpus

C

, the documents of

C

should be ranked such that the documents relevant to

q

appear above the others. This task is generally performed by ranking the documen ...

2005