Relevance feedback in probabilistic multimedia retrieval

Lioudmila Boldareva; Djoerd Hiemstra; Willem Jonker

Relevance feedback in probabilistic multimedia retrieval

Lioudmila Boldareva
, Djoerd Hiemstra
, Willem Jonker

Databases (Former)

Research output: Contribution to conference › Paper › peer-review

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Abstract

In this paper we explore a new view on data organisation and retrieval in a (multimedia) collection. We use probabilistic framework for indexing and interactive retrieval of the data, which enable to fill the semantic gap. Semi-automated experiments with TREC-2002 video collection showed that our approach is efficient and effective.

Original language	English
Number of pages	5
Publication status	Published - Jun 2003
Event	DELOS Workshop on Multimedia Contents in Digital Libraries 2003 - Chania, Crete, Greece Duration: 2 Jun 2003 → 3 Jun 2003

Workshop

Workshop	DELOS Workshop on Multimedia Contents in Digital Libraries 2003
Country/Territory	Greece
City	Chania, Crete
Period	2/06/03 → 3/06/03

Keywords

DB-MMR: MULTIMEDIA RETRIEVAL

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title = "Relevance feedback in probabilistic multimedia retrieval",

abstract = "In this paper we explore a new view on data organisation and retrieval in a (multimedia) collection. We use probabilistic framework for indexing and interactive retrieval of the data, which enable to fill the semantic gap. Semi-automated experiments with TREC-2002 video collection showed that our approach is efficient and effective.",

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note = "DELOS Workshop on Multimedia Contents in Digital Libraries 2003 ; Conference date: 02-06-2003 Through 03-06-2003",

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T1 - Relevance feedback in probabilistic multimedia retrieval

AU - Boldareva, Lioudmila

AU - Hiemstra, Djoerd

AU - Jonker, Willem

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N2 - In this paper we explore a new view on data organisation and retrieval in a (multimedia) collection. We use probabilistic framework for indexing and interactive retrieval of the data, which enable to fill the semantic gap. Semi-automated experiments with TREC-2002 video collection showed that our approach is efficient and effective.

AB - In this paper we explore a new view on data organisation and retrieval in a (multimedia) collection. We use probabilistic framework for indexing and interactive retrieval of the data, which enable to fill the semantic gap. Semi-automated experiments with TREC-2002 video collection showed that our approach is efficient and effective.

KW - DB-MMR: MULTIMEDIA RETRIEVAL

M3 - Paper

T2 - DELOS Workshop on Multimedia Contents in Digital Libraries 2003

Y2 - 2 June 2003 through 3 June 2003

ER -

Relevance feedback in probabilistic multimedia retrieval

Abstract

Workshop

Keywords

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Cite this