An image retrieval system based on the visualization of system relevance via documents

Denos, Nathalie; Berrut, Catherine; Mechkour, Mourad

doi:10.1007/bfb0022033

Cited by 6 publications

(3 citation statements)

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“…[20]) and techniques for visualizing relevancy (see e.g. [11]). Although we focus on the kernel of IR relevancy treatment and pay little attention to the user interface, we propose the incremental model to be embedded within systems having interaction features especially suited for IR applications (see e.g.…”

Section: Exploitation Explorationmentioning

confidence: 99%

Measuring the incremental information value of documents

Weide

Bommel

2006

Information Sciences

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The incremental searcher satisfaction model for Information Retrieval has been introduced to capture the incremental information value of documents. In this paper, from various cognitive perspectives, searcher requirements are derived in terms of the increment function. Different approaches for the construction of increment functions are identified, such as the individual and the collective approach. Translating the requirements to similarity functions leads to the so-called base similarity features and the monotonicity similarity features. We show that most concrete similarity functions in IR, such as Inclusion, JaccardÕs, DiceÕs, and Cosine coefficient, and some other approaches to similarity functions, possess the base similarity features. The Inclusion coefficient also satisfies the monotonicity features.

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Section: Exploitation Explorationmentioning

confidence: 99%

Measuring the incremental information value of documents

Weide

Bommel

2006

Information Sciences

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“…Examples of this approach include systems to select rules for retrieving documents, e.g. Denos et al (1997), and the use of abductive logic to create new rules for retrieving documents (Müller, 1998).…”

Section: P(d → Q)mentioning

confidence: 99%

A survey on the use of relevance feedback for information access systems

Ruthven

Lalmas

2003

The Knowledge Engineering Review

330

227

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Users of online search engines often find it difficult to express their need for information in the form of a query. However, if the user can identify examples of the kind of documents they require then they can employ a technique known as relevance feedback. Relevance feedback covers a range of techniques intended to improve a user's query and facilitate retrieval of information relevant to a user's information need. In this paper we survey relevance feedback techniques. We study both automatic techniques, in which the system modifies the user's query, and interactive techniques, in which the user has control over query modification. We also consider specific interfaces to relevance feedback systems and characteristics of searchers that can affect the use and success of relevance feedback systems.

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“…From studies such as those conducted by Barry and Schamber, (1998), it is clear that current models of RF, although successful at improving recall precision, are not very sophisticated in expressing what makes a document relevant to a user. Denos, Berrut, and Mechkour (1997), for example, make the good point that although users can make explicit judgements on why documents are relevant, most systems cannot use this information to improve a search.…”

Section: Introductionmentioning

confidence: 99%

Combining and selecting characteristics of information use

Ruthven

Lalmas

Rijsbergen

2002

J. Am. Soc. Inf. Sci.

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In this paper we report on a series of experiments designed to investigate the combination of term and document weighting functions in Information Retrieval. We describe a series of weighting functions, each of which is based on how information is used within documents and collections, and use these weighting functions in two types of experiments: one based on combination of evidence for ad-hoc retrieval, the other based on selective combination of evidence within a relevance feedback situation. We discuss the difficulties involved in predicting good combinations of evidence for ad-hoc retrieval, and suggest the factors that may lead to the success or failure of combination. We also demonstrate how, in a relevance feedback situation, the relevance assessments can provide a good indication of how evidence should be selected for query term weighting. The use of relevance information to guide the combination process is shown to reduce the variability inherent in combination of evidence.

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An image retrieval system based on the visualization of system relevance via documents

Cited by 6 publications

References 1 publication

Measuring the incremental information value of documents

Measuring the incremental information value of documents

A survey on the use of relevance feedback for information access systems

Combining and selecting characteristics of information use

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