Requirements for query evaluation in weighted information retrieval

In this article, a general mathematical framework for information retrieval models is presented, giving more insight into the evaluation mechanisms that may be used in IR. In this framework a number of requirements for operators improving recall and precision are investigated. It is shown that these...

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Published inInformation processing & management Vol. 21; no. 4; pp. 291 - 303
Main Author Bartschi, Martin
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 1985
Pergamon Press
Elsevier Science Ltd
Subjects
Online AccessGet full text
ISSN0306-4573
1873-5371
DOI10.1016/0306-4573(85)90054-8

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Abstract In this article, a general mathematical framework for information retrieval models is presented, giving more insight into the evaluation mechanisms that may be used in IR. In this framework a number of requirements for operators improving recall and precision are investigated. It is shown that these requirements can be satisfied by using descriptor weights and one combination operator only. Moreover, information items and queries—virtual items—can be treated in exactly the same way, reflecting the fact, that they both are descriptions of a number of concepts. Evaluation is performed by formulating similarity homomorphisms from query descriptions to retrieval status values that allow ranking items accordingly. For good comparisons, however, ranking must be done by the achieved proportion of perfect similarity rather than by similarity itself. In term independence models, this normalization process may satisfy the homomorphism requirement of algebra under certain conditions, but it contradicts the requirement in the term dependence case. Nevertheless, by demanding separability for the unnormalized part of the evaluation measure, it can be guaranteed that the query is evaluated to each item descriptor by descriptor, and the normalization value must be calculated only once for the whole query, using the query as a whole. Also, for each real item, the normalization value must have been calculated only once, using the item as a whole.
AbstractList A general mathematical framework for information retrieval (IR) models is introduced that offers insight into the evaluation mechanisms that may be used in IR. Several requirements for operators improving recall and precision are examined; it is shown that these requirements can be fulfilled through the use of descriptor weights and one combination operator only. Evaluation is conducted by formulating similarity homomorphisms from query descriptions to retrieval status values that permit the ranking of items accordingly. However, for good comparisons, ranking must be done by the achieved proportion of perfect similarity instead of by similarity itself. In term independence models, this normalization process may meet the homomorphism requirement of algebra under certain conditions, but it goes counter to the requirement in the case of term dependence. Nonetheless, demanding separability for the unnormalized part of the evaluation measure can ensure that the query is evaluated to each item descriptor by descriptor.
In this article, a general mathematical framework for information retrieval models is presented, giving more insight into the evaluation mechanisms that may be used in IR. In this framework a number of requirements for operators improving recall and precision are investigated. It is shown that these requirements can be satisfied by using descriptor weights and one combination operator only. Moreover, information items and queries—virtual items—can be treated in exactly the same way, reflecting the fact, that they both are descriptions of a number of concepts. Evaluation is performed by formulating similarity homomorphisms from query descriptions to retrieval status values that allow ranking items accordingly. For good comparisons, however, ranking must be done by the achieved proportion of perfect similarity rather than by similarity itself. In term independence models, this normalization process may satisfy the homomorphism requirement of algebra under certain conditions, but it contradicts the requirement in the term dependence case. Nevertheless, by demanding separability for the unnormalized part of the evaluation measure, it can be guaranteed that the query is evaluated to each item descriptor by descriptor, and the normalization value must be calculated only once for the whole query, using the query as a whole. Also, for each real item, the normalization value must have been calculated only once, using the item as a whole.
A general mathematical framework for information retrieval models is presented, giving more insight into the evaluation mechanisms that may be used in information retrieval. In this framework a number of requirements for operators improving recall and precision are investigated. These requirements can be satisfied by using descriptor weights and one combination operator only. Evaluation is performed by formulating similarity homomorphisms from query descriptions to retrieval status values that allow ranking items accordingly. By demanding separability for the unnormalised part of the evaluation measure, it can be guaranteed that the query is evaluated to each item descriptor by descriptor, and the normalisation value must be calculated only once for the whole query, using the query as a whole. Also, for each real item, the normalisation value must have been calculated only once, using the item as a whole.
Author Bärtschi, Martin
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Cites_doi 10.1016/S0306-4573(81)80004-0
10.1145/320071.320081
10.1016/0306-4573(79)90030-X
10.1145/182.358466
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Snippet In this article, a general mathematical framework for information retrieval models is presented, giving more insight into the evaluation mechanisms that may be...
A general mathematical framework for information retrieval (IR) models is introduced that offers insight into the evaluation mechanisms that may be used in IR....
A general mathematical framework for information retrieval models is presented, giving more insight into the evaluation mechanisms that may be used in...
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SubjectTerms Information retrieval
Information storage and retrieval
Information work
Mathematical models
Relevance
Searching
Subject indexing
Technical services
Terms
Theory
Weighting
Title Requirements for query evaluation in weighted information retrieval
URI https://dx.doi.org/10.1016/0306-4573(85)90054-8
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