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Article
Publication date: 5 February 2018

Sanjeev K. Sunny and Mallikarjun Angadi

The purpose of this study is to carry out a systematic literature review for evidence-based assessment of the effectiveness of thesaurus in digital information retrieval

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Abstract

Purpose

The purpose of this study is to carry out a systematic literature review for evidence-based assessment of the effectiveness of thesaurus in digital information retrieval systems. It also aimed to identify the evaluation methods, evaluation measures and data collection tools which may be used in evaluating digital information retrieval systems.

Design/methodology/approach

A systematic literature review (SLR) of 344 publications from LISA and 238 from Scopus has been carried out to identify the evaluation studies for analysis, and 15 evaluation studies have been analyzed.

Findings

This study presents evidences for the effectiveness of thesaurus in digital information retrieval systems. Various methods for evaluating digital information systems have been identified. Also, a wide range of evaluation measures and data collection tools have been identified.

Research limitations/implications

The study was limited to the literature published in English language and indexed in LISA and Scopus. The evaluation methods, evaluation measures and data collection tools identified in this study may be used to design more cognizant evaluation studies for digital information retrieval systems.

Practical implications

The findings have significant implications for the administrators of any type of digital information retrieval systems in making more informed decisions toward implementation of thesaurus in resource description and access to digital collections.

Originality/value

This study extends our knowledge on the potentials of thesauri in digital information retrieval systems. It also provides cues for designing more cognizant evaluation studies for digital information systems.

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Article
Publication date: 9 April 2019

Aabid Hussain, Sumeer Gul, Tariq Ahmad Shah and Sheikh Shueb

The purpose of this study is to explore the retrieval effectiveness of three image search engines (ISE) – Google Images, Yahoo Image Search and Picsearch in terms of their…

Abstract

Purpose

The purpose of this study is to explore the retrieval effectiveness of three image search engines (ISE) – Google Images, Yahoo Image Search and Picsearch in terms of their image retrieval capability. It is an effort to carry out a Cranfield experiment to know how efficient the commercial giants in the image search are and how efficient an image specific search engine is.

Design/methodology/approach

The keyword search feature of three ISEs – Google images, Yahoo Image Search and Picsearch – was exploited to make search with keyword captions of photos as query terms. Selected top ten images were used to act as a testbed for the study, as images were searched in accordance with features of the test bed. Features to be looked for included size (1200 × 800), format of images (JPEG/JPG) and the rank of the original image retrieved by ISEs under study. To gauge the overall retrieval effectiveness in terms of set standards, only first 50 result hits were checked. Retrieval efficiency of select ISEs were examined with respect to their precision and relative recall.

Findings

Yahoo Image Search outscores Google Images and Picsearch both in terms of precision and relative recall. Regarding other criteria – image size, image format and image rank in search results, Google Images is ahead of others.

Research limitations/implications

The study only takes into consideration basic image search feature, i.e. text-based search.

Practical implications

The study implies that image search engines should focus on relevant descriptions. The study evaluated text-based image retrieval facilities and thereby offers a choice to users to select best among the available ISEs for their use.

Originality/value

The study provides an insight into the effectiveness of the three ISEs. The study is one of the few studies to gauge retrieval effectiveness of ISEs. Study also produced key findings that are important for all ISE users and researchers and the Web image search industry. Findings of the study will also prove useful for search engine companies to improve their services.

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The Electronic Library , vol. 37 no. 1
Type: Research Article
ISSN: 0264-0473

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Article
Publication date: 8 May 2017

Christiane Behnert and Dirk Lewandowski

The purpose of this paper is to demonstrate how to apply traditional information retrieval (IR) evaluation methods based on standards from the Text REtrieval Conference…

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1785

Abstract

Purpose

The purpose of this paper is to demonstrate how to apply traditional information retrieval (IR) evaluation methods based on standards from the Text REtrieval Conference and web search evaluation to all types of modern library information systems (LISs) including online public access catalogues, discovery systems, and digital libraries that provide web search features to gather information from heterogeneous sources.

Design/methodology/approach

The authors apply conventional procedures from IR evaluation to the LIS context considering the specific characteristics of modern library materials.

Findings

The authors introduce a framework consisting of five parts: search queries, search results, assessors, testing, and data analysis. The authors show how to deal with comparability problems resulting from diverse document types, e.g., electronic articles vs printed monographs and what issues need to be considered for retrieval tests in the library context.

Practical implications

The framework can be used as a guideline for conducting retrieval effectiveness studies in the library context.

Originality/value

Although a considerable amount of research has been done on IR evaluation, and standards for conducting retrieval effectiveness studies do exist, to the authors’ knowledge this is the first attempt to provide a systematic framework for evaluating the retrieval effectiveness of twenty-first-century LISs. The authors demonstrate which issues must be considered and what decisions must be made by researchers prior to a retrieval test.

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Article
Publication date: 1 March 1991

Suliman Al‐Hawamdeh, Rachel de Vere, Geoff Smith and Peter Willett

Full‐text documents are usually searched by means of a Boolean retrieval algorithm that requires the user to specify the logical relationships between the terms of a…

Abstract

Full‐text documents are usually searched by means of a Boolean retrieval algorithm that requires the user to specify the logical relationships between the terms of a query. In this paper, we summarise the results to date of a continuing programme of research at the University of Sheffield to investigate the use of nearest‐neighbour retrieval algorithms for full‐text searching. Given a natural‐language query statement, our methods result in a ranking of the paragraphs comprising a full‐text document in order of decreasing similarity with the query, where the similarity for each paragraph is determined by the number of keyword stems that it has in common with the query. A full‐text document test collection has been created to allow systematic tests of retrieval effectiveness to be carried out. Experiments with this collection demonstrate that nearest‐neighbour searching provides a means for paragraph‐based access to full‐text documents that is of comparable effectiveness to both Boolean and hypertext searching and that index term weighting schemes which have been developed for the searching of bibliographical databases can also be used to improve the effectiveness of retrieval from full‐text databases. A current project is investigating the extent to which a paragraph‐based full‐text retrieval system can be used to augment the explication facilities of an expert system on welding.

Details

Online Review, vol. 15 no. 3/4
Type: Research Article
ISSN: 0309-314X

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Article
Publication date: 1 August 1997

A. Macfarlane, S.E. Robertson and J.A. Mccann

The progress of parallel computing in Information Retrieval (IR) is reviewed. In particular we stress the importance of the motivation in using parallel computing for text…

Abstract

The progress of parallel computing in Information Retrieval (IR) is reviewed. In particular we stress the importance of the motivation in using parallel computing for text retrieval. We analyse parallel IR systems using a classification defined by Rasmussen and describe some parallel IR systems. We give a description of the retrieval models used in parallel information processing. We describe areas of research which we believe are needed.

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Journal of Documentation, vol. 53 no. 3
Type: Research Article
ISSN: 0022-0418

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Book part
Publication date: 10 February 2012

Ben Carterette, Evangelos Kanoulas and Emine Yilmaz

Purpose — The overall quality of an information retrieval system depends on many different aspects of the system and its users' information seeking behaviour, such as the…

Abstract

Purpose — The overall quality of an information retrieval system depends on many different aspects of the system and its users' information seeking behaviour, such as the speed of the system, the user interface, the query language and the features provided by the engine. One of the most important aspects is the effectiveness of the retrieval system, i.e. its ability to retrieve items that are relevant to the information need of an end user. This chapter focuses on methods for measuring effectiveness, in particular focusing on recent work that more directly models the utility of an engine to its users.

Methodology/approach — We discuss traditional approaches to effectiveness evaluation based on test collections, then transition to approaches based on test collections along with explicit models of user interaction with search results. We contrast this with approaches for which the user is ‘in the loop’, such as user studies and online evaluations.

Research limitations/implications — If it were possible to model users perfectly, we could directly estimate the utility of a search engine to its users; this would undoubtedly have a transformative effect on information retrieval and web search research. In practice, this goal will never be achievable because users exhibit far too much variability in how they approach the search engine, and furthermore provide valuable feedback that models and simulations cannot provide. Nevertheless, better models of user interaction will help develop better web search engines for a wider variety of tasks more rapidly.

Originality/value of paper — This is the first work that surveys recent work on user model-based evaluation and places it in a context with traditional evaluation based on the Cranfield paradigm.

Details

Web Search Engine Research
Type: Book
ISBN: 978-1-78052-636-2

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Article
Publication date: 1 August 2004

A. MacFarlane, S.E. Robertson and J.A. McCann

In this paper methods for both speeding up passage processing and examining more passages using parallel computers are explored. The number of passages processed are…

Abstract

In this paper methods for both speeding up passage processing and examining more passages using parallel computers are explored. The number of passages processed are varied in order to examine the effect on retrieval effectiveness and efficiency. The particular algorithm applied has previously been used to good effect in Okapi experiments at TREC. This algorithm and the mechanism for applying parallel computing to speed up processing are described.

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Aslib Proceedings, vol. 56 no. 4
Type: Research Article
ISSN: 0001-253X

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Article
Publication date: 12 April 2013

Jin Zhang, Wei Fei and Taowen Le

The purpose of this paper to investigate the effectiveness of selected search features in the major English and Chinese search engines and compare the search engines…

Abstract

Purpose

The purpose of this paper to investigate the effectiveness of selected search features in the major English and Chinese search engines and compare the search engines’ retrieval effectiveness.

Design/approach/methodology

The search engines Google, Google China, and Baidu were selected for this study. Common search features such as title search, basic search, exact phrase search, PDF search, and URL search, were identified and used. Search results from using the five features in the search engines were collected and compared. One‐way ANOVA and regression analysis were used to compare the retrieval effectiveness of the search engines.

Findings

It was found that Google achieved the best retrieval performance with all five search features among the three search engines. Moreover Google achieved the best webpage ranking performance.

Practical implications

The findings of this study improve the understanding of English and Chinese search engines and the differences between them in terms of search features, and can be used to assist users in choosing appropriate and effective search strategies when they search for information on the internet.

Originality/value

The original contributions of this paper are that the Chinese and English search engines in both languages are compared for retrieval effectiveness. Five search features were evaluated, compared, and analysed in the two different language environments by using the discounted cumulative gain method.

Details

Online Information Review, vol. 37 no. 2
Type: Research Article
ISSN: 1468-4527

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Article
Publication date: 1 December 1998

Mounia Lalmas and Ian Ruthven

In this paper we report on a theoretical model of structured document indexing and retrieval based on the Dempster‐Shafer Theory of Evidence. This includes a description…

Abstract

In this paper we report on a theoretical model of structured document indexing and retrieval based on the Dempster‐Shafer Theory of Evidence. This includes a description of our model of structured document retrieval, the representation of structured documents, the representation of individual components, how components are combined, details of the combination process, and how relevance is captured within the model. We also present a detailed account of an implementation of the model, and an evaluation scheme designed to test the effectiveness of our model. Finally we report on the details and results of a series of experiments performed to investigate the characteristics of the model.

Details

Journal of Documentation, vol. 54 no. 5
Type: Research Article
ISSN: 0022-0418

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Article
Publication date: 8 July 2010

Elaine Ménard

This paper seeks to examine image retrieval within two different contexts: a monolingual context where the language of the query is the same as the indexing language and a…

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1158

Abstract

Purpose

This paper seeks to examine image retrieval within two different contexts: a monolingual context where the language of the query is the same as the indexing language and a multilingual context where the language of the query is different from the indexing language. The study also aims to compare two different approaches for the indexing of ordinary images representing common objects: traditional image indexing with the use of a controlled vocabulary and free image indexing using uncontrolled vocabulary.

Design/methodology/approach

This research uses three data collection methods. An analysis of the indexing terms was employed in order to examine the multiplicity of term types assigned to images. A simulation of the retrieval process involving a set of 30 images was performed with 60 participants. The quantification of the retrieval performance of each indexing approach was based on the usability measures, that is, effectiveness, efficiency and satisfaction of the user. Finally, a questionnaire was used to gather information on searcher satisfaction during and after the retrieval process.

Findings

The results of this research are twofold. The analysis of indexing terms associated with all the 3,950 images provides a comprehensive description of the characteristics of the four non‐combined indexing forms used for the study. Also, the retrieval simulation results offers information about the relative performance of the six indexing forms (combined and non‐combined) in terms of their effectiveness, efficiency (temporal and human) and the image searcher's satisfaction.

Originality/value

The findings of the study suggest that, in the near future, the information systems could benefit from allowing an increased coexistence of controlled vocabularies and uncontrolled vocabularies, resulting from collaborative image tagging, for example, and giving the users the possibility to dynamically participate in the image‐indexing process, in a more user‐centred way.

Details

Aslib Proceedings, vol. 62 no. 4/5
Type: Research Article
ISSN: 0001-253X

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