Search (6 results, page 1 of 1)

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Abstract

Purpose - This study aims to investigate the effects of different search and browse features in digital libraries (DLs) on task interactions, and what features would lead to poor user experience. Design/methodology/approach - Three operational DLs: ACM, IEEE CS, and IEEE Xplore are used in this study. These three DLs present different features in their search and browsing designs. Two information-seeking tasks are constructed: one search task and one browsing task. An experiment was conducted in a usability laboratory. Data from 35 participants are collected on a set of measures for user interactions. Findings - The results demonstrate significant differences in many aspects of the user interactions between the three DLs. For both search and browse designs, the features that lead to poor user interactions are identified. Research limitations/implications - User interactions are affected by specific design features in DLs. Some of the design features may lead to poor user performance and should be improved. The study was limited mainly in the variety and the number of tasks used. Originality/value - The study provided empirical evidence to the effects of interaction design features in DLs on user interactions and performance. The results contribute to our knowledge about DL designs in general and about the three operational DLs in particular.

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Abstract

Stereotyping is a technique used in many information systems to represent user groups and/or to generate initial individual user models. However, there has been a lack of evidence on the accuracy of their use in representing users. We propose a formal evaluation method to test the accuracy or homogeneity of the stereotypes that are based on users' explicit characteristics. Using the method, the results of an empirical testing on 11 common user stereotypes of information retrieval (IR) systems are reported. The participants' memberships in the stereotypes were predicted using discriminant analysis, based on their IR knowledge. The actual membership and the predicted membership of each stereotype were compared. The data show that "librarians/IR professionals" is an accurate stereotype in representing its members, while some others, such as "undergraduate students" and "social sciences/humanities" users, are not accurate stereotypes. The data also demonstrate that based on the user's IR knowledge a stereotype can be made more accurate or homogeneous. The results show the promise that our method can help better detect the differences among stereotype members, and help with better stereotype design and user modeling. We assume that accurate stereotypes have better performance in user modeling and thus the system performance. Limitations and future directions of the study are discussed.

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Abstract

Purpose - The purpose of this paper is to examine changes in relevance assessments, specifically the selection of relevance criteria by subjects as they move through the information search process. Design/methodology/approach - The paper examines the relevance criteria choices of 39 subjects in relation to search stage. Subjects were assigned a specific search task in a controlled test. Statistics were collected and analyzed using descriptive statistics and the chi-square goodness-of-fit tests. Findings - The statistically significant findings identified a number of commonly reported relevance criteria, which varied over an information search process for relevant and partially relevant judgments. These results provide statistical confirmations of previous studies, and extend these findings identifying specific criteria for both relevant and partially relevant judgments. Research limitations/implications - The study only examines a short duration search process and since the convenience sample of subjects were from similar backgrounds and were assigned similar tasks, the study did not explicitly examine the impact of contextual factors such as user experience, background or task in relation to relevance criteria choices. Practical implications - The paper has implications for the development of search systems which are adaptive and recognize the cognitive changes which occur during the information search process. Examining and identifying relevance criteria beyond topicality and the importance of those criteria to a user can help in the generation of better search queries. Originality/value - The paper adds more rigorous statistical analysis to the study of relevance criteria and the information search process.

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Abstract

Relevance judgment has traditionally been considered a personal and subjective matter. A user's search and the search result are treated as an isolated event. To consider the collaborative nature of information retrieval (IR) in a group/organization or even societal context, this article proposes a method that measures relevance based on group/peer consensus. The method can be used in IR experiments. In this method, the relevance of a document is decided by group consensus, or more specifically, by the number of users (or experiment participants) who retrieve it for the same search question. The more users who retrieve it, the more relevant the document will be considered. A user's search performance can be measured by a relevance score based on this notion. The article reports the results of an experiment using this method to compare the search performance of different types of users. Related issues with the method and future directions are also discussed

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Abstract

An integrated information retrieval system generally contains multiple databases that are inconsistent in terms of their content and indexing. This paper proposes a rough set-based transfer (RST) model for integration of the concepts of document databases using various indexing languages, so that users can search through the multiple databases using any of the current indexing languages. The RST model aims to effectively create meaningful transfer relations between the terms of two indexing languages, provided a number of documents are indexed with them in parallel. In our experiment, the indexing concepts of two databases respectively using the Thesaurus of Social Science (IZ) and the Schlagwortnormdatei (SWD) are integrated by means of the RST model. Finally, this paper compares the results achieved with a cross-concordance method, a conditional probability based method and the RST model.

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Abstract

This article reports the results of a study that investigated effects of four user characteristics on users' mental models of information retrieval systems: educational and professional status, first language, academic background, and computer experience. The repertory grid technique was used in the study. Using this method, important components of information retrieval systems were represented by nine concepts, based on four IR experts' judgments. Users' mental models were represented by factor scores that were derived from users' matrices of concept ratings on different attributes of the concepts. The study found that educational and professional status, academic background, and computer experience had significant effects in differentiating users on their factor scores. First language had a borderline effect, but the effect was not significant enough at a = 0.05 level. Specific different views regarding IR systems among different groups of users are described and discussed. Implications of the study for information science and IR system designs are suggested