Search (6 results, page 1 of 1)

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Abstract

Purpose With the shift to an information-based society and to the de-centralisation of information, information overload has attracted a growing interest in the computer and information science research communities. However, there is no clear understanding of the meaning of the term, and while there have been many proposed definitions, there is no consensus. The goal of this work was to define the concept of "information overload". In order to do so, a concept analysis using Rodgers' approach was performed. Design/methodology/approach A concept analysis using Rodgers' approach based on a corpus of documents published between 2010 and September 2020 was conducted. One surrogate for "information overload", which is "cognitive overload" was identified. The corpus of documents consisted of 151 documents for information overload and ten for cognitive overload. All documents were from the fields of computer science and information science, and were retrieved from three databases: Association for Computing Machinery (ACM) Digital Library, SCOPUS and Library and Information Science Abstracts (LISA). Findings The themes identified from the authors' concept analysis allowed us to extract the triggers, manifestations and consequences of information overload. They found triggers related to information characteristics, information need, the working environment, the cognitive abilities of individuals and the information environment. In terms of manifestations, they found that information overload manifests itself both emotionally and cognitively. The consequences of information overload were both internal and external. These findings allowed them to provide a definition of information overload. Originality/value Through the authors' concept analysis, they were able to clarify the components of information overload and provide a definition of the concept.

Date

22. 4.2023 19:27:56

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Abstract

The thesis of this study is to propose an extended methodology for laboratory based Information Retrieval evaluation under incomplete relevance assessments. This new methodology aims to identify potential uncertainty during system comparison that may result from incompleteness. The adoption of this methodology is advantageous, because the detection of epistemic uncertainty - the amount of knowledge (or ignorance) we have about the estimate of a system's performance - during the evaluation process can guide and direct researchers when evaluating new systems over existing and future test collections. Across a series of experiments we demonstrate how this methodology can lead towards a finer grained analysis of systems. In particular, we show through experimentation how the current practice in Information Retrieval evaluation of using a measurement depth larger than the pooling depth increases uncertainty during system comparison.

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Abstract

Purpose - The purpose of this paper is to examine how different aspects of an assessor's context, in particular their knowledge of a search topic, their interest in the search topic and their confidence in assessing relevance for a topic, affect the relevance judgements made and the assessor's ability to predict which documents they will assess as being relevant. Design/methodology/approach - The study was conducted as part of the Text REtrieval Conference (TREC) HARD track. Using a specially constructed questionnaire information was sought on TREC assessors' personal context and, using the TREC assessments gathered, the responses were correlated to the questionnaire questions and the final relevance decisions. Findings - This study found that each of the three factors (interest, knowledge and confidence) had an affect on how many documents were assessed as relevant and the balance between how many documents were marked as marginally or highly relevant. Also these factors are shown to affect an assessors' ability to predict what information they will finally mark as being relevant. Research limitations/implications - The major limitation is that the research is conducted within the TREC initiative. This means that we can report on results but cannot report on discussions with the assessors. The research implications are numerous but mainly on the effect of personal context on the outcomes of a user study. Practical implications - One major consequence is that we should take more account of how we construct search tasks for IIR evaluation to create tasks that are interesting and relevant to experimental subjects. Originality/value - Examining different search variables within one study to compare the relative effects on these variables on the search outcomes.

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Abstract

The aim of the work described in this paper is to evaluate the influencing effects of query-biased summaries in web searching. For this purpose, a summarisation system has been developed, and a summary tailored to the user's query is generated automatically for each document retrieved. The system aims to provide both a better means of assessing document relevance than titles or abstracts typical of many web search result lists. Through visiting each result page at retrieval-time, the system provides the user with an idea of the current page content and thus deals with the dynamic nature of the web. To examine the effectiveness of this approach, a task-oriented, comparative evaluation between four different web retrieval systems was performed; two that use query-biased summarisation, and two that use the standard ranked titles/abstracts approach. The results from the evaluation indicate that query-biased summarisation techniques appear to be more useful and effective in helping users gauge document relevance than the traditional ranked titles/abstracts approach. The same methodology was used to compare the effectiveness of two of the web's major search engines; AltaVista and Google.

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Abstract

Purpose - The purpose of this paper is to examine how various types of TREC data can be used to better understand relevance and serve as test-bed for exploring relevance. The author proposes that there are many interesting studies that can be performed on the TREC data collections that are not directly related to evaluating systems but to learning more about human judgements of information and relevance and that these studies can provide useful research questions for other types of investigation. Design/methodology/approach - Through several case studies the author shows how existing data from TREC can be used to learn more about the factors that may affect relevance judgements and interactive search decisions and answer new research questions for exploring relevance. Findings - The paper uncovers factors, such as familiarity, interest and strictness of relevance criteria, that affect the nature of relevance assessments within TREC, contrasting these against findings from user studies of relevance. Research limitations/implications - The research only considers certain uses of TREC data and assessment given by professional relevance assessors but motivates further exploration of the TREC data so that the research community can further exploit the effort involved in the construction of TREC test collections. Originality/value - The paper presents an original viewpoint on relevance investigations and TREC itself by motivating TREC as a source of inspiration on understanding relevance rather than purely as a source of evaluation material.

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Abstract

Evaluation has always been a strong element of Information Retrieval (IR) research, much of our focus being on how we evaluate IR algorithms. As a research field we have benefited greatly from initiatives such as Cranfield, TREC, CLEF and INEX that have added to our knowledge of how to create test collections, the reliability of system-based evaluation criteria and our understanding of how to interpret the results of an algorithmic evaluation. In contrast, evaluations whose main focus is the user experience of searching have not yet reached the same level of maturity. Such evaluations are complex to create and assess due to the increased number of variables to incorporate within the study, the lack of standard tools available (for example, test collections) and the difficulty of selecting appropriate evaluation criteria for study. In spite of the complicated nature of user-centred evaluations, this form of evaluation is necessary to understand the effectiveness of individual IR systems and user search interactions. The growing incorporation of users into the evaluation process reflects the changing nature of IR within society; for example, more and more people have access to IR systems through Internet search engines but have little training or guidance in how to use these systems effectively. Similarly, new types of search system and new interactive IR facilities are becoming available to wide groups of end-users. In this special topic issue we present papers that tackle the methodological issues of evaluating interactive search systems. Methodologies can be presented at different levels; the papers by Blandford et al. and Petrelli present whole methodological approaches for evaluating interactive systems whereas those by Göker and Myrhaug and López Ostenero et al., consider what makes an appropriate evaluation methodological approach for specific retrieval situations. Any methodology must consider the nature of the methodological components, the instruments and processes by which we evaluate our systems. A number of papers have examined these issues in detail: Käki and Aula focus on specific methodological issues for the evaluation of Web search interfaces, Lopatovska and Mokros present alternate measures of retrieval success, Tenopir et al. examine the affective and cognitive verbalisations that occur within user studies and Kelly et al. analyse questionnaires, one of the basic tools for evaluations. The range of topics in this special issue as a whole nicely illustrates the variety and complexity by which user-centred evaluation of IR systems is undertaken.