Search (33 results, page 1 of 2)

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Abstract

The Initiative for the Evaluation of XML retrieval (INEX) provides a TREC-like platform for evaluating content-oriented XML retrieval systems. Since 2007, INEX has been using a set of precision-recall based metrics for its ad hoc tasks. The authors investigate the reliability and robustness of these focused retrieval measures, and of the INEX pooling method. They explore four specific questions: How reliable are the metrics when assessments are incomplete, or when query sets are small? What is the minimum pool/query-set size that can be used to reliably evaluate systems? Can the INEX collections be used to fairly evaluate "new" systems that did not participate in the pooling process? And, for a fixed amount of assessment effort, would this effort be better spent in thoroughly judging a few queries, or in judging many queries relatively superficially? The authors' findings validate properties of precision-recall-based metrics observed in document retrieval settings. Early precision measures are found to be more error-prone and less stable under incomplete judgments and small topic-set sizes. They also find that system rankings remain largely unaffected even when assessment effort is substantially (but systematically) reduced, and confirm that the INEX collections remain usable when evaluating nonparticipating systems. Finally, they observe that for a fixed amount of effort, judging shallow pools for many queries is better than judging deep pools for a smaller set of queries. However, when judging only a random sample of a pool, it is better to completely judge fewer topics than to partially judge many topics. This result confirms the effectiveness of pooling methods.

Date

22. 1.2011 14:20:56

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.375-394

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Abstract

Purpose - One core element of interactive information retrieval (IIR) experiments is the assignment of search tasks. The purpose of this paper is to provide an analytical review of current practice in developing those search tasks to test, observe or control task complexity and difficulty. Design/methodology/approach - Over 100 prior studies of IIR were examined in terms of how each defined task complexity and/or difficulty (or related concepts) and subsequently interpreted those concepts in the development of the assigned search tasks. Findings - Search task complexity is found to include three dimensions: multiplicity of subtasks or steps, multiplicity of facets, and indeterminability. Search task difficulty is based on an interaction between the search task and the attributes of the searcher or the attributes of the search situation. The paper highlights the anomalies in our use of these two concepts, concluding with suggestions for future methodological research related to search task complexity and difficulty. Originality/value - By analyzing and synthesizing current practices, this paper provides guidance for future experiments in IIR that involve these two constructs.

Content

Beitrag in einem Special Issue: Festschrift in honour of Nigel Ford

Date

6. 4.2015 19:31:22

Source

Journal of documentation. 70(2014) no.6, S.1118-1140

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Abstract

Purpose - This study intends to identify factors that affect relevance judgment of retrieved information as part of the 2007 TREC Legal track interactive task. Design/methodology/approach - Data were gathered and analyzed from the participants of the 2007 TREC Legal track interactive task using a questionnaire which includes not only a list of 80 relevance factors identified in prior research, but also a space for expressing their thoughts on relevance judgment in the process. Findings - This study finds that topicality remains a primary criterion, out of various options, for determining relevance, while specificity of the search request, task, or retrieved results also helps greatly in relevance judgment. Research limitations/implications - Relevance research should focus on the topicality and specificity of what is being evaluated as well as conducted in real environments. Practical implications - If multiple relevance factors are presented to assessors, the total number in a list should be below ten to take account of the limited processing capacity of human beings' short-term memory. Otherwise, the assessors might either completely ignore or inadequately consider some of the relevance factors when making judgment decisions. Originality/value - This study presents a method for reducing the artificiality of relevance research design, an apparent limitation in many related studies. Specifically, relevance judgment was made in this research as part of the 2007 TREC Legal track interactive task rather than a study devised for the sake of it. The assessors also served as searchers so that their searching experience would facilitate their subsequent relevance judgments.

Date

12. 7.2011 18:29:22

Source

Journal of documentation. 67(2011) no.2, S.264-278

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Abstract

Purpose The purpose of this paper is to propose a method to have more accurate results in comparing performance of the paired information retrieval (IR) systems with reference to the current method, which is based on the mean effectiveness scores of the systems across a set of identified topics/queries. Design/methodology/approach Based on the proposed approach, instead of the classic method of using a set of topic scores, the documents level scores are considered as the evaluation unit. These document scores are the defined document's weight, which play the role of the mean average precision (MAP) score of the systems as a significance test's statics. The experiments were conducted using the TREC 9 Web track collection. Findings The p-values generated through the two types of significance tests, namely the Student's t-test and Mann-Whitney show that by using the document level scores as an evaluation unit, the difference between IR systems is more significant compared with utilizing topic scores. Originality/value Utilizing a suitable test collection is a primary prerequisite for IR systems comparative evaluation. However, in addition to reusable test collections, having an accurate statistical testing is a necessity for these evaluations. The findings of this study will assist IR researchers to evaluate their retrieval systems and algorithms more accurately.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 67(2015) no.4, S.408-421

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Abstract

With the increasing number and diversity of search tools available, interest in the evaluation of search systems, particularly from a user perspective, has grown among researchers. More researchers are designing and evaluating interactive information retrieval (IIR) systems and beginning to innovate in evaluation methods. Maturation of a research specialty relies on the ability to replicate research, provide standards for measurement and analysis, and understand past endeavors. This article presents a historical overview of 40 years of IIR evaluation studies using the method of systematic review. A total of 2,791 journal and conference units were manually examined and 127 articles were selected for analysis in this study, based on predefined inclusion and exclusion criteria. These articles were systematically coded using features such as author, publication date, sources and references, and properties of the research method used in the articles, such as number of subjects, tasks, corpora, and measures. Results include data describing the growth of IIR studies over time, the most frequently occurring and cited authors and sources, and the most common types of corpora and measures used. An additional product of this research is a bibliography of IIR evaluation research that can be used by students, teachers, and those new to the area. To the authors' knowledge, this is the first historical, systematic characterization of the IIR evaluation literature, including the documentation of methods and measures used by researchers in this specialty.

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.4, S.745-770

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Abstract

Purpose The effort in addition to relevance is a major factor for satisfaction and utility of the document to the actual user. The purpose of this paper is to propose a method in generating relevance judgments that incorporate effort without human judges' involvement. Then the study determines the variation in system rankings due to low effort relevance judgment in evaluating retrieval systems at different depth of evaluation. Design/methodology/approach Effort-based relevance judgments are generated using a proposed boxplot approach for simple document features, HTML features and readability features. The boxplot approach is a simple yet repeatable approach in classifying documents' effort while ensuring outlier scores do not skew the grading of the entire set of documents. Findings The retrieval systems evaluation using low effort relevance judgments has a stronger influence on shallow depth of evaluation compared to deeper depth. It is proved that difference in the system rankings is due to low effort documents and not the number of relevant documents. Originality/value Hence, it is crucial to evaluate retrieval systems at shallow depth using low effort relevance judgments.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 71(2019) no.1, S.2-17

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Abstract

This paper reports on an investigation into the scholarly impact of the TRECVid (Text Retrieval and Evaluation Conference, Video Retrieval Evaluation) benchmarking conferences between 2003 and 2009. The contribution of TRECVid to research in video retrieval is assessed by analyzing publication content to show the development of techniques and approaches over time and by analyzing publication impact through publication numbers and citation analysis. Popular conference and journal venues for TRECVid publications are identified in terms of number of citations received. For a selection of participants at different career stages, the relative importance of TRECVid publications in terms of citations vis à vis their other publications is investigated. TRECVid, as an evaluation conference, provides data on which research teams 'scored' highly against the evaluation criteria and the relationship between 'top scoring' teams at TRECVid and the 'top scoring' papers in terms of citations is analyzed. A strong relationship was found between 'success' at TRECVid and 'success' at citations both for high scoring and low scoring teams. The implications of the study in terms of the value of TRECVid as a research activity, and the value of bibliometric analysis as a research evaluation tool, are discussed.

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.4, S.613-627

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Abstract

Bias quantification of retrieval functions with the help of document retrievability scores has recently evolved as an important evaluation measure for recall-oriented retrieval applications. While numerous studies have evaluated retrieval bias of retrieval functions, solid validation of its impact on realistic types of queries is still limited. This is due to the lack of well-accepted criteria for query generation for estimating retrievability. Commonly, random queries are used for approximating documents retrievability due to the prohibitively large query space and time involved in processing all queries. Additionally, a cumulative retrievability score of documents over all queries is used for analyzing retrieval functions (retrieval) bias. However, this approach does not consider the difference between different query characteristics (QCs) and their influence on retrieval functions' bias quantification. This article provides an in-depth study of retrievability over different QCs. It analyzes the correlation of lower/higher retrieval bias with different query characteristics. The presence of strong correlation between retrieval bias and query characteristics in experiments indicates the possibility of determining retrieval bias of retrieval functions without processing an exhaustive query set. Experiments are validated on TREC Chemical Retrieval Track consisting of 1.2 million patent documents.

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.8, S.1515-1532

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Abstract

A large body of research work examined, from both the query side and the user behavior side, the characteristics of medical- and health-related searches. One of the core issues in medical information retrieval (IR) is diversity of tasks that lead to diversity of categories of information needs and queries. From the evaluation perspective, another related and challenging issue is the limited availability of appropriate test collections allowing the experimental validation of medically task oriented IR techniques and systems. In this paper, we explore the peculiarities of TREC and CLEF medically oriented tasks and queries through the analysis of the differences and the similarities between queries across tasks, with respect to length, specificity, and clarity features and then study their effect on retrieval performance. We show that, even for expert oriented queries, language specificity level varies significantly across tasks as well as search difficulty. Additional findings highlight that query clarity factors are task dependent and that query terms specificity based on domain-specific terminology resources is not significantly linked to term rareness in the document collection. The lessons learned from our study could serve as starting points for the design of future task-based medical information retrieval frameworks.

Source

Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2626-2642

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Abstract

Purpose - The purpose of this paper is to report a study of how the test instrument of a simulated work task situation is used in empirical evaluations of interactive information retrieval (IIR) and reported in the research literature. In particular, the author is interested to learn whether the requirements of how to employ simulated work task situations are followed, and whether these requirements call for further highlighting and refinement. Design/methodology/approach - In order to study how simulated work task situations are used, the research literature in question is identified. This is done partly via citation analysis by use of Web of Science®, and partly by systematic search of online repositories. On this basis, 67 individual publications were identified and they constitute the sample of analysis. Findings - The analysis reveals a need for clarifications of how to use simulated work task situations in IIR evaluations. In particular, with respect to the design and creation of realistic simulated work task situations. There is a lack of tailoring of the simulated work task situations to the test participants. Likewise, the requirement to include the test participants' personal information needs is neglected. Further, there is a need to add and emphasise a requirement to depict the used simulated work task situations when reporting the IIR studies. Research limitations/implications - Insight about the use of simulated work task situations has implications for test design of IIR studies and hence the knowledge base generated on the basis of such studies. Originality/value - Simulated work task situations are widely used in IIR studies, and the present study is the first comprehensive study of the intended and unintended use of this test instrument since its introduction in the late 1990's. The paper addresses the need to carefully design and tailor simulated work task situations to suit the test participants in order to obtain the intended authentic and realistic IIR under study.

Source

Journal of documentation. 72(2016) no.3, S.394-413

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Abstract

The authors investigate factors influencing user satisfaction in information retrieval. It is evident from this study that user satisfaction is a subjective variable, which can be influenced by several factors such as system effectiveness, user effectiveness, user effort, and user characteristics and expectations. Therefore, information retrieval evaluators should consider all these factors in obtaining user satisfaction and in using it as a criterion of system effectiveness. Previous studies have conflicting conclusions on the relationship between user satisfaction and system effectiveness; this study has substantiated these findings and supports using user satisfaction as a criterion of system effectiveness.

Source

Journal of the American Society for Information Science and Technology. 61(2010) no.5, S.859-868

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Abstract

Numerous past studies have demonstrated the effectiveness of the relevance model (RM) for information retrieval (IR). This approach enables relevance or pseudo-relevance feedback to be incorporated within the language modeling framework of IR. In the traditional RM, the feedback information is used to improve the estimate of the query language model. In this article, we introduce an extension of RM in the setting of relevance feedback. Our method provides an additional way to incorporate feedback via the improvement of the document language models. Specifically, we make use of the context information of known relevant and nonrelevant documents to obtain weighted counts of query terms for estimating the document language models. The context information is based on the words (unigrams or bigrams) appearing within a text window centered on query terms. Experiments on several Text REtrieval Conference (TREC) collections show that our context-dependent relevance model can improve retrieval performance over the baseline RM. Together with previous studies within the BM25 framework, our current study demonstrates that the effectiveness of our method for using context information in IR is quite general and not limited to any specific retrieval model.

Source

Journal of the Association for Information Science and Technology. 67(2016) no.3, S.582-593

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Abstract

In information retrieval evaluation, pooling is a well-known technique to extract a sample of documents to be assessed for relevance. Given the pooled documents, a number of studies have proposed different prioritization methods to adjudicate documents for judgment. These methods follow different strategies to reduce the assessment effort. However, there is no clear guidance on how many relevance judgments are required for creating a reliable test collection. In this article we investigate and further develop methods to determine when to stop making relevance judgments. We propose a highly diversified set of stopping methods and provide a comprehensive analysis of the usefulness of the resulting test collections. Some of the stopping methods introduced here combine innovative estimates of recall with time series models used in Financial Trading. Experimental results on several representative collections show that some stopping methods can reduce up to 95% of the assessment effort and still produce a robust test collection. We demonstrate that the reduced set of judgments can be reliably employed to compare search systems using disparate effectiveness metrics such as Average Precision, NDCG, P@100, and Rank Biased Precision. With all these measures, the correlations found between full pool rankings and reduced pool rankings is very high.

Source

Journal of the Association for Information Science and Technology. 70(2019) no.1, S.49-60

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Abstract

In this article, the use of a new term extraction method for query expansion (QE) in text retrieval is investigated. The new method expands the initial query with a structured representation made of weighted word pairs (WWP) extracted from a set of training documents (relevance feedback). Standard text retrieval systems can handle a WWP structure through custom Boolean weighted models. We experimented with both the explicit and pseudorelevance feedback schemas and compared the proposed term extraction method with others in the literature, such as KLD and RM3. Evaluations have been conducted on a number of test collections (Text REtrivel Conference [TREC]-6, -7, -8, -9, and -10). Results demonstrated that the QE method based on this new structure outperforms the baseline.

Source

Journal of the Association for Information Science and Technology. 66(2015) no.11, S.2223-2234

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Abstract

Modeling multidimensional relevance in information retrieval (IR) has attracted much attention in recent years. However, most existing studies are conducted through relatively small-scale user studies, which may not reflect a real-world and natural search scenario. In this article, we propose to study the multidimensional user relevance model (MURM) on large scale query logs, which record users' various search behaviors (e.g., query reformulations, clicks and dwelling time, etc.) in natural search settings. We advance an existing MURM model (including five dimensions: topicality, novelty, reliability, understandability, and scope) by providing two additional dimensions, that is, interest and habit. The two new dimensions represent personalized relevance judgment on retrieved documents. Further, for each dimension in the enriched MURM model, a set of computable features are formulated. By conducting extensive document ranking experiments on Bing's query logs and TREC session Track data, we systematically investigated the impact of each dimension on retrieval performance and gained a series of insightful findings which may bring benefits for the design of future IR systems.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.12, S.2743-2754

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Abstract

A non-negligible fraction of user queries end up with very few or even no matching results in leading commercial web search engines. In this work, we provide a detailed characterization of such queries and show that search engines try to improve such queries by showing the results of related queries. Through a user study, we show that these query suggestions are usually perceived as relevant. Also, through a query log analysis, we show that the users are dissatisfied after submitting a query that match no results at least 88.5% of the time. As a first step towards solving these no-answer queries, we devised a large number of features that can be used to identify such queries and built machine-learning models. These models can be useful for scenarios such as the mobile- or meta-search, where identifying a query that will retrieve no results at the client device (i.e., even before submitting it to the search engine) may yield gains in terms of the bandwidth usage, power consumption, and/or monetary costs. Experiments over query logs indicate that, despite the heavy skew in class sizes, our models achieve good prediction quality, with accuracy (in terms of area under the curve) up to 0.95.

Source

Journal of the Association for Information Science and Technology. 69(2018) no.2, S.256-270

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Abstract

This study investigates the retrieval effectiveness of collaborative tags and author keywords in different environments through controlled experiments. Three test collections were built. The first collection tests the impact of tags on retrieval performance when only the title and abstract are available (the abstract environment). The second tests the impact of tags when the full text is available (the full-text environment). The third compares the retrieval effectiveness of tags and author keywords in the abstract environment. In addition, both single-word queries and phrase queries are tested to understand the impact of different query types. Our findings suggest that including tags and author keywords in indexes can enhance recall but may improve or worsen average precision depending on retrieval environments and query types. Indexing tags and author keywords for searching using phrase queries in the abstract environment showed improved average precision, whereas indexing tags for searching using single-word queries in the full-text environment led to a significant drop in average precision. The comparison between tags and author keywords in the abstract environment indicates that they have comparable impact on average precision, but author keywords are more advantageous in enhancing recall. The findings from this study provide useful implications for designing retrieval systems that incorporate tags and author keywords.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.3, S.483-500

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Abstract

We analyzed how effort in searching is associated with search output and task outcome. In a field study, we examined how students' search effort for an assigned learning task was associated with precision and relative recall, and how this was associated to the quality of learning outcome. The study subjects were 41 medical students writing essays for a class in medicine. Searching in Medline was part of their assignment. The data comprised students' search logs in Medline, their assessment of the usefulness of references retrieved, a questionnaire concerning the search process, and evaluation scores of the essays given by the teachers. Pearson correlation was calculated for answering the research questions. Finally, a path model for predicting task outcome was built. We found that effort in the search process degraded precision but improved task outcome. There were two major mechanisms reducing precision while enhancing task outcome. Effort in expanding Medical Subject Heading (MeSH) terms within search sessions and effort in assessing and exploring documents in the result list between the sessions degraded precision, but led to better task outcome. Thus, human effort compensated bad retrieval results on the way to good task outcome. Findings suggest that traditional effectiveness measures in information retrieval should be complemented with evaluation measures for search process and outcome.

Source

Journal of the American Society for Information Science and Technology. 63(2012) no.4, S.657-670

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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.

Content

Beitrag in einem Special Issue: Festschrift in honour of Nigel Ford

Source

Journal of documentation. 70(2014) no.6, S.1098-1117

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Abstract

Controlled vocabulary and subject headings in OPAC records have proven to be useful in improving search results. The authors used a survey to gather information about librarian opinions and professional use of controlled vocabulary. Data from a range of backgrounds and expertise were examined, including academic and public libraries, and technical services as well as public services professionals. Responses overall demonstrated positive opinions of the value of controlled vocabulary, including in reference interactions as well as during bibliographic instruction sessions. Results are also examined based upon factors such as age and type of librarian.