Search (12 results, page 1 of 1)

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Abstract

To be effective and at the same time sustainable, a community data curation model needs to be aligned with the community's current data practices, including research project activities, data types, and perceptions of data quality. Based on a survey of members of the condensed matter physics (CMP) community gathered around the National High Magnetic Field Laboratory, a large national laboratory, this article defines a model of CMP research project tasks consisting of 10 task constructs. In addition, the study develops a model of data quality perceptions by CMP scientists consisting of four data quality constructs. The paper also discusses relationships among the data quality perceptions, project roles, and demographic characteristics of CMP scientists. The findings of the study can inform the design of a CMP data curation model that is aligned and harmonized with the community's research work structure and data practices.

Type

a

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Abstract

RILM Index is a partially controlled vocabulary designated to index scholarly writings on music and related subjects, created and curated by Répertoire International de Littérature Musicale (RILM). It has been developed over 50 years and has served the music community as a primary research tool. This analytical review of the characteristics of RILM Index reveals several issues, related to the Index's history, that impinge on its usefulness. An in-progress thesaurus is presented as a possible solution to these issues. RILM Index, despite being imperfect, provides a foundation for developing an ontological structure for both indexing and information retrieval purposes.

Type

a

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Abstract

This study examined how researchers used research information systems (RIMSs) and the relationships among researchers' seniority, discipline, and types and extent of RIMS use. Most researchers used RIMSs to discover research content. Fewer used RIMSs for sharing and promoting their research. Early career researchers were more frequent users of RIMSs than were associate and full professors. Likewise, assistant professors and postdocs exhibited a higher probability of using RIMSs to promote their research than did students and full professors. Humanities researchers were the least frequent users of RIMSs. Moreover, humanities scholars used RIMSs to evaluate research less than did scholars in other disciplines. The tasks of discovering papers, monitoring the literature, identifying potential collaborators, and promoting research were predictors of higher RIMS use. Researchers who engaged in promoting their research, evaluating research, or monitoring the literature showed a greater propensity to have a public RIMS profile. Furthermore, researchers mostly agreed that not being required, having no effect on their status, not being useful, or not being a norm were reasons for not having a public RIMS profile. Humanities scholars were also more likely than social scientists to agree that having a RIMS profile was not a norm in their fields.

Type

a

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Abstract

Data fusion is currently used extensively in information retrieval for various tasks. It has proved to be a useful technology because it is able to improve retrieval performance frequently. However, in almost all prior research in data fusion, static search environments have been used, and dynamic search environments have generally not been considered. In this article, we investigate adaptive data fusion methods that can change their behavior when the search environment changes. Three adaptive data fusion methods are proposed and investigated. To test these proposed methods properly, we generate a benchmark from a historic Text REtrieval Conference data set. Experiments with the benchmark show that 2 of the proposed methods are good and may potentially be used in practice.

Type

a

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Abstract

This study examined the characteristics of users' free-text queries submitted to RILM Abstracts of Music Literature (a music literature database), and compared those queries with the controlled vocabularies used by RILM. Search-log analysis identified 11 categories of user-created search terms, and mapped each user-created search term to RILM's index terms, assessing whether it was a perfect match, a partial match, or no match. Only 30.04% of the user-created search terms did not match RILM's index terms. Most of the partial-matching and non-matching user-created search terms were personal names, work titles, and topical terms. Suggestions are offered to enhance RILM's controlled vocabularies.

Type

a

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Abstract

This study examined the characteristics of users' free-text queries submitted to RILM Abstracts of Music Literature (a music literature database), and compared those queries with the controlled vocabularies used by RILM. Search-log analysis identified 11 categories of user-created search terms, and mapped each user-created search term to RILM's index terms, assessing whether it was a perfect match, a partial match, or no match. Only 30.04% of the user-created search terms did not match RILM's index terms. Most of the partial-matching and non-matching user-created search terms were personal names, work titles, and topical terms. Suggestions are offered to enhance RILM's controlled vocabularies.

Type

a

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Abstract

Using the library and information science journals 2003-2012 in Nanjing University's Chinese Social Sciences Citation Index as data sources, the paper reveals the citation structure implied in these journals by applying social network analysis. Results show that, first, journal knowledge transfer activity in library and information science is frequent, and both the level of knowledge and discipline integration as well as the knowledge gap influenced knowledge transfer activity. According to the out-degree and in-degree, journals can be divided into three kinds. Second, based on professional bias and citation frequency, the knowledge transfer network can be divided into four blocks. With the change of discipline capacity and knowledge gap among journals, the "core-periphery" structure of the knowledge transfer network is getting weaker. Finally, regions of the knowledge transfer network evolved from a "weak-weak" subgroup to a "strong-weak" subgroup or a "weak-strong" subgroup, and then move to a "strong-strong" subgroup.

Type

a

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Abstract

How to merge and organise query results retrieved from different resources is one of the key issues in distributed information retrieval. Some previous research and experiments suggest that cluster-based document browsing is more effective than a single merged list. Cluster-based retrieval results presentation is based on the cluster hypothesis, which states that documents that cluster together have a similar relevance to a given query. However, while this hypothesis has been demonstrated to hold in classical information retrieval environments, it has never been fully tested in heterogeneous distributed information retrieval environments. Heterogeneous document representations, the presence of document duplicates, and disparate qualities of retrieval results, are major features of an heterogeneous distributed information retrieval environment that might disrupt the effectiveness of the cluster hypothesis. In this paper we report on an experimental investigation into the validity and effectiveness of the cluster hypothesis in highly heterogeneous distributed information retrieval environments. The results show that although clustering is affected by different retrieval results representations and quality, the cluster hypothesis still holds and that generating hierarchical clusters in highly heterogeneous distributed information retrieval environments is still a very effective way of presenting retrieval results to users.

Type

a

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Abstract

With the recent interest in socially created metadata as a potentially complementary resource for image description in relation to established tools such as thesauri and other forms of controlled vocabulary, questions remain about the quality and reuse value of these metadata. This study describes and examines a set of tags using quantitative and qualitative methods and assesses relationships among categories of image tags, tag assignment order, and users' perceptions of usefulness of index terms and user-contributed tags. The study found that tags provide much descriptive information about an image but that users also value and trust controlled vocabulary terms. The study found no correlation between tag length and assignment order, and tag length and its perceived usefulness. The findings of this study can contribute to the design of controlled vocabularies, indexing processes, and retrieval systems for images. In particular, the findings of the study can advance the understanding of image tagging practices, tag facet/category distributions, relative usefulness and importance of these categories to the user, and potential mechanisms for identifying useful terms.

Type

a

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Abstract

The aim of this research is twofold. On the one hand, high accuracy retrieval has been a concern of the information retrieval community for some time. We aim to investigate this issue via data fusion. On the other hand, the correlation among component results has been proven harmful to data fusion, but it has not been taken into account in data fusion algorithms. In the hope of achieving better performance, we propose a group of algorithms to eliminate the effect of uneven correlation among component results by assigning different weights to all component results or their combinations. Then the linear combination method or a variation is used for fusion. Extensive experimentation is carried out to evaluate the performances of these algorithms with six groups of component results, which are the top 10 systems submitted to Text REtrieval Conference (TREC) 6, 7, 8, 9, 2001, and 2002. The experimental results show that all eight data fusion methods involved outperform the best component system on average. Therefore, we demonstrate that the data fusion technique in general is effective with accurate retrieval results. The experimental results also demonstrate that all six methods presented in this article are effective for eliminating the effect of uneven correlation among component results. All of them outperform CombSum and five of them outperform CombMNZ on average.

Type

a

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Abstract

This study examines users' needs for bibliographic enhancement data (BIBED) in academic library catalogs. Qualitative data were collected through 30 academic users' activity logs and follow-up interviews. These 30 participants were recruited from a public university in the United States that has over 19,000 students enrolled and over 600 full-time faculty members. This study identified 19 types of BIBED useful for supporting the five user tasks proposed in the IFLA Library Reference Model and in seven other contexts, such as enhancing one's understanding, offering search instructions, and providing readers' advisory. Findings suggest that adopting BIBFRAME and Semantic Web technologies may enable academic library catalogs to provide BIBED to better meet user needs in various contexts.

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