Search results
1 – 10 of 661Jiangping Chen, Marie Bloechle, Beth Thomsett-Scott and Eileen Breen
Koraljka Golub, Xu Tan, Ying-Hsang Liu and Jukka Tyrkkö
This exploratory study aims to help contribute to the understanding of online information search behaviour of PhD students from different humanities fields, with a focus on…
Abstract
Purpose
This exploratory study aims to help contribute to the understanding of online information search behaviour of PhD students from different humanities fields, with a focus on subject searching.
Design/methodology/approach
The methodology is based on a semi-structured interview within which the participants are asked to conduct both a controlled search task and a free search task. The sample comprises eight PhD students in several humanities disciplines at Linnaeus University, a medium-sized Swedish university from 2020.
Findings
Most humanities PhD students in the study have received training in information searching, but it has been too basic. Most rely on web search engines like Google and Google Scholar for publications' search, and university's discovery system for known-item searching. As these systems do not rely on controlled vocabularies, the participants often struggle with too many retrieved documents that are not relevant. Most only rarely or never use disciplinary bibliographic databases. The controlled search task has shown some benefits of using controlled vocabularies in the disciplinary databases, but incomplete synonym or concept coverage as well as user unfriendly search interface present hindrances.
Originality/value
The paper illuminates an often-forgotten but pervasive challenge of subject searching, especially for humanities researchers. It demonstrates difficulties and shows how most PhD students have missed finding an important resource in their research. It calls for the need to reconsider training in information searching and the need to make use of controlled vocabularies implemented in various search systems with usable search and browse user interfaces.
Details
Keywords
Abstract
Details
Keywords
Matjaž Kragelj and Mirjana Kljajić Borštnar
The purpose of this study is to develop a model for automated classification of old digitised texts to the Universal Decimal Classification (UDC), using machine-learning methods.
Abstract
Purpose
The purpose of this study is to develop a model for automated classification of old digitised texts to the Universal Decimal Classification (UDC), using machine-learning methods.
Design/methodology/approach
The general research approach is inherent to design science research, in which the problem of UDC assignment of the old, digitised texts is addressed by developing a machine-learning classification model. A corpus of 70,000 scholarly texts, fully bibliographically processed by librarians, was used to train and test the model, which was used for classification of old texts on a corpus of 200,000 items. Human experts evaluated the performance of the model.
Findings
Results suggest that machine-learning models can correctly assign the UDC at some level for almost any scholarly text. Furthermore, the model can be recommended for the UDC assignment of older texts. Ten librarians corroborated this on 150 randomly selected texts.
Research limitations/implications
The main limitations of this study were unavailability of labelled older texts and the limited availability of librarians.
Practical implications
The classification model can provide a recommendation to the librarians during their classification work; furthermore, it can be implemented as an add-on to full-text search in the library databases.
Social implications
The proposed methodology supports librarians by recommending UDC classifiers, thus saving time in their daily work. By automatically classifying older texts, digital libraries can provide a better user experience by enabling structured searches. These contribute to making knowledge more widely available and useable.
Originality/value
These findings contribute to the field of automated classification of bibliographical information with the usage of full texts, especially in cases in which the texts are old, unstructured and in which archaic language and vocabulary are used.
Details
Keywords
Abstract
Details
Keywords
Abstract
Details