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Outputs (105)

Library catalogue’s search interface: Making the most of subject metadata (2024)
Journal Article
Gnoli, C., Golub, K., Haynes, D., Salaba, A., Shiri, A., & Slavic, A. (2024). Library catalogue’s search interface: Making the most of subject metadata. Knowledge Organization, 51, 169-186. https://doi.org/10.5771/0943-7444-2024-3-169

This article addresses the underutilization of knowledge organization systems (KOS) elements in online library catalogues, hindering effective subject-based search and discovery. It highlights the International Society for Knowledge Organization's in... Read More about Library catalogue’s search interface: Making the most of subject metadata.

Reputation Gaming in Crowd Technical Knowledge Sharing (2024)
Journal Article
Mazloomzadeh, I., Uddin, G., Khomh, F., & Sami, A. (2025). Reputation Gaming in Crowd Technical Knowledge Sharing. ACM transactions on software engineering and methodology, 34(1), Article 10. https://doi.org/10.1145/3691627

Stack Overrow incentive system awards users with reputation scores to ensure quality. The decentralized nature of the forum may make the incentive system prone to manipulation. This paper ooers, for the rst time, a comprehensive study of the reported... Read More about Reputation Gaming in Crowd Technical Knowledge Sharing.

An information literacy lens on community representation for participatory budgeting in Brazil (2023)
Journal Article
Cruickshank, P., & Ryan, B. (2023). An information literacy lens on community representation for participatory budgeting in Brazil. Journal of Information Literacy, 17(2), 46-68. https://doi.org/10.11645/17.2.5

This paper presents an evaluation of the information literacies used by community representatives when engaging with participatory budgeting in São Paulo City, Brazil. Using questions established from context-setting interviews with stakeholders, a f... Read More about An information literacy lens on community representation for participatory budgeting in Brazil.

Selective Query Processing: A Risk-Sensitive Selection of Search Configurations (2023)
Journal Article
Mothe, J., & Ullah, M. Z. (2024). Selective Query Processing: A Risk-Sensitive Selection of Search Configurations. ACM transactions on information systems, 42(1), https://doi.org/10.1145/3608474

In information retrieval systems, search parameters are optimized to ensure high effectiveness based on a set of past searches and these optimized parameters are then used as the system configuration for all subsequent queries. A better approach, how... Read More about Selective Query Processing: A Risk-Sensitive Selection of Search Configurations.

Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq (2023)
Journal Article
Stokes, T., Cen, H. H., Kapranov, P., Gallagher, I. J., Pitsillides, A. A., Volmar, C., Kraus, W. E., Johnson, J. D., Phillips, S. M., Wahlestedt, C., & Timmons, J. A. (2023). Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq. Advanced Genetics, 4(2), Article 2200024. https://doi.org/10.1002/ggn2.202200024

Sequencing the human genome empowers translational medicine, facilitating transcriptome-wide molecular diagnosis, pathway biology, and drug repositioning. Initially, microarrays are used to study the bulk transcriptome; but now short-read RNA sequenc... Read More about Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq.

TAFFO: The compiler-based precision tuner (2022)
Journal Article
Cattaneo, D., Chiari, M., Agosta, G., & Cherubin, S. (2022). TAFFO: The compiler-based precision tuner. SoftwareX, 20, Article 101238. https://doi.org/10.1016/j.softx.2022.101238

We present taffo, a framework that automatically performs precision tuning to exploit the performance/accuracy trade-off. In order to avoid expensive dynamic analyses, taffo leverages programmer annotations which encapsulate domain knowledge about th... Read More about TAFFO: The compiler-based precision tuner.

An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos (2022)
Journal Article
Hoffmann, B., Urquhart, N., Chalmers, K., & Guckert, M. (2022). An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos. Empirical Software Engineering, 27(7), Article 180. https://doi.org/10.1007/s10664-022-10210-w

Domain-specific languages (DSLs) are a popular approach among software engineers who demand for a tailored development interface. A DSL-based approach allows to encapsulate the intricacies of the target platform in transformations that turn DSL model... Read More about An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos.

Modelling the Impact of Individual Preferences on Traffic Policies (2022)
Journal Article
Nguyen, J., Powers, S., Urquhart, N., Farrenkopf, T., & Guckert, M. (2022). Modelling the Impact of Individual Preferences on Traffic Policies. SN Computer Science, 3(5), Article 365. https://doi.org/10.1007/s42979-022-01253-3

Urban traffic is a system always prone to overload, often approaching breakdown during rush hour times. Well adjusted modifications of traffic policies, with appropriate interventions, promise potential improvements by inducing change in both individ... Read More about Modelling the Impact of Individual Preferences on Traffic Policies.

The public library as public sphere: a longitudinal analysis (2022)
Journal Article
Appleton, L., & Hall, H. (2023). The public library as public sphere: a longitudinal analysis. Journal of Documentation, 79(1), 112-126. https://doi.org/10.1108/JD-02-2022-0031

Purpose
The research was undertaken to explore the role of the UK public library as a public sphere and the ways in which this role relates to the epistemic, community and political functions of public libraries.

Design/methodology/approach
A lo... Read More about The public library as public sphere: a longitudinal analysis.

A VMD and LSTM based hybrid model of load forecasting for power grid security (2021)
Journal Article
Lv, L., Wu, Z., Zhang, J., Tan, Z., Zhang, L., & Tian, Z. (2022). A VMD and LSTM based hybrid model of load forecasting for power grid security. IEEE Transactions on Industrial Informatics, 18(9), 6474-6482. https://doi.org/10.1109/tii.2021.3130237

As the basis for the static security of the power grid, power load forecasting directly affects the safety of grid operation, the rationality of grid planning, and the economy of supply-demand balance. However, various factors lead to drastic changes... Read More about A VMD and LSTM based hybrid model of load forecasting for power grid security.

Workplace information literacy: Measures and methodological challenges (2021)
Journal Article
Widén, G., Ahmad, F., Nikou, S., Ryan, B., & Cruickshank, P. (2021). Workplace information literacy: Measures and methodological challenges. Journal of Information Literacy, 15(2), https://doi.org/10.11645/15.2.2812

This paper focuses information literacy (IL) from a methodological perspective, addressing quantitative IL measures, suitable for evaluating the role of IL in supporting work activities. IL in workplace contexts has so far mostly been studied using... Read More about Workplace information literacy: Measures and methodological challenges.

Delphi Study of Risk to Individuals who Disclose Personal Information Online (2021)
Journal Article
Haynes, D., & Robinson, L. (2023). Delphi Study of Risk to Individuals who Disclose Personal Information Online. Journal of Information Science, 49(1), 93-106. https://doi.org/10.1177/0165551521992756

A two-round Delphi study was conducted to explore priorities for addressing online risk to individuals. A corpus of literature was created based on 69 peer-reviewed articles about privacy risk and the privacy calculus published between 2014 and 2019... Read More about Delphi Study of Risk to Individuals who Disclose Personal Information Online.

Computopia Revisited: Yoneji Masuda’s Realistic Utopianism (2020)
Journal Article
Duff, A., & Ito, Y. (2020). Computopia Revisited: Yoneji Masuda’s Realistic Utopianism. Keio communication review, 42(3), 53-74

Utopianism has always had a bad press. The whole genre, not least classics such as Thomas More’s Utopia (More, 1516), Robert Owen’s New View of Society (Owen, 1813), and William Morris’s News From Nowhere (Morris, 1891), has allegedly been shot throu... Read More about Computopia Revisited: Yoneji Masuda’s Realistic Utopianism.

On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining (2020)
Journal Article
Cha, S.-C., Wang, H., Tan, Z., Joung, Y.-J., Tseng, Y.-C., & Yeh, K.-H. (2020). On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining. IEEE Transactions on Emerging Topics in Computational Intelligence, 4(5), 641-652. https://doi.org/10.1109/tetci.2019.2938547

Intelligence mining is one of the most promising technologies for effectively extracting intelligence (and knowledge) to enhance the quality of decision-making. In Taiwan, the government curtails underground economic activities and facilitates tax ma... Read More about On Privacy Aware Carriers for Value-Possessed e-Invoices Considering Intelligence Mining.

Deep learning based emotion analysis of microblog texts (2020)
Journal Article
Xu, D., Tian, Z., Lai, R., Kong, X., Tan, Z., & Shi, W. (2020). Deep learning based emotion analysis of microblog texts. Information Fusion, 64, 1-11. https://doi.org/10.1016/j.inffus.2020.06.002

Traditional text emotion analysis methods are primarily devoted to studying extended texts, such as news reports and full-length documents. Microblogs are considered short texts that are often characterized by large noises, new words, and abbreviatio... Read More about Deep learning based emotion analysis of microblog texts.

Exploring coupled images fusion based on joint tensor decomposition (2020)
Journal Article
Lu, L., Ren, X., Yeh, K.-H., Tan, Z., & Chanussot, J. (2020). Exploring coupled images fusion based on joint tensor decomposition. Human-Centric Computing and Information Sciences, 10, Article 10 (2020). https://doi.org/10.1186/s13673-020-00215-z

Data fusion has always been a hot research topic in human-centric computing and extended with the development of artificial intelligence. Generally, the coupled data fusion algorithm usually utilizes the information from one data set to improve the e... Read More about Exploring coupled images fusion based on joint tensor decomposition.

Machine-Learning Methods for Computational Science and Engineering (2020)
Journal Article
Frank, M., Drikakis, D., & Charissis, V. (2020). Machine-Learning Methods for Computational Science and Engineering. Computation, 8(1), Article 15. https://doi.org/10.3390/computation8010015

The re-kindled fascination in machine learning (ML), observed over the last few decades, has also percolated into natural sciences and engineering. ML algorithms are now used in scientific computing, as well as in data-mining and processing. In this... Read More about Machine-Learning Methods for Computational Science and Engineering.