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Article
Publication date: 20 April 2018

Xuefeng Zhang and Jiafu Su

Task recommendation is an important way for workers and requesters to get better outcomes in shorter time in crowdsourcing. This paper aims to propose an approach based on 2-tuple…

Abstract

Purpose

Task recommendation is an important way for workers and requesters to get better outcomes in shorter time in crowdsourcing. This paper aims to propose an approach based on 2-tuple fuzzy linguistic method to recommend tasks to the workers who would be capable of completing and accept them.

Design/methodology/approach

In this paper, worker’s capability-to-complete (CTC) and possibility-to-accept (PTA) for a task needs to be recommended are proposed, measured and aggregated to determine worker’s priority for task recommendation. Therein, the similarity between the recommended task and its similar tasks and worker’s performance on these similar tasks are computed and aggregated to determine worker’s CTC quantitatively. In addition, two factors of worker’s active degree and worker’s preferences to a task category are presented to reflect and determine worker’s PTA. In the process of measuring them, 2-tuple fuzzy linguistic method is used to represent, process and aggregate vague and imprecise information.

Findings

To demonstrate the implementation process and performance of the proposed approach, an illustrative example is conducted on Taskcn, a widely used Chinese online crowdsourcing market. The experimental results show that the proposed approach outperformed the self-selection approach, especially for complex or creative tasks. Moreover, comparing with task recommendation considering worker’s CTC solely, the proposed approach would be better in terms of workers’ response rate. Additionally, the use of linguistic terms and fuzzy linguistic method facilitates the expression of vague and subjective information and makes recommendation process more practical.

Research limitations/implications

In the study, the authors capture alternative workers, collect workers’ behaviors and compute workers’ CTC and PTA manually. However, as the number of tasks and alternative workers grow, the issue, i.e. how to conveniently collect workers’ behaviors and determine their CTC and PTA, becomes conspicuous and needs to be studied further.

Practical implications

The proposed approach provides an alternative way to perform tasks posted in crowdsourcing platforms. It can assist workers to contribute to right tasks, and requesters to get outcomes with high quality more efficiently.

Originality/value

This study proposes an approach to task recommendation in crowdsourcing that integrates workers’ CTC and PTA for the recommended tasks and can deal with vague and imprecise information.

Details

Kybernetes, vol. 47 no. 8
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 2 March 2015

Ming Li, Mengyue Yuan and Yingcheng Xu

In organizations, knowledge intensive activities are mainly task oriented. Finding relevant completed tasks to the new task and providing task-related knowledge to workers…

Abstract

Purpose

In organizations, knowledge intensive activities are mainly task oriented. Finding relevant completed tasks to the new task and providing task-related knowledge to workers facilitate the knowledge reuse. However, relevant tasks are not easily found in the huge amount of completed tasks. The purpose of this paper is to assist the worker to find the required knowledge for the task at hand by reusing the knowledge related to relevant competed tasks.

Design/methodology/approach

First, the task profile is constructed. Relevant degrees to categories which tasks to are derived by multi-granularity fuzzy linguistic method. The stages of completed tasks are identified by the modified KNN method. Second, similar completed tasks on categories are retrieved and then the relevant tasks are selected from the retrieved similar tasks by multi-granularity fuzzy linguistic method. Third, the worker’s current task stage is derived by calculating the similarity between the rated knowledge and the knowledge in the stage of completed tasks. Finally, the knowledge is recommend based on stage relevance, relevance of the completed tasks and importance of the knowledge.

Findings

The proposed method helps the worker find the knowledge related to the task at hand by finding and reusing the completed tasks. The experimental results show that the proposed method performs well and can fulfill the worker’s’ knowledge needs. The use of the linguistic term set with preferred granularities instead of precise numbers facilitates the expression of the opinions. The recommendation stage by stage makes the knowledge recommended more precisely. The obtained linguistic weight of the knowledge makes the recommended results understood more easily than the numerical values.

Research limitations/implications

In the study, the authors just focus on the codified knowledge recommendation. However, there is another kind of knowledge named tacit knowledge, which exists in the mind of the experts. The constructing and updating of the expert profile can be investigated. Meanwhile, the new recommendation method which considers more factors also needs to be studied further.

Practical implications

The paper includes implications for the development of the knowledge management system. The proposed approach can be applied as a tool of knowledge sharing. It facilitates the finding of the knowledge that is related to the task at hand.

Originality/value

The paper provides new ways to find the relevant tasks and the related knowledge to the task at hand. Meanwhile, the new method to recommend the knowledge stage by stage is also proposed. It expands the research in the knowledge sharing and knowledge recommendation.

Details

Kybernetes, vol. 44 no. 3
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 8 May 2017

Aravind Sesagiri Raamkumar, Schubert Foo and Natalie Pang

Systems to support literature review (LR) and manuscript preparation tend to focus on only one or two of the tasks involved. The purpose of this paper is to describe an…

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Abstract

Purpose

Systems to support literature review (LR) and manuscript preparation tend to focus on only one or two of the tasks involved. The purpose of this paper is to describe an intervention framework that redesigns a particular set of tasks, allowing for interconnectivity between the tasks and providing appropriate user interface display features for each task in a prototype system.

Design/methodology/approach

A user evaluation study was conducted on the prototype system. The system supports the three tasks: building a reading list (RL) of research papers, finding similar papers based on a set of papers and shortlisting papers from the final RL for inclusion in manuscript based on article type. A total of 119 researchers who had experience in authoring research papers, participated in the evaluation study. They had to select one of the provided 43 topics and execute the tasks offered by the system. Three questionnaires were provided for evaluating the tasks and system. Both quantitative and qualitative analyses were performed on the collected evaluation data.

Findings

Task redesign aspects had a positive impact in user evaluation for the second task of finding similar papers while improvement was found to be required for the first and third tasks. The tasks interconnectivity features seed basket and RL were helpful for the participants in conveniently searching for papers within the system. Two of the four proposed informational display features, namely, information cue labels and shared co-relations were the most preferred features of the system. Student user group found the task recommendations and the overall system to be more useful and effective than the staff group.

Originality/value

This study validates the importance of interconnected task design and novel informational display features in accentuating task-based recommendations for LR and manuscript preparatory tasks. The potential for improvement in recommendations was shown through the task redesign exercise where new requirements for the tasks were identified. The resultant prototype system helps in bridging the gap between novices and experts in terms of LR skills.

Article
Publication date: 4 July 2016

Mohammad Ehson Rangiha, Marco Comuzzi and Bill Karakostas

The purpose of this paper is to present a framework for social business process management (BPM) in which social tagging is used to capture process knowledge emerging during the…

Abstract

Purpose

The purpose of this paper is to present a framework for social business process management (BPM) in which social tagging is used to capture process knowledge emerging during the design and enactment of the processes. Process knowledge concerns both the type of activities chosen to fulfil a certain goal and the skills and experience of users in executing specific tasks. This knowledge is exploited by recommendation tools to support the design and enactment of current and future process instances.

Design/methodology/approach

The literature about traditional BPM is analysed to highlight the limitations of traditional BPM regarding management of ad hoc and semi-structured processes. Having identified this gap, an innovative BPM framework based on social tagging is proposed to address these limitations. This model is exemplified in a real case scenario and evaluated through the implementation of a prototype and a case study in real world non-profit organisation.

Findings

An overview of the social BPM framework is presented, introducing the concepts of role and task recommendation, which are supported by social tagging. The prototype shows the buildability of the social BPM framework as an extension of a Wiki platform. The case study demonstrates that the social BPM framework improves user collaborativeness in designing and executing process instances.

Research limitations/implications

The applicability of the framework is targeted to ad hoc and possibly semi-structured business processes and it does not extend to highly procedural and codified processes. A single case study limits the generalisability of the evaluation results.

Originality/value

The social BPM framework is the first to introduce task and role recommendation supported by social tagging to overcome the limitations of traditional BPM models.

Details

Business Process Management Journal, vol. 22 no. 4
Type: Research Article
ISSN: 1463-7154

Keywords

Article
Publication date: 20 November 2017

Aravind Sesagiri Raamkumar, Schubert Foo and Natalie Pang

Although many interventional approaches have been proposed to address the apparent gap between novices and experts for literature review (LR) search tasks, there have been very…

Abstract

Purpose

Although many interventional approaches have been proposed to address the apparent gap between novices and experts for literature review (LR) search tasks, there have been very few approaches proposed for manuscript preparation (MP) related tasks. The purpose of this paper is to describe a task and an incumbent technique for shortlisting important and unique papers from the reading list (RL) of researchers, meant for citation in a manuscript.

Design/methodology/approach

A user evaluation study was conducted on the prototype system which was built for supporting the shortlisting papers (SP) task along with two other LR search tasks. A total of 119 researchers who had experience in authoring research papers participated in this study. An online questionnaire was provided to the participants for evaluating the task. Both quantitative and qualitative analyses were performed on the collected evaluation data.

Findings

Graduate research students prefer this task more than research and academic staff. The evaluation measures relevance, usefulness and certainty were identified as predictors for the output quality measure “good list”. The shortlisting feature and information cues were the preferred aspects while limited data set and rote steps in the study were ascertained as critical aspects from the qualitative feedback of the participants.

Originality/value

Findings point out that researchers are clearly interested in this novel task of SP from the final RL prepared during LR. This has implications for digital library, academic databases and reference management software where this task can be included to benefit researchers at the manuscript preparatory stage of the research lifecycle.

Details

Aslib Journal of Information Management, vol. 69 no. 6
Type: Research Article
ISSN: 2050-3806

Keywords

Article
Publication date: 2 January 2018

Akira Matsuoka

To identify the reason of Japan not complying with the Financial Action Task Force (FATF) recommendation 35 and suggesting a strategic solution to overcoming the barrier.

Abstract

Purpose

To identify the reason of Japan not complying with the Financial Action Task Force (FATF) recommendation 35 and suggesting a strategic solution to overcoming the barrier.

Design/methodology/approach

Through contextual, historical, and legal analysis of the anti-money laundering (AML) measures in Japan.

Findings

This paper implies that less flexible mindsets in stone of major players in the field of AML measures in Japan are the fundamental barrier for Japan not complying with the FATF Recommendation 35, while this paper suggests better realistic ways to address the barrier.

Originality/value

The novel point of this paper is that this paper illustriously uncovers the mindsets of the major players pertaining to the Japanese AML measures in a very illustrative way, points out the underlying true barrier, and describes a useful strategy desperately needed to address the barrier.

Article
Publication date: 9 July 2018

Emmanuel Senanu Mekpor, Anthony Aboagye and Jonathan Welbeck

This paper aims to compute a measure for anti-money laundering/counter-financing of terrorism (AML/CFT) compliance and investigate its determinants.

1949

Abstract

Purpose

This paper aims to compute a measure for anti-money laundering/counter-financing of terrorism (AML/CFT) compliance and investigate its determinants.

Design/methodology/approach

Using the Financial Action Task Force (FATF) recommendations and assigning weights to them, the study computes a measure for AML compliance. Further, the determinants of AML compliance were investigated using ordinary least squares (OLS) data of 155 countries between 2004 and 2016.

Findings

The findings suggest that AML compliance have slightly improved over the years. Further, the OLS regression results show that technology, regulatory quality, bank concentration, trade openness and financial intelligence center significantly determined and improved AML compliance.

Practical implications

From the findings, it is evident that countries that wish to improve the AML compliance should focus more on technology, regulatory quality, structure of the banking sector, size of the economy and institution of financial intelligence center so as to enhance AML compliance.

Originality/value

To the best of the author’s knowledge, this paper reveals a first AML/CFT compliance index that measures the cross-country level of AML/CFT compliance from the year 2004 to 2016. Subsequently, this paper adopted an OLS econometric model to identify the key determinants of AML/CFT compliance among member states of FATF.

Details

Journal of Financial Regulation and Compliance, vol. 26 no. 3
Type: Research Article
ISSN: 1358-1988

Keywords

Article
Publication date: 9 January 2020

Duen-Ren Liu, Yun-Cheng Chou and Ciao-Ting Jian

Online news websites provide diverse article topics, such as fashion news, entertainment and movie information, to attract more users and create more benefits. Recommending movie…

Abstract

Purpose

Online news websites provide diverse article topics, such as fashion news, entertainment and movie information, to attract more users and create more benefits. Recommending movie information to users reading news online can enhance the impression of diverse information and may consequently improve benefits. Accordingly, providing online movie recommendations can improve users’ satisfactions with the website, and thus is an important trend for online news websites. This study aims to propose a novel online recommendation method for recommending movie information to users when they are browsing news articles.

Design/methodology/approach

Association rule mining is applied to users’ news and movie browsing to find latent associations between news and movies. A novel online recommendation approach is proposed based on latent Dirichlet allocation (LDA), enhanced collaborative topic modeling (ECTM) and the diversity of recommendations. The performance of proposed approach is evaluated via an online evaluation on a real news website.

Findings

The online evaluation results show that the click-through rate can be improved by the proposed hybrid method integrating recommendation diversity, LDA, ECTM and users’ online interests, which are adapted to the current browsing news. The experiment results also show that considering recommendation diversity can achieve better performance.

Originality/value

Existing studies had not investigated the problem of recommending movie information to users while they are reading news online. To address this problem, a novel hybrid recommendation method is proposed for dealing with cross-type recommendation tasks and the cold-start issue. Moreover, the proposed method is implemented and evaluated online in a real world news website, while such online evaluation is rarely conducted in related research. This work contributes to deriving user’s online preferences for cross-type recommendations by integrating recommendation diversity, LDA, ECTM and adaptive online interests. The research findings also contribute to increasing the commercial value of the online news websites.

Article
Publication date: 1 April 2006

Sarah Barbara Watstein

This paper aims to investigate the “buzz” about the University of California's Bibliographic Services Task Force report Rethinking How We Provide Bibliographic Services for the

553

Abstract

Purpose

This paper aims to investigate the “buzz” about the University of California's Bibliographic Services Task Force report Rethinking How We Provide Bibliographic Services for the University of California and begins to explore Task Force findings from a public service perspective.

Design/methodology/approach

Members of the University of California's Bibliographic Services Task Force were interviewed about their report published in December 2005, Rethinking How We Provide Bibliographic Services for the University of California.

Findings

Establishes that “search and retrieval” are of primary importance to today's library users, and that the design and delivery of bibliographic services are of equal import to public services librarians.

Practical implications

Informs and stimulates discussion about the value of “search” as service, and reinforces the importance of bibliographic services in today's information marketplace.

Originality/value

Challenges librarians and library workers to think about their roles and responsibilities with regards to the care for and tending of the entire bibliographic information space.

Details

Reference Services Review, vol. 34 no. 2
Type: Research Article
ISSN: 0090-7324

Keywords

Article
Publication date: 13 February 2024

Jia Jin, Yi He, Chenchen Lin and Liuting Diao

Social recommendation has been recognized as a kind of e-commerce with large potential, but how social recommendations influence consumer decisions is still unclear. This paper…

Abstract

Purpose

Social recommendation has been recognized as a kind of e-commerce with large potential, but how social recommendations influence consumer decisions is still unclear. This paper aims to investigate how recommendations from different social ties influence consumers’ purchase intentions through both behavior and brain activity.

Design/methodology/approach

Utilizing behavioral (N = 70) and electroencephalogram (EEG) (N = 49) experiments, this study explored participants’ behavior and brain responses after being recommended by different social ties. The data were analyzed using statistical inference and event-related potential (ERP) analysis.

Findings

Behavioral results show that social tie strength positively impacts purchase intention, which can be fitted by a logarithmic model. Moreover, recommender-to-customer similarity and product affect mediate the effect of tie strength on purchase intention serially. EEG findings show that recommendations from weak tie strength elicit larger N100, N200 and P300 amplitudes than those from strong tie strength. These results imply that weak tie strength may motivate individuals to recruit more mental resources in social recommendation, including unconscious processing of consumer attention and conscious processing of cognitive conflict and negative emotion.

Originality/value

This study considers the effects of continuous social ties on purchase intention and models them mathematically, exploring the intrinsic mechanisms by which strong and weak ties influence purchase intentions through recommender-to-customer similarity and product affect, contributing to the applications of the stimulus-organism-response (SOR) model in the field of social recommendation. Furthermore, our study adopting EEG techniques bridges the gap of relying solely on self-report by providing an avenue to obtain relatively objective findings about the consumers’ early-occurred (unconscious) attentional responses and late-occurred (conscious) cognitive and emotional responses in purchase decisions.

Details

Internet Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1066-2243

Keywords

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