Software Resource Recommendation for Process Execution Based on the Organization’s Profile

Biazus, Miller; Santos, Carlos Habekost dos; Takeda, Larissa Narumi; Oliveira, José Palazzo M. de; Fantinato, Marcelo; Mendling, Jan; Thom, Lucinéia Heloisa

doi:10.1007/978-3-030-27618-8_9

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…Scholars Mehdi and David [18] took into account factors such as the different categories in the resource systems and the educational process of the resource subjects and proposed a recommendation model that is sensitive to students' learning ability level, and the proposed model contains three main function modules, namely the student ability level characterization module, the candidate learning resource characterization module, and the resource recommendation module. In the current knowledge push or resource recommendation services, the main reason for the inability to fully explore the information of the potential relationships between students, learning projects, and learning resources is the sparseness of data [19][20][21][22]. In order to improve the accuracy of knowledge push or resource recommendation, Yang et al [23] applied a resource content feature extraction optimization algorithm based on multi-source data fusion to the dynamic tracking of students' learning preferences; in order to avoid the problem of undiversified content that is commonly seen during resource recommendation, they also proposed a multi-user joint-comparison algorithm to evaluate the candidate learning resources.…”

Section: Introductionmentioning

confidence: 99%

A Resource Recommendation Algorithm for Online English Learning Systems Based on Learning Ability Evaluation

Zhou

2021

Int. J. Emerg. Technol. Learn.

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Mature online English learning platforms should provide students with necessary learning resources, ensure efficient access to learning projects, and offer the optimal learning experience. However, the traditional recommendation methods for English learning resources cannot satisfy the in-depth learning demand of students. To solve the problem, this paper designs a resource recommendation algorithm for online English learning systems based on learning ability evaluation. Firstly, the workflow of the designed algorithm was introduced, and a four-layer test system was developed for students’ English learning ability evaluation. Next, an English learning ability evaluation method was proposed based on the maximum expectation algorithm, as well as the estimation methods for parameters like learning ability, degree of discrimination, difficulty, and guess coefficient. Experimental results demonstrated the good effect of the proposed resource recommendation algorithm. The research findings provide a reference for resource recommendation of other online learning systems.

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Section: Introductionmentioning

confidence: 99%

A Resource Recommendation Algorithm for Online English Learning Systems Based on Learning Ability Evaluation

Zhou

2021

Int. J. Emerg. Technol. Learn.

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Investigating business process changes: a framework for identifying outdated process models

Avila,

Sanchez,

Fantinato

et al. 2024

BPMJ

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PurposeDue to a lack of event data, organizations using Business Process Management may struggle to update their process models whenever business process changes occur. As such, alternative data sources are needed to detect and monitor business process changes.Design/methodology/approachWe conducted interviews with domain experts to analyze real business processes and classify any identified changes using Reijers and Mansar's framework on business process redesign heuristics. Based on the results, we proposed a taxonomy of entity groups as well as a method for identifying entities in process models based on the taxonomy. With this method, we define how to create a mapping between entities and process models, forming a framework to identify outdated process models through monitoring the entities.FindingsThe analyses of 25 business processes let us define three entity groups that form our taxonomy. We confirmed the feasibility of our entity identification method by classifying process elements of 85 pre-existing process models according to the taxonomy. Regarding the mapping that forms the basis of our framework, we found it necessary to define requirement recommendations to ensure its consistency and rigor.Originality/valueThis study offers a novel approach to handling the challenges of business process change. By emphasizing the identification and use of entities in the analysis of business process changes, it provides a holistic approach to monitoring the work systems of an organization.

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Software Resource Recommendation for Process Execution Based on the Organization’s Profile

Cited by 2 publications

References 17 publications

A Resource Recommendation Algorithm for Online English Learning Systems Based on Learning Ability Evaluation

A Resource Recommendation Algorithm for Online English Learning Systems Based on Learning Ability Evaluation

Investigating business process changes: a framework for identifying outdated process models

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