A systematic literature review on web service clustering approaches to enhance service discovery, selection and recommendation

N Agarwal, G Sikka, LK Awasthi - Computer Science Review, 2022 - Elsevier
With the advancement of web 2.0 and the development of the Internet of Things (IoT), all
tasks can be handled with the help of handheld devices. Web APIs or web services are …

A Web service clustering method based on topic enhanced Gibbs sampling algorithm for the Dirichlet Multinomial Mixture model and service collaboration graph

Q Hu, J Shen, K Wang, J Du, Y Du - Information Sciences, 2022 - Elsevier
A method to enhance Web service clustering is proposed in this paper. Since current service
clustering methods usually face low quality of service representation vectors and lack …

WGSDMM+ GA: A genetic algorithm-based service clustering methodology assimilating dirichlet multinomial mixture model with word embedding

N Agarwal, G Sikka, LK Awasthi - Future Generation Computer Systems, 2023 - Elsevier
Advancement of web 2.0 results in the expeditious growth of services in repositories and
service portals, which raises the demand for service management. With the clusters of …

[HTML][HTML] Towards Lean Automation: Fine-Grained sentiment analysis for customer value identification

Y Xiao, C Li, M Thürer, Y Liu, T Qu - Computers & Industrial Engineering, 2022 - Elsevier
That customer value should drive product development and production is a basic tenet of the
Toyota Production System and Lean. Traditional means to extract what the customer wants …

A semantic matching approach addressing multidimensional representations for web service discovery

Z Huang, W Zhao - Expert Systems with Applications, 2022 - Elsevier
In recent years, discovering appropriate web services has become increasingly difficult as
the number of services has grown rapidly. With the goal of improving discovery performance …

Weighting construction by bag-of-words with similarity-learning and supervised training for classification models in court text documents

APC Junior, GA Wainer, WP Calixto - Applied Soft Computing, 2022 - Elsevier
Traditional models of bag-of-words for text classification are unable to identify weights for the
co-occurrence of terms, and, mainly, for this reason, they are being replaced by models of …

[HTML][HTML] PICF-LDA: a topic enhanced LDA with probability incremental correction factor for Web API service clustering

J Shen, W Huang, Q Hu - Journal of Cloud Computing, 2022 - Springer
Web API is a popular way to organize network services in cloud computing environment.
However, it is a challenge to find an appropriate service for the requestor from massive Web …

Contextual text analytics framework for citizen report classification: a case study using the indonesian language

ED Madyatmadja, BN Yahya, C Wijaya - IEEE Access, 2022 - ieeexplore.ieee.org
Citizen science has emerged in many countries to contribute to the prompt resolution of
individual field problems and has been shifted toward Information System (IS) research. In …

[HTML][HTML] Integrating semantic similarity with Dirichlet multinomial mixture model for enhanced web service clustering

N Agarwal, G Sikka, LK Awasthi - Knowledge and Information Systems, 2024 - Springer
With accelerated advancement of web 2.0, developers generally describe the functionality of
services in short natural text. Keyword-based searching techniques are not an efficient way …

A web service clustering method based on semantic similarity and multidimensional scaling analysis

C Shan, Y Du - Scientific Programming, 2021 - Wiley Online Library
Clustering web services is an effective method to solving service computing problems. The
key insight behind it is to extract the vectors based on the service description documents …