Web Service Recommendation Based on Semantic Analysis of Web Service Specification and Enhanced Collaborative Filtering

Subbulakshmi, S.; Ramar, K.; Shaji, Ameena; Prakash, P. Veera

doi:10.1007/978-3-319-68385-0_5

Cited by 13 publications

(2 citation statements)

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“…WSs-related research has mostly focused on developing methods for identifying and suggesting WSs based on user requirements for the last two decades. The majority of previous research on WSs searching and recommendation may be classified as keyword-based [19], [20], [21], [22], [23], [24], quality of services-based [25], [26], [27], [28], [29], semantics-based [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], and network-based [41], [42], [43], [44], [45], [46] studies according to the WSs requirement descriptive models and approaches used for assessing relationship between WSs and users' requirements. In spite of the various studies on WSs retrieval and suggestions, a number of studies [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63],…”

Section: Related Workmentioning

confidence: 99%

An Empirical Study of Web Services Topics in Web Developer Discussions on Stack Overflow

et al. 2023

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Web Services (WSs) are gaining worldwide popularity due to reliable and fast intercommunication services for the development of web and mobile applications. WSs are provided to client application developers through web Application Programming Interfaces (APIs), such as YouTube API, Twitter API, Facebook API, etc. Due to the popularity of WSs, the developers frequently discuss various WSs-based application' issues on online forums, such as Stack Overflow (SO). This study aims to highlight the problems faced by client developers in the development process of WSs-based applications using the dataset of SO. The comprehension of developers' conversations on SO can give insight into the frequency, difficulty, and popularity of different WSs-related problems of developers. We downloaded 12,746 posts from SO relevant to WSs-related issues for this article. We used the topic modeling technique (LDA) to extract various topics from the SO dataset. The topics are labeled and organized into categories and sub-categories according to relationships among them. The difficulty and popularity of each topic have been analyzed. Our investigation yield several findings. First, developers focus on six topics related to WSs on SO: Client APIs development, Data Processing, Web services Authorization, Framework Support, Web APIs, and Mobile Applications. Secondly, the advantages and disadvantages of web applications topic (Fused_Popularity=0.39), from the Clients APIs development category have the highest prevalence, followed by Database (DB) and Data Processing in Applications topic (Fused_Popularity=0.38) from the Data Processing category. Third, most WSs-related topics in all categories are evolving promptly on SO, i.e., new questions are added daily about WSs development, deployment, and authorization. Fourth, the questions of type ''how'' are primarily asked in Framework support, Client APIs development, and Web APIs categories. Although, many questions in other categories are of the kind ''What''. It is also observed that WSs developers not only used SO to ask How and What types of questions but they also used SO to ask information-seeking questions (i.e., in Data processing and Client APIs development categories). Fifth, the topics relevant to Web APIs (Fused_Popularity=10.8) and Client API Development ((Fused_Popularity=9.35) categories of WSs are very popular on SO. Sixth, the questions relevant to the Web APIs (Fused_Difficulty =3) & Client APIs development (Fused_Difficulty=2.25) categories are more difficult than the other four categories. The results of our research may be helpful for the following WSs stakeholders: WSs Client application developers, WSs Educators, and WSs researchers. The WSs Educators and investigators can get more knowledge of new methods and discover novel techniques to make challenging WSs topics easy to understand. WSs framework developers can utilize our extracted WSs topics and categories to know the preferences of WSs developers that may support them in upgrading existing frameworks or developing ne...

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Section: Related Workmentioning

confidence: 99%

An Empirical Study of Web Services Topics in Web Developer Discussions on Stack Overflow

et al. 2023

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“…General awareness of some of the major machine learning algorithms has been done on the domain [5]. Like various implementations in the area [6], implementation of various classification methods was also considered [7]. K-Means clustering [8] was a method widely used in segmentation.…”

Section: Introductionmentioning

confidence: 99%

RFM-Based Customer Analysis and Product Recommendation System

Krishnan

Nair

2021

Advanced Computing and Intelligent Technologies

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In this current Covid-19 pandemic scenario, most of the supermarkets and retail stores that are present even in small towns have started giving out products online. This system classifies the customers into categories based on their Recency, Frequency and Monetary (RFM) values and recommends products to them to make sure the potentially valuable customers are retained. Based on the RFM scores, each of these customers will be divided into segments based on the scores that they obtain. To make sure that the customers are retained, better offers should be given to them, and they must also get proper product recommendations. The product recommendation system that is used is based on a concept called cognitive similarity. It is a hybrid recommendation model by taking Collaborative filtering as the base model. Comparison is also done with the existing methods to make sure that there is an improvement in the method put up. For performance evaluation, precision@k was considered. The proposed method using cognitive similarity shows an improvement of 5% in comparison with the existing methods.

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Rule Based Medicine Recommendation for Skin Diseases Using Ontology with Semantic Information

Subbulakshmi

Hari²,

jyothi³

2022

Communications in Computer and Information Science

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Web Service Recommendation Based on Semantic Analysis of Web Service Specification and Enhanced Collaborative Filtering

Cited by 13 publications

References 14 publications

An Empirical Study of Web Services Topics in Web Developer Discussions on Stack Overflow

An Empirical Study of Web Services Topics in Web Developer Discussions on Stack Overflow

RFM-Based Customer Analysis and Product Recommendation System

Rule Based Medicine Recommendation for Skin Diseases Using Ontology with Semantic Information

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