Fuzzy Matching of OpenAPI Described REST Services

Peng, Cong; Goswami, Prashant; Bai, Guohua

doi:10.1016/j.procs.2018.08.081

Cited by 6 publications

(4 citation statements)

References 15 publications

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“…Nominatim uses OpenStreetMap data to find places on Earth by name and address (geocoding). He can also do the opposite -find an address for any place on the planet [19,20].…”

Section: Determining the Coordinates Of Educational Institutions And ...mentioning

confidence: 99%

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Models of the APIEd system under development to collect data on different levels of educational institutions

Nikich,

Kvashnin,

Chervonnova

et al. 2023

E3S Web Conf.

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The article discusses an approach to developing a web resource that aggregates information about educational organizations of various levels: from kindergartens to universities. The technology stack used is described, the stages of development of the main components of the system are demonstrated. The article presents the architecture of the system with a description of the operation of individual modules, including modules for determining the geo-location of an educational institution. It is shown how information about more than 150,000 educational institutions in Russia is collected on the basis of open data.

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“…Nominatim uses OpenStreetMap data to find places on Earth by name and address (geocoding). He can also do the opposite -find an address for any place on the planet [19,20].…”

Section: Determining the Coordinates Of Educational Institutions And ...mentioning

confidence: 99%

“…After removing all duplicates, invalid values and organizations whose licenses have expired, 163,510 educational organizations remained regions of Russia [20]. Of these, about 2,700 universities, 40,800 schools, and about 70,000 additional education programs.…”

Section: Development Of a Prototype Of The Apied Systemmentioning

confidence: 99%

Models of the APIEd system under development to collect data on different levels of educational institutions

Nikich,

Kvashnin,

Chervonnova

et al. 2023

E3S Web Conf.

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“…In the mining process, fuzzy logic is generally used to enrich and treat uncertainty [12], setting association rules mining for generating classifiers [13] and bridging the gap between the ambiguities of different understandings [14]. The fuzzy matching approach was slightly better than the weighted approach [15]. Fuzzy logic is also a promising approach that can significantly improve accuracy [16].…”

Section: Fuzzy Matchingmentioning

confidence: 99%

Social Media Mining with Fuzzy Text Matching: A Knowledge Extraction on Tourism After COVID-19 Pandemic

Manuaba¹,

Sentana

Astawa³

et al. 2022

Knowl. Eng. Data Sci.

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Social media mining is an emerging technique for analyzing data to extract valuable knowledge related to various domains. However, traditional text matching techniques, such as exact matching, are not always suitable for social media data, which can contain spelling mistakes, abbreviations, and variations in the use of words. Fuzzy matching is a text matching technique that can handle such variations and identify similarities between two texts, even if there are differences in spelling or phrasing. The gap in existing research is the limited use of fuzzy matching in social media mining for tourism recovery analysis. By applying fuzzy matching to social media data related to COVID-19 and tourism recovery, this research seeks to bridge this gap and extract valuable insights related to the impact of the pandemic on tourism recovery. We manually retrieved 19,462 Twitter records and differentiated the data sources using four diver parameters to indicate data related to the impact of COVID-19 on the tourism industry, such as the economy, restrictions, government policies, and vaccination. We conducted text mining analysis on the collected 7,352 words and identified 25 highly recommended words that indicated COVID-19 recovery from a tourism perspective. We separated the four words representing the tourism perspective to perform fuzzy matching as a dataset. We then used the inbound dataset on the fuzzy matching process, with the 7,352-word data collected from the text mining process. The matching process resulted in 18 words representing COVID-19 recovery from a tourism perspective.

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“…This approach is not using any semantic descriptions and does not provide support for reasoning via JSON-LD annotations. • Using fuzzy inference methods to match services considering QoS metrics [24], or denoted by OpenAPI specifications [25]. • Generating, in an automatic manner, the suitable GraphQL-based wrappers for REST APIs described by OpenAPI documents [26].…”

Section: Related Workmentioning

confidence: 99%

A Web Service Composition Method Based on OpenAPI Semantic Annotations

Netedu¹,

Buraga²,

Diac³

et al. 2019

Advances in E-Business Engineering for Ubiquitous Computing

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Automatic Web service composition is a research direction aimed to improve the process of aggregating multiple Web services to create some new, specific functionality. The use of semantics is required as the proper semantic model with annotation standards is enabling the automation of reasoning required to solve non-trivial cases. Most previous models are limited in describing service parameters as concepts of a simple hierarchy.Our proposed method is increasing the expressiveness at the parameter level, using concept properties that define attributes expressed by name and type. Concept properties are inherited. The paper also describes how parameters are matched to create, in an automatic manner, valid compositions. Additionally, the composition algorithm is practically used on descriptions of Web services implemented by REST APIs expressed by OpenAPI specifications. Our proposal uses knowledge models (ontologies) to enhance these OpenAPI constructs with JSON-LD semantic annotations in order to obtain better compositions for involved services. We also propose an adjusted composition algorithm that extends the semantic knowledge defined by our model.

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Fuzzy Matching of OpenAPI Described REST Services

Cited by 6 publications

References 15 publications

Models of the APIEd system under development to collect data on different levels of educational institutions

Models of the APIEd system under development to collect data on different levels of educational institutions

Social Media Mining with Fuzzy Text Matching: A Knowledge Extraction on Tourism After COVID-19 Pandemic

A Web Service Composition Method Based on OpenAPI Semantic Annotations

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