Representing Web Applications As Knowledge Graphs
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866914984397635584 |
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| author | Chandrasekharuni, Yogesh |
| author_facet | Chandrasekharuni, Yogesh |
| contents | Traditional methods for crawling and parsing web applications predominantly rely on extracting hyperlinks from initial pages and recursively following linked resources. This approach constructs a graph where nodes represent unstructured data from web pages, and edges signify transitions between them. However, these techniques are limited in capturing the dynamic and interactive behaviors inherent to modern web applications. In contrast, the proposed method models each node as a structured representation of the application's current state, with edges reflecting user-initiated actions or transitions. This structured representation enables a more comprehensive and functional understanding of web applications, offering valuable insights for downstream tasks such as automated testing and behavior analysis. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_17258 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Representing Web Applications As Knowledge Graphs Chandrasekharuni, Yogesh Information Retrieval Artificial Intelligence Traditional methods for crawling and parsing web applications predominantly rely on extracting hyperlinks from initial pages and recursively following linked resources. This approach constructs a graph where nodes represent unstructured data from web pages, and edges signify transitions between them. However, these techniques are limited in capturing the dynamic and interactive behaviors inherent to modern web applications. In contrast, the proposed method models each node as a structured representation of the application's current state, with edges reflecting user-initiated actions or transitions. This structured representation enables a more comprehensive and functional understanding of web applications, offering valuable insights for downstream tasks such as automated testing and behavior analysis. |
| title | Representing Web Applications As Knowledge Graphs |
| topic | Information Retrieval Artificial Intelligence |
| url | https://arxiv.org/abs/2410.17258 |