Abstract
Today’s web is human readable where information cannot be easily processed by machines. The current existing Keyword-Based Search Engines provides an efficient way to browse the web content. But they do not consider the context of the user query or the web page and return a large result set, out of which very few are relevant to the user. Therefore, users are often confronted with the daunting task of shifting through multiple pages, to find the exact match. In addition, the Ranking factors employed by these search engines do not take into account the context or the domain of the web page. In this paper, to rank a context sensitive web page, a ranking factor is developed which uses the underlying ontology of the particular domain in which it lies. The value of this factor is computed by calculating the number of data properties present in the web page.
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Bansal, R., Jyoti, Bhatia, K.K. (2018). Ontology-Based Ranking in Search Engine. In: Aggarwal, V., Bhatnagar, V., Mishra, D. (eds) Big Data Analytics. Advances in Intelligent Systems and Computing, vol 654. Springer, Singapore. https://doi.org/10.1007/978-981-10-6620-7_12
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DOI: https://doi.org/10.1007/978-981-10-6620-7_12
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