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Ontologies for Knowledge Representation
Published in Archana Patel, Narayan C. Debnath, Bharat Bhushan, Semantic Web Technologies, 2023
Knowledge representation is done in the most efficient way when ontologies take the leading role. Knowledge discovery applications are widely used where end-users write complex search requests to retrieve information. These users may not be able to grasp the semantic relationship between the data stored. Such a difficulty can be overcome by representing the knowledge and interactive queries using ontologies. Like any other technology evolving today developing semantic web, technology is also being motivated and benefitted by several opportunities including Semantic web services: Semantic web services are built around universal standards for the interchange of semantic data, which makes it easy for programmers to combine data from different sources and services without losing meaning. Semantic web services can also be used by automatic programs that run without any connection to a web browser. The semantic descriptions are registered in public registries that help the intelligent agents to migrate from one service registry to another and find required web services for the user.Semantic search engines: With the initiation of the Semantic Web, the resources on the Web are represented semantically using ontologies, and search engines can be built where queries can be executed within the context of some ontology. Swoogle is an example of a semantic web search engine for ontologies and documents saved on the web in the form of RDF and RDFS. It uses a collection of crawlers to discover the RDF and HTML documents [42].
Information Retrieval and Semantic Search
Published in Anuradha D. Thakare, Shilpa Laddha, Ambika Pawar, Hybrid Intelligent Systems for Information Retrieval, 2023
Anuradha D. Thakare, Shilpa Laddha, Ambika Pawar
Because it is written primarily for programmed machine handling, a semantic web document is not quite the same as a normal document (e.g., site page, email, and insightful article), but it is comprehensible. In addition, unlike hyperlinks between Web papers, semantic web document joins are named with meanings. To resolve these issues, an ontology ranking algorithm that is based on a “rational surfer model” rather than “random surfer model,” Onto Rank, is presented in [19]. A web crawler called Swoogle [18] is used to look through ontology documents on the Web.
Semantically Linked Media for Interactive User-Centric Services
Published in Hassnaa Moustafa, Sherali Zeadally, Media Networks: Architectures, Applications, and Standards, 2016
Violeta Damjanovic, Thomas Kurz, Georg Güntner, Sebastian Schaffert, Lyndon Nixon
Swoogle* allows a user to search through ontologies and browse the Web of Data. It uses an archive functionality to identify and provide different versions of the Semantic Web documents.
A comprehensive review from hyperlink to intelligent technologies based personalized search systems
Published in Journal of Management Analytics, 2019
When different users fire the same search query, even a state of art search engine returns the same result, irrespective of the user submitting the query (Salonen and Karjaluoto, 2016). For example, if a user is from the technical side and usually searches for laptops, computers or mobiles, then an incomplete or erroneous query search such as Apple should retrieve results related to Apple mobiles by intermediary expanding the query string rather than returning the results of some fruit. There are several types of traditional personalized search systems which are already been discussed in the literature. However, most of these search systems failed in satisfying the personalized user requirements without having explicit ratings/feedbacks from the users (Bennett et al., 2012). Furthermore, such systems can’t handle the second generation big data as these systems need not require only scalability, partial failure support, etc. but also need to support multiple analytic methods on varied data types, as well as the ability to respond in real time. Ding et al. (2004) designed a semantic web based meta search tool, i.e. ‘Swoogle.’ The proposed tool will calculate proximity between various web documents using metadata. The authors computed the ontology rank to determine the semantic significance of the web document. They claimed that popular search engines could work well only with natural languages and hence can’t take benefit of SWDs due to failure to understand their structure. The proposed system can explore various SWDs through multiple crawlers.