Perspectives and Key Technologies of Semantic Web Search
Konstantinos I Kotis2009
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Abstract
Current keyword-based Web search engines (e.g. Google i ) provide access to thousands of people for billions of indexed Web pages. Although the amount of irrelevant results returned due to polysemy (one word with several meanings) and synonymy (several words with one meaning) linguistic phenomena tends to be reduced (e.g. by narrowing the search using human-directed topic hierarchies as in Yahoo ii ), still the uncontrolled publication of Web pages requires an alternative to the way Web information is authored and retrieved today. This alternative can be the technologies of the new era of the Semantic Web.
Key takeaways
- This article aims to provide an insight on current technologies used in Semantic Web search, focusing on two issues: a) the automatic construction of a formal query (query ontology) and b) the querying of a collection of knowledge sources whose structure is not known a priory (distributed and semantically heterogeneous documents).
- Furthermore, to be able to execute a semantic matching, the document (in addition to the query) must also provide its semantics.
- Latest research work (Lopez et al, 2006a; builds towards a method for a) automatically approximating the meaning of a simple NL query, reformulating it into an ontology (query ontology) that expresses the intended meaning of the query terms and of the query string as a whole, b) retrieving the most "relative" SWDs based on their similarity with the query ontology.
- However, to be able to retrieve SWDs, the query must be further processed towards the construction of the query ontology.
- The ranking of retrieved SWDs is computed based on how well they match to the query ontology: This is determined by the number of mappings (mapped concepts) between the query ontology and a SWD .
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