Abstract
There are major trends to advance the functionality of search engines to a more expressive semantic level. This is enabled by the advent of knowledge-sharing communities such as Wikipedia and the progress in automatically extracting entities and relationships from semistructured as well as natural-language Web sources. In addition, Semantic-Web-style ontologies, structured Deep-Web sources, and Social-Web networks and tagging communities can contribute towards a grand vision of turning the Web into a comprehensive knowledge base that can be efficiently searched with high precision. This vision and position paper discusses opportunities and challenges along this research avenue. The technical issues to be looked into include knowledge harvesting to construct large knowledge bases, searching for knowledge in terms of entities and relationships, and ranking the results of such queries.
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Weikum, G. (2010). Chapter 3: Search for Knowledge. In: Ceri, S., Brambilla, M. (eds) Search Computing. Lecture Notes in Computer Science, vol 5950. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12310-8_3
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DOI: https://doi.org/10.1007/978-3-642-12310-8_3
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