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In other words, it enables access to both HW documents and SW data, incorporating indexing information from the neighboring nodes. Specifically, the wordset queries can use anchor text in the HW to retrieve SW nodes, and wordset pair queries can express disambiguation information using the ISA edges encoded in the SW for semantic search of HW documents. Before we go into the details of the query language, let us first define some more utility functions/relations in addition to the four in the previous section: homeURI: N -> Set(URI) indexWords : NN -> PowerSet(STRINGS) hasTriples: DN -> PowerSet(NN x NN x NN) hasLiteral: LN -> STRINGS URI denotes a string that must satisfy the URI syntax requirement (RFC 3986), while STRINGS denotes a set of words, phrases, and other fragments.
311–322. 1353383 28. org/tpch/ 29. : Index selection in relational databases. In: FODO, pp. 487–500 (1985) Integrated Retrieval from Web of Documents and Data Krishnaprasad Thirunarayan and Trivikram Immaneni1 Abstract. The Semantic Web is evolving into a property-linked web of data, conceptually different from but contained in the Web of hyperlinked documents. Data Retrieval techniques are typically used to retrieve data from the Semantic Web while Information Retrieval techniques are used to retrieve documents from the Hypertext Web.
But note that all of the AIFB web pages are not indexed and PDF documents and the likes are ignored. Moreover, SITAR indexes and retrieves RDF files too. SITAR allows users to simply enter a set of keywords which is then automatically plugged into the query getDocsByIndexOrContent. So, the query peter haase returns 299 documents which are a mix of HTML and OWL documents (it also retrieves a PDF document URI). Note that in all of the above queries, the user is using intuitive keywords to explore the RDF data.