Storage Retrieval

Download Data Management and Query Processing in Semantic Web by Sven Groppe PDF

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By Sven Groppe

The Semantic net, that's meant to set up a machine-understandable net, is presently altering from being an rising pattern to a know-how utilized in advanced real-world purposes. a few criteria and methods were built via the area large internet Consortium (W3C), e.g., the source Description Framework (RDF), which gives a normal strategy for conceptual descriptions for internet assets, and SPARQL, an RDF querying language. contemporary examples of enormous RDF facts with billions of proof contain the UniProt accomplished catalog of protein series, functionality and annotation information, the RDF info extracted from Wikipedia, and Princeton University’s WordNet. truly, querying functionality has develop into a key factor for Semantic net applications.

In his e-book, Groppe info numerous features of high-performance Semantic internet info administration and question processing. His presentation fills the space among Semantic net and database books, which both fail take into consideration the functionality problems with large-scale facts administration or fail to take advantage of the specific homes of Semantic internet information types and queries. After a basic advent to the proper Semantic internet criteria, he offers really good indexing and sorting algorithms, tailored methods for logical and actual question optimization, optimization percentages whilst utilizing the parallel database applied sciences of today’s multicore processors, and visible and embedded question languages.

Groppe basically ambitions researchers, scholars, and builders of large-scale Semantic net functions. at the complementary ebook web site readers will locate extra fabric, equivalent to a web demonstration of a question engine, and routines, and their recommendations, that problem their comprehension of the subjects presented.

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Extra info for Data Management and Query Processing in Semantic Web Databases

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9 Construct query 20 2 Semantic Web DESCRIBE queries return RDF graphs containing relevant information about the resources found for a given query pattern in the WHERE clause. However, the result of a DESCRIBE query has not been formally defined and is implementationdependent. In most implementations, replacing line (3) in Fig. x and applying this query on the RDF data in Fig. 3 would return at least all triples containing :book1, that is, {(:book1, v:author, “Fritz”), (:book1, v:author, “Egon”), (:book1, rdf:type, v:book)}.

N holds and thus h ! log2*k+1 (N/k0 ). Therefore, log2*k+1 (N/k0 ) h logk+1 (N/(2*k0 )) + 1 holds, such that the height of a B+-tree is always logarithmic to the number of stored key-value pairs and in this way self-balancing. For example, for a B+-tree with parameters k ¼ 400, k0 ¼ 200 and N ¼ 4,000,000,000 (four billions), a B+-tree storing N key-value pairs has a height of at most 4. 3 Searching Searching for the value of a key k starts at the root node, and searching proceeds in the following way: If the current node is an interior node with keys K1, .

If the current node is a leaf node with key-value pairs (k1, v1),. , (kj, vj), where ki represents a key and vi represents its value, then we found the value vi for the key k if k ¼ ki with 1 i j; otherwise, the B+-tree does not contain any such key-value pair with key k. 2 presents the accessed path in the B+-tree of Fig. 1 while searching for the value of the key 8. 4 Prefix Search in Combination with Sideways Information Passing While we have described a search for the value of a key in the previous section, we describe the search for all values of keys starting with a given prefix (also called Path for searching for the value of 8 9 3 keys 1 2 3 4 6 5 12 6 7 8 9 10 11 12 13 14 values Fig.

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