Facts administration is the method of making plans, coordinating and controlling info assets. extra usually, functions have to shop and seek a large number of facts. coping with info has been constantly challenged by means of calls for from a number of parts and purposes and has advanced in parallel with advances in and computing techniques.
This quantity specializes in its contemporary advances and it truly is composed of 5 components and a complete of eighteen chapters. the 1st a part of the publication comprises 5 contributions within the zone of data retrieval & internet intelligence: a singular method of fixing index choice challenge, built-in retrieval from net of files and knowledge, bipolarity in database querying, deriving information summarization via ontologies, and granular computing for net intelligence.
The moment a part of the ebook includes 4 contributions in wisdom discovery quarter. Its 3rd half comprises 3 contributions in info integration & information safety region. the rest elements of the e-book include six contributions within the quarter of clever brokers and purposes of knowledge administration in clinical area.
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Additional info for Advances in Data Management (Studies in Computational Intelligence, Volume 223)
As can be imagined, this will especially be useful when dealing with those documents that have both text and semantic markup. Such documents can be indexed using URIs, triples and text, and the getLinkingNodes and getAssertingNodes will play a major role in retrieving those documents. These examples demonstrate that HQL can be used to query and retrieve RDF and HTML documents. Comparing RDF document retrieval with other search systems is pointless unless they provide a querying mechanism to retrieve RDF documents.
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.
Evaluating such a hybrid system is a tricky process. The system has DR components (triple matching) which render the precision and recall criteria irrelevant. But at the same time, the system also has IR components such as keyword based retrieval of documents in which case precision and recall become important. Furthermore, there are no suitable benchmarks that has documents, their semantic descriptions, some queries, and results of those queries (adjudged to be relevant by human experts). Here, we present results obtained by experimenting with the realworld AIFB SEAL  data that exercises some of the issues being addressed.
Advances in Data Management (Studies in Computational Intelligence, Volume 223)