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By C. J. van Rijsbergen
Keith Van Rijsbergen demonstrates how diversified types of data retrieval (IR) could be mixed within the similar framework used to formulate the overall rules of quantum mechanics. all of the general effects should be utilized to handle difficulties in IR, equivalent to pseudo-relevance suggestions, relevance suggestions and ostensive retrieval. The relation with quantum computing is tested. Appendices with historical past fabric on physics and arithmetic also are integrated.
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If one intends to introduce logical reasoning within a vector space then this issue has to be confronted. The problem also has to be avoided when the Galois connection is interpreted as an inverted file relation. Intersection of the posting lists (buckets) of index terms works without any problems, so does the union of lists, and indeed this is how Boolean retrieval is implemented. But the operations intersection and union do not necessarily correspond to the equivalent logical notions for artificial classes.
However, they are strange predicates because they are not known in advance. Let us take the predicate retrieved first. This is usually specified algorithmically, and indeed in the case of Boolean retrieval is the set satisfying a Boolean expression Q, whatever that may turn out to be. The second predicate relevance is user dependent, because only a user can determine whether an object x ∈ is relevant to her or his information need. The impression given by the definitions of precision and recall is slightly misleading because they appear to have asserted that the set A is known in advance and static, neither of which in practice is the case.
Intersection of the posting lists (buckets) of index terms works without any problems, so does the union of lists, and indeed this is how Boolean retrieval is implemented. But the operations intersection and union do not necessarily correspond to the equivalent logical notions for artificial classes. They are simple convenient ways of talking logically about set-theoretic operations relying on the Stone Representation Theorem. This is convenient and comfortable in the context of retrieving textual objects, but consider now the case of retrieving from a set of image objects where retrieval is based on the contents (a largely unsolved problem).