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Relevance feedback is a feature of some information retrieval systems. The idea behind relevance feedback is to take the results that are initially returned from a given query, to gather user feedback, and to use information about whether or not those results are relevant to perform a new query. We can usefully distinguish between three types ...
The Rocchio algorithm is based on a method of relevance feedback found in information retrieval systems which stemmed from the SMART Information Retrieval System developed between 1960 and 1964. Like many other retrieval systems, the Rocchio algorithm was developed using the vector space model .
This is the so called pseudo-relevance feedback (PRF). [6] Pseudo-relevance feedback is efficient in average but can damage results for some queries, [7] especially difficult ones since the top retrieved documents are probably non-relevant. Pseudo-relevant documents are used to find expansion candidate terms that co-occur with many query terms. [8]
This way a document may be somewhat relevant if it matches some of the queried terms and will be returned as a result, whereas in the Standard Boolean model it wasn't. [ 1 ] Thus, the extended Boolean model can be considered as a generalization of both the Boolean and vector space models; those two are special cases if suitable settings and ...
In some cases language features may create many duplicate expressions. For instance, C macros , where macro expansions may result in common subexpressions not apparent in the original source code. Compilers need to be judicious about the number of temporaries created to hold values.
Relevance feedback is a feature that helps users determine if the results returned for their queries meet their information needs. In other words, relevance is assessed relative to an information need, not a query. A document is relevant if it addresses the stated information need, not because it just happens to contain all the words in the ...
The ROSE compiler framework, developed at Lawrence Livermore National Laboratory (LLNL), is an open-source software compiler infrastructure to generate source-to-source analyzers and translators for multiple source languages including C (C89, C99, Unified Parallel C (UPC)), C++ (C++98, C++11), Fortran (77, 95, 2003), OpenMP, Java, Python, and PHP.
C11 mainly standardizes features already supported by common contemporary compilers, and includes a detailed memory model to better support multiple threads of execution. Due to delayed availability of conforming C99 implementations, C11 makes certain features optional, to make it easier to comply with the core language standard.