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In this paper a system based on information retrieval and text mining methods is presented.
Currently, the recovery of traceability links is mostly based on information retrieval techniques, for instance, probabilistic model, vector space model, and latent semantic indexing.
We conducted several experiments to evaluate the different parameters and challenges that can impact the automatic authentication process of Quranic verses based on information retrieval and hashing algorithms.
The network architecture we consider is based on information retrieval natively pull-based, driven by user requests, point-to-multipoint and intrinsically coupled with in-network caching.
Many state-of-the-art bug localization techniques are based on information retrieval.
Open IE evaluation is strongly based on information retrieval evaluation strategies.
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Slightly more expensive is the automatic generation of cross-links, based on statistical information retrieval methods and patterns of semantic links, that point users to other discussions with themes or information similar to their own.
But today, the unprecedented power of computation also favors a new kind of science where prediction can be based on sheer information retrieval, and form finding by simulation and optimization can replace deduction from mathematical formulas.
Nonetheless, weighing constructs proved to be a promising way of increasing the effectiveness of bug localization techniques based on structured information retrieval.
It was previously demonstrated that bug localization based on structured information retrieval benefits from the usage of more program constructs (RQ2, Section 3.7).
Thus, contrary to our initial assumption, it is not needed to remove low-contributing constructs from bug localization models based on structured information retrieval.
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