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was used as a query target.
Consider Fig. 3, and suppose the query target is finding the records generated in weekdays (from Monday to Friday).
Aggregation queries target all records, rather than specific ones, and therefore naturally ensure access and pattern confidentiality.
In our chosen test cases, we assume that service clients' queries target the same service type in the same RI.
The performance of the system is illustrated with examples from various application domains and for different types of queries (target search as well as similarity search).
Suppose that the query target is the set of records whose "Longitude" ranges from 23.73 to 23.74, "Latitude" ranges from 61.48 to 61.50, and "Date" is Wednesday or Thursday.
Web Search is increasingly entity centric; as a large fraction of common queries target specific entities, search results get progressively augmented with semi-structured and multimedia information about those entities.
The basic idea of LOR is to "learn" a rank function instead of traditional regression or classification function to predict the activity of candidate compounds for the query target.
The system analyzes the consistence among iterations: if the current feedback is consistent with the previous ones, higher probabilities are assigned to the images that are similar to the query target.
To this end, we developed a web interface that provides direct HTML links to Ensembl[9] UCSC[10], and NCBI[11] genome browsers for each exact or near-exact matches to a query target found in a collection of large sequence databases.
A query target with DrugFEATURE score higher than 1.9 is considered druggable.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com