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The obvious use of increasingly parallel architectures for large-scale search applications is to execute multiple search queries simultaneously, which often results in significant increases in throughput.
The tab browsing allows users to run multiple search queries concurrently in the same browser window; not an earth shattering feature but some what handy.
Because no direct feedback is given, it is also difficult to quickly compare results for multiple search queries.
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Most academic databases give you the ability to ask for very specific information by presenting multiple search query boxes as well as archives containing only a single type of resource (such as only journal articles or only newspapers).
While using PHI-BLAST, for each query we obtain a set of patterns to initiate multiple searches per query, thereby adding an extra dimension for multiple patterns.
If this is a piggyback service offered through Safari, it would make more sense (i.e. automatically submitting search queries multiple times client-side instead of server-side displaying results for partial input).
The flexibility, ease of use and precision of the SAQP are due to (i) 'readable', interactive, expandable form constructs for specifying search constraints and object attributes; (ii) the inclusion of variables in searches, which allow search components to refer to one another; and (iii) the inclusion of multiple search components within one query.
* Power Search Tools: Allows users to send search queries to multiple search engines via one click and in one view, saving time and improving the quality of results.
The model provides a foundation for building consistent and standardized APIs to access multiple vocabularies that support lexical search queries, hierarchy navigation, and a rich set of features such as recursive subsumption (e.g., get all the children of the concept penicillin).
Siri and Snips share the same shortcomings — users expect to be able to do complicated search queries that combine multiple web services.
They explore many topics in parallel, experiment with query variations, consult multiple search engines, and gather information over many sessions.
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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