Sentence examples for retrieval question from inspiring English sources

At Google, his primary research interest is developing fast, powerful, and scalable deep learning models for information retrieval, question answering, and other language understanding tasks.

However, one of the challenges of research in this area is the continuous evolution of semantic linguistic resources that express world knowledge to support NLP tasks, such as information extraction, information retrieval, question and answer systems, text summarization, semantic annotation of texts, among others.

In the final recognition test for items presented as foils in the preceding main experiment, foils were more accurately recognized if they had previously been presented with a conceptual self/other retrieval question than an agentic self/other retrieval question.

The Dependent model captures this by assuming that performance on a retrieval question reflects the mean performance on the other questions regarding that event (the episodic factor E; see Experimental Procedures and Supplemental Information).

The hit rate was significantly higher for foils that had been presented with a Conceptual than Agentic retrieval question during the preceding source memory test (Conceptual: mean proportion correct = 0.66, SEM = 0.03; Agentic: mean proportion correct = 0.57, standard error of the mean (SEM) = 0.03; t(17) = 3.18, P = 0.005).

Using sessions previously saved through the MEMOS tool to tackle specific retrieval questions was significantly faster and more accurate than trying to use standard rediscovery methods.

There are password retrieval questions, unlike other wallet services where you might have to remember a mnemonic or risk losing your account permanently.

Our findings fully support prior work that has found evidence supporting the theory that of the two types of information retrieval questions, recognition questions are of lesser complexity and more likely to trigger memory as the information is provided as a clue within the question itself, whereas in recall questions the subject must, devoid of clues, independently retrieve 'the memory' [ 35].

Natural language processing (NLP), which is the "understanding" of the natural human language by computers, involves machine translation, information retrieval, and question answering.

Word vectors with such semantic relationships could be used to improve many existing NLP applications, such as machine translation, information retrieval, and question response systems.

The inevitability of such retrieval is questioned, however, by recent evidence that the brain activity correlates of general memory retrieval may be under more voluntary control than has been previously assumed (e.g. Dzulkifli & Wilding, 2005; Herron & Rugg, 2003; Rissman, Greely, & Wagner, 2010).