Search results
Results from the WOW.Com Content Network
Depth of processing falls on a shallow to deep continuum. [citation needed] Shallow processing (e.g., processing based on phonemic and orthographic components) leads to a fragile memory trace that is susceptible to rapid decay. Conversely, deep processing (e.g., semantic processing) results in a more durable memory trace. [1]
Deep linguistic processing is a natural language processing framework which draws on theoretical and descriptive linguistics. It models language predominantly by way of theoretical syntactic/semantic theory (e.g. CCG , HPSG , LFG , TAG , the Prague School ).
For example, in a sentence such as "He entered John's house through the front door", "the front door" is a referring expression and the bridging relationship to be identified is the fact that the door being referred to is the front door of John's house (rather than of some other structure that might also be referred to). Dialog system –
Semantic parsing maps text to formal meaning representations. This contrasts with semantic role labeling and other forms of shallow semantic processing, which do not aim to produce complete formal meanings. [9] In computer vision, semantic parsing is a process of segmentation for 3D objects. [10] [11] Major levels of linguistic structure
In VBA, an assignment of variables of type Object is a shallow copy, an assignment for all other types (numeric types, String, user defined types, arrays) is a deep copy. So the keyword Set for an assignment signals a shallow copy and the (optional) keyword Let signals a deep copy. There is no built-in method for deep copies of Objects in VBA.
These types of inferences are also referred to as "bridging inferences." For example, if a reader came across the following sentences together, they would need to have inferred that the sentences are related to one-another if they are to make any sense of the text as a whole: "Mary poured the water on the bonfire. The fire went out."
These models are shallow, two-layer neural networks that are trained to reconstruct linguistic contexts of words. Word2vec takes as its input a large corpus of text and produces a vector space , typically of several hundred dimensions , with each unique word in the corpus being assigned a corresponding vector in the space.
They claimed that the level of processing information was dependent upon the depth at which the information was being processed; mainly, shallow processing and deep processing. According to Craik and Lockhart, the encoding of sensory information would be considered shallow processing, as it is highly automatic and requires very little focus.