Editing Semantic memory (section)

====Hyperspace Analogue to Language (HAL)====
The Hyperspace Analogue to Language (HAL) model<ref>Lund, K., Burgess, C. & Atchley, R. A. (1995). Semantic and associative priming in a high-dimensional semantic space. ''Cognitive Science Proceedings (LEA)'', 660-665.</ref><ref>{{cite journal | last1 = Lund | first1 = K. | last2 = Burgess | first2 = C. | year = 1996 | title = Producing high-dimensional semantic spaces from lexical co-occurrence | journal = Behavior Research Methods, Instruments, and Computers | volume = 28 | issue = 2| pages = 203–208 | doi=10.3758/bf03204766| doi-access = free }}</ref> considers context only as the words that immediately surround a given word. HAL computes an NxN matrix, where N is the number of words in its lexicon, using a 10-word reading frame that moves incrementally through a corpus of text. Like SAM, any time two words are simultaneously in the frame, the association between them is increased, that is, the corresponding cell in the NxN matrix is incremented. The bigger the distance between the two words, the smaller the amount by which the association is incremented (specifically, <math>\Delta=11-d</math>, where <math>d</math> is the distance between the two words in the frame).