Editing Semantic memory (section)

====Latent semantic analysis====
One of the more popular models is [[latent semantic analysis]] (LSA).<ref>{{cite journal | last1 = Landauer | first1 = T. K. | last2 = Dumais | first2 = S. T. | year = 1997 | title = A solution to Plato's problem: The Latent Semantic Analysis theory of the acquisition, induction, and representation of knowledge | journal = Psychological Review | volume = 104 | issue = 2| pages = 211–240 | doi=10.1037/0033-295x.104.2.211| citeseerx = 10.1.1.184.4759 | s2cid = 1144461 }}</ref> In LSA, a T × D [[matrix (mathematics)|matrix]] is constructed from a [[text corpus]], where T is the number of terms in the corpus and D is the number of documents (here "context" is interpreted as "document" and only words—or word phrases—are considered as items in memory). Each cell in the matrix is then transformed according to the equation:

<math>\mathbf{M}_{t,d}'=\frac{\ln{(1 + \mathbf{M}_{t,d})}}{-\sum_{i=0}^D P(i|t) \ln{P(i|t)}}</math>

where <math>P(i|t)</math> is the probability that context <math>i</math> is active, given that item <math>t</math> has occurred (this is obtained simply by dividing the raw frequency, <math>\mathbf{M}_{t,d}</math> by the total of the item vector, <math>\sum_{i=0}^D \mathbf{M}_{t,i}</math>).