The Vector Space Model of Word Meaning Informatics 1 CG: Lecture 13 Reading: An Introduction to Latent Semantic Analysis. Discourse Processes, 25, 259–284.

First Page		Document Content
Date: 2016-02-08 08:36:36 Natural language processing Computational linguistics Semantics Vectors Machine learning Latent semantic analysis Semantic similarity Distributional semantics Word embedding Vector space model Document-term matrix Euclidean vector		The Vector Space Model of Word Meaning Informatics 1 CG: Lecture 13 Reading: An Introduction to Latent Semantic Analysis. Discourse Processes, 25, 259–284. Add to Reading List Source URL: www.inf.ed.ac.uk Download Document from Source Website File Size: 116,64 KB Share Document on Facebook

	Lecture 3, Tues Jan 24: Basic Rules of QM Tensor products are a way of building bigger vectors out of smaller ones. Let’s apply a NOT operation to the first bit, and do nothing to the second bit. That’s really the sa DocID: 1xVI0 - View Document
	An MCSAT treatment of Bit-Vectors (preliminary report) St´ephane Graham-Lengrand1,2 and Dejan Jovanovi´c1 1 2 DocID: 1xV1f - View Document
	GloVe: Global Vectors for Word Representation Jeffrey Pennington, Richard Socher, Christopher D. Manning Computer Science Department, Stanford University, Stanford, CA 94305 , , mann DocID: 1xUHr - View Document
	A Tale Of Two Solvers: Eager and Lazy Approaches to Bit-vectors? Liana Hadarean1 , Kshitij Bansal1 , Dejan Jovanovi´c3 , Clark Barrett1 , and Cesare Tinelli2 1 2 DocID: 1xU8Z - View Document
	Solving Constraints over Bit-Vectors with SAT-based Model Checking Extended Abstract Yakir Vizel1 , Alexander Nadel2 , and Sharad Malik1 2 DocID: 1xTvZ - View Document