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Vector space model
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21	Informatics 1 CG – Tutorial 5 Mirella Lapata, Carina Silberer Week 6 In the lectures, we covered the vector space model and the associationist view of word meaning. Here, we will try to build a vector space model by ha Add to Reading List Source URL: www.inf.ed.ac.uk Language: English - Date: 2015-02-19 15:49:00 Syntax Grammar Natural language parsing Generative linguistics Compiler construction Parsing Parse tree Dependency grammar Garden path sentence Almond Phrase structure rules Sentence diagram
22	Building a Search Engine Model with Morphological Normalization Support 1 ˇ Jure Miji´c1 , Bojana Dalbelo Baˇsi´c1 , Jan Snajder 1 Add to Reading List Source URL: hnk.ffzg.hr Language: English - Date: 2012-11-27 12:07:35 Natural language processing Information retrieval Full text search Query expansion Ranking Vector space model Search engine indexing Document retrieval Stop words Index term Extended Boolean model Book:Information retrieval
23	Towards a Comprehensive Understanding of Context in Conceptual Spaces Carsten Keßler1 and Martin Raubal2 1 Institute for Geoinformatics, University of Münster, Germany Add to Reading List Source URL: carsten.io Language: English - Date: 2013-09-07 23:22:37 Semantics Cognitive science Abstract algebra Vectors Cognition Conceptual Spaces Conceptual system Prototype theory Conceptual model Dimension Vector space Conceptual
24	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 Language: English - 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
25	PeARS: a Peer-to-peer Agent for Reciprocated Search Aurélie Herbelot University of Trento, Centre for Mind/Brain Sciences Palazzo Fedrigotti, Corso BettiniRovereto, Italy Add to Reading List Source URL: www2016.net Language: English - Date: 2016-04-10 09:02:58 Natural language processing Semantics Computational linguistics Distributional semantics Language acquisition Vector space model Euclidean vector Peer-to-peer Information retrieval Internet privacy Latent semantic analysis Explicit semantic analysis
26	Random Indexing Explained with High Probability Add to Reading List Source URL: pars.ie Language: English - Date: 2015-09-18 07:15:22 Linear algebra Random projection Random indexing Cosine similarity Euclidean vector Vector space model Latent semantic analysis Vector Basis Singular value decomposition Matrix Euclidean space
27	Introduction to Information Retrieval ` `%%%`#_`__~~~false [0.5cm] IIR 15-2: Learning to Rank Add to Reading List Source URL: essir.uni-koblenz.de Language: English - Date: 2016-02-24 18:38:54 Machine learning Natural language processing Information retrieval evaluation Learning to rank Information retrieval Ranking Relevance Vector space model
28	Random Manhattan Indexing A Randomized Scalable Method for Semantic Similarity Measurement in L1 Normed Spaces Behrang Q. Zadeh Insight Centre for Data Analytics National University of Ireland, Galway behrang.qasemizadeh Add to Reading List Source URL: pars.ie Language: English - Date: 2015-10-23 12:32:06 Linear algebra Vectors Machine learning Dimension reduction Computational linguistics Vector space model Vector Euclidean vector Semantic similarity Normed vector space Norm Random projection
29	Investigating Context Parameters in Technology Term Recognition Behrang QasemiZadeh∗† Insight Centre of Data Analytics National University of Ireland, Galway † Department of Computer Science and Mathematics Add to Reading List Source URL: pars.ie Language: English - Date: 2015-04-03 14:11:11 Vectors Computational linguistics Abstract algebra Linear algebra Vector calculus Vector space model Euclidean vector K-nearest neighbors algorithm Vector space Distributional semantics Frame Cosine similarity
30	Investigating the Use of Distributional Semantic Models for Co-Hyponym Identification in Special Corpora Investigating the Use of Distributional Semantic Models for Co-Hyponym Identification in Special Corpora Add to Reading List Source URL: pars.ie Language: English - Date: 2015-09-10 14:27:00 Computational linguistics Semantics Vectors Distributional semantics Language acquisition Vector space model Euclidean vector Vector Co-occurrence Distribution

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