PPT-1 Vector Space Model for IR:

Implementation Notes CSC 575 Intelligent Information Retrieval These notes are based in part on notes by Dr Raymond J Mooney at the University of Texas at Austin 2 Implementation Issues for Ranking System. Scott Wen-tau Yih . (Microsoft Research). Joint work with. . Vahed Qazvinian . (University of . Michigan). Measuring Semantic Word Relatedness. How related are words “movie” and “popcorn”?. Real Vector Spaces. Subspaces. Linear Independence. Basis and Dimension. Row Space, Column Space, and Nullspace. Rank and Nullity. 2. 5-2 Subspaces. A . subset. . W. of a vector space . V. is called a . Daniel Svozil. based on excelent video lectures by Gilbert Strang, MIT. http://ocw.mit.edu/OcwWeb/Mathematics/18-06Spring-2005/VideoLectures/index.htm. Lectur. e. 5, Lecture 6. Transposes. How to write tra. More formally: Definitions. Definition: A . stream. is a sequence whose . codomain. . is a non empty set.. Definition: A. structure . is a . tuple. (. G, L, F. ) where . G. = (. V,E. ) is a directed graph with vertex set . & Subspaces. Kristi Schmit. Definitions. A subset W of vector space V is called a . subspace . of V . iff. The. . zero vector of V is in W.. W. is closed under vector addition, for each . u. . The matrix . C. has . M. rows and . N. columns, . M. < . N. If we have set this up correctly, the rows of . C. are independent. Nonholonomic (including the pseudo ones) constraints. (If not, do a row reduction and rewrite the constraints) . This lecture will be recorded and . you will be able to download it. Dr . Damian Giaouris. http://www.staff.ncl.ac.uk/damian.giaouris/. State Space. Very difficult to be studied => so we use computers . 2014: Anders Melen. 2015: Rachel Temple. The Nature of Statistical Learning Theory by V. Vapnik. 1. Table of Contents. Empirical Data Modeling. What is Statistical Learning Theory. Model of Supervised Learning. Lexical Semantics. 2. Information Retrieval System. IR. System. Query String. Document. corpus. Ranked. Documents. 1. Doc1. 2. Doc2. 3. Doc3. .. .. The Vector-Space Model. Graphic Representation. INTRODUCTION. An approach for classification that was developed in the computer science community in the 1990s.. Generalization of a classifier called the Maximal Margin Classifier.. HYPERPLANE. In a . Lexical Semantics. 2. Information Retrieval System. IR. System. Query String. Document. corpus. Ranked. Documents. 1. Doc1. 2. Doc2. 3. Doc3. .. .. The Vector-Space Model. Graphic Representation. 4.1 Vectors in . R. n. 4.2 Vector Spaces. 4.3 Subspaces of Vector Spaces. 4.4 Spanning Sets and Linear Independence. 4.5 Basis and Dimension. 4.6 Rank of a Matrix and Systems of Linear Equations. Scott Wen-tau Yih . (Microsoft Research). Joint work with. . Vahed Qazvinian . (University of . Michigan). Measuring Semantic Word Relatedness. How related are words “movie” and “popcorn”?. . H. HABEEB RANI. Assistant professor of Mathematics. Department of mathematics. Hajee. . Karutha. . Rowther. . Howdia. College. VECTOR SPACES. Definition. Examples. THEOREM. Subspaces.