1 / 23

Lecture 4.2: Relations Basics

Lecture 4.2: Relations Basics. CS 250, Discrete Structures, Fall 2011 Nitesh Saxena * Adopted from previous lectures by Cinda Heeren , Zeph Grunschlag. Course Admin. Mid-Term 2 Exam Solution will be posted soon Should have the results by the coming weekend HW3

Télécharger la présentation

Lecture 4.2: Relations Basics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Lecture 4.2: Relations Basics CS 250, Discrete Structures, Fall 2011 NiteshSaxena *Adopted from previous lectures by CindaHeeren, ZephGrunschlag

  2. Course Admin • Mid-Term 2 Exam • Solution will be posted soon • Should have the results by the coming weekend • HW3 • Solution will be posted soon • Results should be ready by the coming weekend Lecture 4.2 -- Relations

  3. Outline • Relation Examples and Definitions • Matrix Representation • Closures Lecture 4.2 -- Relations

  4. Composing Relations Q: Suppose R defined on N by: xRy iff y = x 2 and S defined on N by: xSy iff y = x 3 What is the composition SR? Lecture 4.2 -- Relations

  5. Composing Relations xRy iff y = x 2 xSy iff y = x 3 A: These are functions (squaring and cubing) so the composite SRis just the function composition (raising to the 6th power). xSRy iff y = x 6 (in this odd case SR= RS) Q: Compose the following: 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 5 5 Lecture 4.2 -- Relations

  6. Composing Relations 1 1 1 2 2 2 3 3 3 4 4 5 A: Draw all possible shortcuts. In our case, all shortcuts went through 1: 1 1 2 2 3 3 4 Lecture 4.2 -- Relations

  7. Composing Relations: Picture 1 1 1 2 2 2 3 3 3 4 4 5 A: Draw all possible shortcuts. In our case, all shortcuts went through 1: 1 1 2 2 3 3 4 Lecture 4.2 -- Relations

  8. Composing Relations: Picture 1 1 1 2 2 2 3 3 3 4 4 5 A: Draw all possible shortcuts. In our case, all shortcuts went through 1: 1 1 2 2 3 3 4 Lecture 4.2 -- Relations

  9. Composing Relations: Picture 1 1 1 2 2 2 3 3 3 4 4 5 A: Draw all possible shortcuts. In our case, all shortcuts went through 1: 1 1 2 2 3 3 4 Lecture 4.2 -- Relations

  10. Composing Relations: Picture 1 1 1 2 2 2 3 3 3 4 4 5 A: Draw all possible shortcuts. In our case, all shortcuts went through 1: 1 1 2 2 3 3 4 Lecture 4.2 -- Relations

  11. Inverting Relations Relational inversion amounts to just reversing all the tuples of a binary relation. DEF: If R is a relation from A to B, then the relation R -1from B to A defined by setting bR -1a if and only aRb. Q: Suppose R defined from Z to N by: xRy iff y = x 2. What is the inverse R -1? Lecture 4.2 -- Relations

  12. Inverting Relations A: xRy iff y = x 2. R is the square function so R -1is square root: i.e. the union of the two square-root branches. I.e: yR -1x iff y = x 2 or in terms of square root: xR -1y iff y = ±x where x is non-negative Lecture 4.2 -- Relations

  13. The labels on the outside are for clarity. It’s really the matrix in the middle that’s important. Relations – matrix representation Suppose we have a relation R on AxB, where A={1,2,3,4}, and B={u,v,w}, R={(1,u),(1,v),(2,w),(3,w),(4,u)}. Then we can represent R as: This is a |A| x |B| matrix whose entries indicate membership in R. Lecture 4.2 -- Relations

  14. All entries in MR are 1. The \ diagonal of MR contains only 1s. The first column of MR contains no 0s. None of the above. Relations – matrix representation Some things to think about. Let R be a relation on a set A, and let MR be the matrix representation of R. Then R is reflexive if, ______________. Lecture 4.2 -- Relations

  15. All entries above the \ are 1. The first and last columns of MR contain an equal # of 0s. MR is visually symmetric about the \ diagonal. None of the above. Relations – matrix representation Some things to think about. Let R be a relation on a set A, and let MR be the matrix representation of R. Then R is symmetric if, ______________. Lecture 4.2 -- Relations

  16. MR1R2 = MR1 v MR2 MR1R2 = MR1  MR2 Relations – matrix representation Suppose we have R1 and R2 defined on A: Then R1  R2 is the bitwise “or” of the entries (Join By): Then R1  R2 is the bitwise “and” of the entries (Meet): Lecture 4.2 -- Relations

  17. Relations – composition using matrices Suppose we have R and S defined on A: Then SR corresponds to the boolean product Lecture 4.2 -- Relations

  18. Relations - A Theorem Theorem: If R is a transitive relation, then Rn R, n. How to prove? What strategy or technique should we use? Cs173 - Spring 2004

  19. Typical way of proving subset. Relations - A Theorem If R is a transitive relation, then Rn R, n. Proof by induction on n. Base case (n=1): R1 R because by definition, R1= R. Induction case: if R is transitive, then Rk R. Prove: if R is transitive, then Rk+1 R. We are trying to prove that Rk+1 R. To do this, we select an element of Rk+1 and show that it is also an element of R. Let (a,b) be an element of Rk+1. Since Rk+1 = Rk R, we know there is an x so that (a,x)  R and (x,b)  Rk. By assumption at the induction step, since Rk R, (x,b)  R. But wait, if (a,x)  R, and (x,b)  R, and R is transitive, then (a,b)  R. Cs173 - Spring 2004

  20. Relations - Another Theorem If R is a reflexive relation, then Rn is reflexive relation, n. Whiteboard! Cs173 - Spring 2004

  21. N-ary Relations • So far, we were talking about binary relations – defined on two sets. • Can be generalized to N sets • Ex: R = {(a, b, c): a < b < c}, defined on set of integers – a 3-ary relation • Applications in databases Lecture 4.2 -- Relations

  22. No (1,1), (4,4) R’ = R U {(1,1),(4,4)} is called the reflexive closure of R. Closure • Consider relation R={(1,2),(2,2),(3,3)} on the set A = {1,2,3,4}. • Is R reflexive? • What can we add to R to make it reflexive? Lecture 4.2 -- Relations

  23. Today’s Reading • Rosen 9.1 and 9.3 Lecture 4.2 -- Relations

More Related