Binary relation
In mathematics, a binary relation on a set A is a collection of ordered pairs of elements of A. In other words, it is a subset of the Cartesian product A^{2} = A × A. More generally, a binary relation between two sets A and B is a subset of A × B. The terms correspondence, dyadic relation and 2place relation are synonyms for binary relation.
An example is the "divides" relation between the set of prime numbers P and the set of integers Z, in which every prime p is associated with every integer z that is a multiple of p (but with no integer that is not a multiple of p). In this relation, for instance, the prime 2 is associated with numbers that include −4, 0, 6, 10, but not 1 or 9; and the prime 3 is associated with numbers that include 0, 6, and 9, but not 4 or 13.
Binary relations are used in many branches of mathematics to model concepts like "is greater than", "is equal to", and "divides" in arithmetic, "is congruent to" in geometry, "is adjacent to" in graph theory, "is orthogonal to" in linear algebra and many more. The concept of function is defined as a special kind of binary relation. Binary relations are also heavily used in computer science.
A binary relation is the special case n = 2 of an nary relation R ⊆ A_{1} × … × A_{n}, that is, a set of ntuples where the jth component of each ntuple is taken from the jth domain A_{j} of the relation. An example for a ternary relation on Z×Z×Z is " ... lies between ... and ...", containing e.g. the triples (5,2,8), (5,8,2), and (−4,9,−7).
In some systems of axiomatic set theory, relations are extended to classes, which are generalizations of sets. This extension is needed for, among other things, modeling the concepts of "is an element of" or "is a subset of" in set theory, without running into logical inconsistencies such as Russell's paradox.
Contents
Formal definition
A binary relation R between arbitrary sets (or classes) X (the set of departure) and Y (the set of destination or codomain) is specified by its graph G, which is a subset of the Cartesian product X × Y. The binary relation R itself is usually identified with its graph G, but some authors define it as an ordered triple (X, Y, G), which is otherwise referred to as a correspondence.^{[1]}
The statement (x, y) ∈ G is read "x is Rrelated to y", and is denoted by xRy or R(x, y). The latter notation corresponds to viewing R as the characteristic function of the subset G of X × Y, i.e. R(x, y) equals to 1 (true), if (x, y) ∈ G, and 0 (false) otherwise.
The order of the elements in each pair of G is important: if a ≠ b, then aRb and bRa can be true or false, independently of each other. Resuming the above example, the prime 3 divides the integer 9, but 9 doesn't divide 3.
The domain of R is the set of all x such that xRy for at least one y. The range of R is the set of all y such that xRy for at least one x. The field of R is the union of its domain and its range.^{[2]}^{[3]}^{[4]}
Is a relation more than its graph?
This section may contain misleading parts.
(September 2015)

According to the definition above, two relations with identical graphs but different domains or different codomains are considered different. For example, if , then , , and are three distinct relations, where is the set of integers, is the set of real numbers and is the set of natural numbers.
Especially in set theory, binary relations are often defined as sets of ordered pairs, identifying binary relations with their graphs. The domain of a binary relation is then defined as the set of all such that there exists at least one such that , the range of is defined as the set of all such that there exists at least one such that , and the field of is the union of its domain and its range.^{[2]}^{[3]}^{[4]}
A special case of this difference in points of view applies to the notion of function. Many authors insist on distinguishing between a function's codomain and its range. Thus, a single "rule," like mapping every real number x to x^{2}, can lead to distinct functions and , depending on whether the images under that rule are understood to be reals or, more restrictively, nonnegative reals. But others view functions as simply sets of ordered pairs with unique first components. This difference in perspectives does raise some nontrivial issues. As an example, the former camp considers surjectivity—or being onto—as a property of functions, while the latter sees it as a relationship that functions may bear to sets.
Either approach is adequate for most uses, provided that one attends to the necessary changes in language, notation, and the definitions of concepts like restrictions, composition, inverse relation, and so on. The choice between the two definitions usually matters only in very formal contexts, like category theory.
Example
ball  car  doll  gun  

John  +  −  −  − 
Mary  −  −  +  − 
Venus  −  +  −  − 
ball  car  doll  gun  

John  +  −  −  − 
Mary  −  −  +  − 
Ian  −  −  −  − 
Venus  −  +  −  − 
Example: Suppose there are four objects {ball, car, doll, gun} and four persons {John, Mary, Ian, Venus}. Suppose that John owns the ball, Mary owns the doll, and Venus owns the car. Nobody owns the gun and Ian owns nothing. Then the binary relation "is owned by" is given as
 R = ({ball, car, doll, gun}, {John, Mary, Ian, Venus}, {(ball, John), (doll, Mary), (car, Venus)}).
Thus the first element of R is the set of objects, the second is the set of persons, and the last element is a set of ordered pairs of the form (object, owner).
The pair (ball, John), denoted by _{ball}R_{John} means that the ball is owned by John.
Two different relations could have the same graph. For example: the relation
 ({ball, car, doll, gun}, {John, Mary, Venus}, {(ball, John), (doll, Mary), (car, Venus)})
is different from the previous one as everyone is an owner. But the graphs of the two relations are the same.
Nevertheless, R is usually identified or even defined as G(R) and "an ordered pair (x, y) ∈ G(R)" is usually denoted as "(x, y) ∈ R".^{[5]}
Special types of binary relations
Some important types of binary relations R between two sets X and Y are listed below. To emphasize that X and Y can be different sets, some authors call such binary relations heterogeneous.^{[6]}^{[7]}
Uniqueness properties:
 injective (also called leftunique^{[8]}): for all x and z in X and y in Y it holds that if xRy and zRy then x = z. For example, the green relation in the diagram is injective, but the red relation is not, as it relates e.g. both x = −5 and z = +5 to y = 25.
 functional (also called univalent^{[9]} or rightunique^{[8]} or rightdefinite^{[10]}): for all x in X, and y and z in Y it holds that if xRy and xRz then y = z; such a binary relation is called a partial function. Both relations in the picture are functional. An example for a nonfunctional relation can be obtained by rotating the red graph clockwise by 90 degrees, i.e. by considering the relation x=y^{2} which relates e.g. x=25 to both y=5 and z=+5.
 onetoone (also written 1to1): injective and functional. The green relation is onetoone, but the red is not.
Totality properties (only definable if the sets of departure X resp. destination Y are specified; not to be confused with a total relation):
 lefttotal:^{[8]} for all x in X there exists a y in Y such that xRy. For example, R is lefttotal when it is a function or a multivalued function. Note that this property, although sometimes also referred to as total, is different from the definition of total in the next section. Both relations in the picture are lefttotal. The relation x=y^{2}, obtained from the above rotation, is not lefttotal, as it doesn't relate, e.g., x = −14 to any real number y.
 surjective (also called righttotal^{[8]} or onto): for all y in Y there exists an x in X such that xRy. The green relation is surjective, but the red relation is not, as it doesn't relate any real number x to e.g. y = −14.
Uniqueness and totality properties:
 A function: a relation that is functional and lefttotal. Both the green and the red relation are functions.
 An injective function or injection: a relation that is injective, functional, and lefttotal.
 A surjective function or surjection: a relation that is functional, lefttotal, and righttotal.
 A bijection: a surjective onetoone or surjective injective function is said to be bijective, also known as onetoone correspondence.^{[11]} The green relation is bijective, but the red is not.
Difunctional
Less commonly encountered is the notion of difunctional (or regular) relation, defined as a relation R such that R=RR^{−1}R.^{[12]}
To understand this notion better, it helps to consider a relation as mapping every element x∈X to a set xR = { y∈Y  xRy }.^{[12]} This set is sometimes called the successor neighborhood of x in R; one can define the predecessor neighborhood analogously.^{[13]} Synonymous terms for these notions are afterset and respectively foreset.^{[6]}
A difunctional relation can then be equivalently characterized as a relation R such that wherever x_{1}R and x_{2}R have a nonempty intersection, then these two sets coincide; formally x_{1}R ∩ x_{2}R ≠ ∅ implies x_{1}R = x_{2}R.^{[12]}
As examples, any function or any functional (rightunique) relation is difunctional; the converse doesn't hold. If one considers a relation R from set to itself (X = Y), then if R is both transitive and symmetric (i.e. a partial equivalence relation), then it is also difunctional.^{[14]} The converse of this latter statement also doesn't hold.
A characterization of difunctional relations, which also explains their name, is to consider two functions f: A → C and g: B → C and then define the following set which generalizes the kernel of a single function as joint kernel: ker(f, g) = { (a, b) ∈ A × B  f(a) = g(b) }. Every difunctional relation R ⊆ A × B arises as the joint kernel of two functions f: A → C and g: B → C for some set C.^{[15]}
In automata theory, the term rectangular relation has also been used to denote a difunctional relation. This terminology is justified by the fact that when represented as a boolean matrix, the columns and rows of a difunctional relation can be arranged in such a way as to present rectangular blocks of true on the (asymmetric) main diagonal.^{[16]} Other authors however use the term "rectangular" to denote any heterogeneous relation whatsoever.^{[7]}
Relations over a set
This section needs expansion with: wellfounded relation & Noetherian relation. You can help by adding to it. (April 2015)

If X = Y then we simply say that the binary relation is over X, or that it is an endorelation over X.^{[17]} In computer science, such a relation is also called a homogeneous (binary) relation.^{[7]}^{[17]}^{[18]} Some types of endorelations are widely studied in graph theory, where they are known as simple directed graphs permitting loops.
The set of all binary relations Rel(X) on a set X is the set 2^{X × X} which is a Boolean algebra augmented with the involution of mapping of a relation to its inverse relation. For the theoretical explanation see Relation algebra.
Some important properties that a binary relation R over a set X may have are:
 reflexive: for all x in X it holds that xRx. For example, "greater than or equal to" (≥) is a reflexive relation but "greater than" (>) is not.
 irreflexive (or strict): for all x in X it holds that not xRx. For example, > is an irreflexive relation, but ≥ is not.
 coreflexive relation: for all x and y in X it holds that if xRy then x = y.^{[19]} An example of a coreflexive relation is the relation on integers in which each odd number is related to itself and there are no other relations. The equality relation is the only example of a both reflexive and coreflexive relation, and any coreflexive relation is a subset of the identity relation.

 The previous 3 alternatives are far from being exhaustive; e.g. the red relation y=x^{2} from the above picture is neither irreflexive, nor coreflexive, nor reflexive, since it contains the pair (0,0), and (2,4), but not (2,2), respectively.
 symmetric: for all x and y in X it holds that if xRy then yRx. "Is a blood relative of" is a symmetric relation, because x is a blood relative of y if and only if y is a blood relative of x.
 antisymmetric: for all x and y in X, if xRy and yRx then x = y. For example, ≥ is antisymmetric; so is >, but vacuously (the condition in the definition is always false).^{[20]}
 asymmetric: for all x and y in X, if xRy then not yRx. A relation is asymmetric if and only if it is both antisymmetric and irreflexive.^{[21]} For example, > is asymmetric, but ≥ is not.
 transitive: for all x, y and z in X it holds that if xRy and yRz then xRz. For example, "is ancestor of" is transitive, while "is parent of" is not. A transitive relation is irreflexive if and only if it is asymmetric.^{[22]}
 total: for all x and y in X it holds that xRy or yRx (or both). This definition for total is different from left total in the previous section. For example, ≥ is a total relation.
 trichotomous: for all x and y in X exactly one of xRy, yRx or x = y holds. For example, > is a trichotomous relation, while the relation "divides" on natural numbers is not.^{[23]}
 Right Euclidean: for all x, y and z in X it holds that if xRy and xRz, then yRz.
 Left Euclidean: for all x, y and z in X it holds that if yRx and zRx, then yRz.
 Euclidean: A Euclidean relation is both left and right Euclidean. Equality is a Euclidean relation because if x=y and x=z, then y=z.
 serial: for all x in X, there exists y in X such that xRy. "Is greater than" is a serial relation on the integers. But it is not a serial relation on the positive integers, because there is no y in the positive integers such that 1>y.^{[24]} However, "is less than" is a serial relation on the positive integers, the rational numbers and the real numbers. Every reflexive relation is serial: for a given x, choose y=x. A serial relation can be equivalently characterized as every element having a nonempty successor neighborhood (see the previous section for the definition of this notion). Similarly an inverse serial relation is a relation in which every element has nonempty predecessor neighborhood.^{[13]}
 setlike (or local): for every x in X, the class of all y such that yRx is a set. (This makes sense only if relations on proper classes are allowed.) The usual ordering < on the class of ordinal numbers is setlike, while its inverse > is not.
A relation that is reflexive, symmetric, and transitive is called an equivalence relation. A relation that is symmetric, transitive, and serial is also reflexive. A relation that is only symmetric and transitive (without necessarily being reflexive) is called a partial equivalence relation.
A relation that is reflexive, antisymmetric, and transitive is called a partial order. A partial order that is total is called a total order, simple order, linear order, or a chain.^{[25]} A linear order where every nonempty subset has a least element is called a wellorder.

Binary endorelations by property reflexivity symmetry transitivity symbol example directed graph → undirected graph irreflexive symmetric tournament irreflexive antisymmetric pecking order dependency reflexive symmetric strict weak order irreflexive antisymmetric yes < total preorder reflexive yes ≤ preorder reflexive yes ≤ preference partial order reflexive antisymmetric yes ≤ subset partial equivalence symmetric yes equivalence relation reflexive symmetric yes ∼, ≅, ≈, ≡ equality strict partial order irreflexive antisymmetric yes < proper subset
Operations on binary relations
If R, S are binary relations over X and Y, then each of the following is a binary relation over X and Y:
 Union: R ∪ S ⊆ X × Y, defined as R ∪ S = { (x, y)  (x, y) ∈ R or (x, y) ∈ S }. For example, ≥ is the union of > and =.
 Intersection: R ∩ S ⊆ X × Y, defined as R ∩ S = { (x, y)  (x, y) ∈ R and (x, y) ∈ S }.
If R is a binary relation over X and Y, and S is a binary relation over Y and Z, then the following is a binary relation over X and Z: (see main article composition of relations)
 Composition: S ∘ R, also denoted R ; S (or R ∘ S), defined as S ∘ R = { (x, z)  there exists y ∈ Y, such that (x, y) ∈ R and (y, z) ∈ S }. The order of R and S in the notation S ∘ R, used here agrees with the standard notational order for composition of functions. For example, the composition "is mother of" ∘ "is parent of" yields "is maternal grandparent of", while the composition "is parent of" ∘ "is mother of" yields "is grandmother of".
A relation R on sets X and Y is said to be contained in a relation S on X and Y if R is a subset of S, that is, if x R y always implies x S y. In this case, if R and S disagree, R is also said to be smaller than S. For example, > is contained in ≥.
If R is a binary relation over X and Y, then the following is a binary relation over Y and X:
 Inverse or converse: R ^{−1}, defined as R ^{−1} = { (y, x)  (x, y) ∈ R }. A binary relation over a set is equal to its inverse if and only if it is symmetric. See also duality (order theory). For example, "is less than" (<) is the inverse of "is greater than" (>).
If R is a binary relation over X, then each of the following is a binary relation over X:
 Reflexive closure: R ^{=}, defined as R ^{=} = { (x, x)  x ∈ X } ∪ R or the smallest reflexive relation over X containing R. This can be proven to be equal to the intersection of all reflexive relations containing R.
 Reflexive reduction: R ^{≠}, defined as R ^{≠} = R \ { (x, x)  x ∈ X } or the largest irreflexive relation over X contained in R.
 Transitive closure: R ^{+}, defined as the smallest transitive relation over X containing R. This can be seen to be equal to the intersection of all transitive relations containing R.
 Reflexive transitive closure: R *, defined as R * = (R ^{+}) ^{=}, the smallest preorder containing R.
 Reflexive transitive symmetric closure: R ^{≡}, defined as the smallest equivalence relation over X containing R.
Complement
If R is a binary relation over X and Y, then the following too:
 The complement S is defined as x S y if not x R y. For example, on real numbers, ≤ is the complement of >.
The complement of the inverse is the inverse of the complement.
If X = Y, the complement has the following properties:
 If a relation is symmetric, the complement is too.
 The complement of a reflexive relation is irreflexive and vice versa.
 The complement of a strict weak order is a total preorder and vice versa.
The complement of the inverse has these same properties.
Restriction
The restriction of a binary relation on a set X to a subset S is the set of all pairs (x, y) in the relation for which x and y are in S.
If a relation is reflexive, irreflexive, symmetric, antisymmetric, asymmetric, transitive, total, trichotomous, a partial order, total order, strict weak order, total preorder (weak order), or an equivalence relation, its restrictions are too.
However, the transitive closure of a restriction is a subset of the restriction of the transitive closure, i.e., in general not equal. For example, restricting the relation "x is parent of y" to females yields the relation "x is mother of the woman y"; its transitive closure doesn't relate a woman with her paternal grandmother. On the other hand, the transitive closure of "is parent of" is "is ancestor of"; its restriction to females does relate a woman with her paternal grandmother.
Also, the various concepts of completeness (not to be confused with being "total") do not carry over to restrictions. For example, on the set of real numbers a property of the relation "≤" is that every nonempty subset S of R with an upper bound in R has a least upper bound (also called supremum) in R. However, for a set of rational numbers this supremum is not necessarily rational, so the same property does not hold on the restriction of the relation "≤" to the set of rational numbers.
The leftrestriction (rightrestriction, respectively) of a binary relation between X and Y to a subset S of its domain (codomain) is the set of all pairs (x, y) in the relation for which x (y) is an element of S.
Algebras, categories, and rewriting systems
This section needs expansion. You can help by adding to it. (April 2015)

Various operations on binary endorelations can be treated as giving rise to an algebraic structure, known as relation algebra. It should not be confused with relational algebra which deals in finitary relations (and in practice also finite and manysorted).
For heterogenous binary relations, a category of relations arises.^{[7]}
Despite their simplicity, binary relations are at the core of an abstract computation model known as an abstract rewriting system.
Sets versus classes
Certain mathematical "relations", such as "equal to", "member of", and "subset of", cannot be understood to be binary relations as defined above, because their domains and codomains cannot be taken to be sets in the usual systems of axiomatic set theory. For example, if we try to model the general concept of "equality" as a binary relation =, we must take the domain and codomain to be the "class of all sets", which is not a set in the usual set theory.
In most mathematical contexts, references to the relations of equality, membership and subset are harmless because they can be understood implicitly to be restricted to some set in the context. The usual workaround to this problem is to select a "large enough" set A, that contains all the objects of interest, and work with the restriction =_{A} instead of =. Similarly, the "subset of" relation ⊆ needs to be restricted to have domain and codomain P(A) (the power set of a specific set A): the resulting set relation can be denoted ⊆_{A}. Also, the "member of" relation needs to be restricted to have domain A and codomain P(A) to obtain a binary relation ∈_{A} that is a set. Bertrand Russell has shown that assuming ∈ to be defined on all sets leads to a contradiction in naive set theory.
Another solution to this problem is to use a set theory with proper classes, such as NBG or Morse–Kelley set theory, and allow the domain and codomain (and so the graph) to be proper classes: in such a theory, equality, membership, and subset are binary relations without special comment. (A minor modification needs to be made to the concept of the ordered triple (X, Y, G), as normally a proper class cannot be a member of an ordered tuple; or of course one can identify the function with its graph in this context.)^{[26]} With this definition one can for instance define a function relation between every set and its power set.
The number of binary relations
The number of distinct binary relations on an nelement set is 2^{n2} (sequence A002416 in the OEIS):
n  all  transitive  reflexive  preorder  partial order  total preorder  total order  equivalence relation 

0  1  1  1  1  1  1  1  1 
1  2  2  1  1  1  1  1  1 
2  16  13  4  4  3  3  2  2 
3  512  171  64  29  19  13  6  5 
4  65536  3994  4096  355  219  75  24  15 
n  2^{n2}  2^{n2−n}  Σn k=0 k! S(n, k) 
n!  Σn k=0 S(n, k) 

OEIS  A002416  A006905  A053763  A000798  A001035  A000670  A000142  A000110 
Notes:
 The number of irreflexive relations is the same as that of reflexive relations.
 The number of strict partial orders (irreflexive transitive relations) is the same as that of partial orders.
 The number of strict weak orders is the same as that of total preorders.
 The total orders are the partial orders that are also total preorders. The number of preorders that are neither a partial order nor a total preorder is, therefore, the number of preorders, minus the number of partial orders, minus the number of total preorders, plus the number of total orders: 0, 0, 0, 3, and 85, respectively.
 the number of equivalence relations is the number of partitions, which is the Bell number.
The binary relations can be grouped into pairs (relation, complement), except that for n = 0 the relation is its own complement. The nonsymmetric ones can be grouped into quadruples (relation, complement, inverse, inverse complement).
Examples of common binary relations

order relations, including strict orders:
 greater than
 greater than or equal to
 less than
 less than or equal to
 divides (evenly)
 is a subset of

equivalence relations:
 equality
 is parallel to (for affine spaces)
 is in bijection with
 isomorphy
 dependency relation, a finite, symmetric, reflexive relation.
 independency relation, a symmetric, irreflexive relation which is the complement of some dependency relation.
See also
Notes
 ^ Encyclopedic dictionary of Mathematics. MIT. 2000. pp. 1330–1331. ISBN 0262590204.
 ^ ^{a} ^{b} Suppes, Patrick (1972) [originally published by D. van Nostrand Company in 1960]. Axiomatic Set Theory. Dover. ISBN 0486616304.
 ^ ^{a} ^{b} Smullyan, Raymond M.; Fitting, Melvin (2010) [revised and corrected republication of the work originally published in 1996 by Oxford University Press, New York]. Set Theory and the Continuum Problem. Dover. ISBN 9780486474847.
 ^ ^{a} ^{b} Levy, Azriel (2002) [republication of the work published by SpringerVerlag, Berlin, Heidelberg and New York in 1979]. Basic Set Theory. Dover. ISBN 0486420795.
 ^ Megill, Norman (5 August 1993). "dfbr (Metamath Proof Explorer)". Retrieved 18 November 2016.
 ^ ^{a} ^{b} Christodoulos A. Floudas; Panos M. Pardalos (2008). Encyclopedia of Optimization (2nd ed.). Springer Science & Business Media. pp. 299–300. ISBN 9780387747583.
 ^ ^{a} ^{b} ^{c} ^{d} Michael Winter (2007). Goguen Categories: A Categorical Approach to Lfuzzy Relations. Springer. pp. x–xi. ISBN 9781402061646.

^ ^{a} ^{b} ^{c} ^{d} Kilp, Knauer and Mikhalev: p. 3. The same four definitions appear in the following:
 Peter J. Pahl; Rudolf Damrath (2001). Mathematical Foundations of Computational Engineering: A Handbook. Springer Science & Business Media. p. 506. ISBN 9783540679950.
 Eike Best (1996). Semantics of Sequential and Parallel Programs. Prentice Hall. pp. 19–21. ISBN 9780134606439.
 RobertChristoph Riemann (1999). Modelling of Concurrent Systems: Structural and Semantical Methods in the High Level Petri Net Calculus. Herbert Utz Verlag. pp. 21–22. ISBN 9783896756299.
 ^ Gunther Schmidt, 2010. Relational Mathematics. Cambridge University Press, ISBN 9780521762687, Chapt. 5
 ^ Mäs, Stephan (2007), "Reasoning on Spatial Semantic Integrity Constraints", Spatial Information Theory: 8th International Conference, COSIT 2007, Melbourne, Australia, September 19–23, 2007, Proceedings, Lecture Notes in Computer Science, 4736, Springer, pp. 285–302, doi:10.1007/9783540747888_18
 ^ Note that the use of "correspondence" here is narrower than as general synonym for binary relation.
 ^ ^{a} ^{b} ^{c} Chris Brink; Wolfram Kahl; Gunther Schmidt (1997). Relational Methods in Computer Science. Springer Science & Business Media. p. 200. ISBN 9783211829714.
 ^ ^{a} ^{b} Yao, Y. (2004). "Semantics of Fuzzy Sets in Rough Set Theory". Transactions on Rough Sets II. Lecture Notes in Computer Science. 3135. p. 309. doi:10.1007/9783540277781_15. ISBN 9783540239901.
 ^ William Craig (2006). Semigroups Underlying Firstorder Logic. American Mathematical Soc. p. 72. ISBN 9780821865880.
 ^ Gumm, H. P.; Zarrad, M. (2014). "Coalgebraic Simulations and Congruences". Coalgebraic Methods in Computer Science. Lecture Notes in Computer Science. 8446. p. 118. doi:10.1007/9783662441244_7. ISBN 9783662441237.
 ^ Julius Richard Büchi (1989). Finite Automata, Their Algebras and Grammars: Towards a Theory of Formal Expressions. Springer Science & Business Media. pp. 35–37. ISBN 9781461388531.
 ^ ^{a} ^{b} M. E. Müller (2012). Relational Knowledge Discovery. Cambridge University Press. p. 22. ISBN 9780521190213.
 ^ Peter J. Pahl; Rudolf Damrath (2001). Mathematical Foundations of Computational Engineering: A Handbook. Springer Science & Business Media. p. 496. ISBN 9783540679950.
 ^ Fonseca de Oliveira, J. N., & Pereira Cunha Rodrigues, C. D. J. (2004). Transposing Relations: From Maybe Functions to Hash Tables. In Mathematics of Program Construction (p. 337).
 ^ Smith, Douglas; Eggen, Maurice; St. Andre, Richard (2006), A Transition to Advanced Mathematics (6th ed.), Brooks/Cole, p. 160, ISBN 0534399002
 ^ Nievergelt, Yves (2002), Foundations of Logic and Mathematics: Applications to Computer Science and Cryptography, SpringerVerlag, p. 158.
 ^ Flaška, V.; Ježek, J.; Kepka, T.; Kortelainen, J. (2007). Transitive Closures of Binary Relations I (PDF). Prague: School of Mathematics – Physics Charles University. p. 1. Lemma 1.1 (iv). This source refers to asymmetric relations as "strictly antisymmetric".
 ^ Since neither 5 divides 3, nor 3 divides 5, nor 3=5.
 ^ Yao, Y.Y.; Wong, S.K.M. (1995). "Generalization of rough sets using relationships between attribute values" (PDF). Proceedings of the 2nd Annual Joint Conference on Information Sciences: 30–33..
 ^ Joseph G. Rosenstein, Linear orderings, Academic Press, 1982, ISBN 0125976801, p. 4
 ^ Tarski, Alfred; Givant, Steven (1987). A formalization of set theory without variables. American Mathematical Society. p. 3. ISBN 0821810413.
References
 M. Kilp, U. Knauer, A.V. Mikhalev, Monoids, Acts and Categories: with Applications to Wreath Products and Graphs, De Gruyter Expositions in Mathematics vol. 29, Walter de Gruyter, 2000, ISBN 3110152487.
 Gunther Schmidt, 2010. Relational Mathematics. Cambridge University Press, ISBN 9780521762687.
External links
 Hazewinkel, Michiel, ed. (2001) [1994], "Binary relation", Encyclopedia of Mathematics, Springer Science+Business Media B.V. / Kluwer Academic Publishers, ISBN 9781556080104