In a previous post, I discussed the distinction between attributes and relations:
An attribute is a characteristic of an entity, whereas a relation is a connection between two or more entities. In logic, we can define an attribute as a predicate with one argument and a relation as a predicate with two or more arguments. The distinction between attributes and relations can be unclear. For example, the colour red may be seen as an attribute, RED(X), or a relation, REDDER_THAN(X, Y).
This leads to a distinction between attributional similarity and relational similarity. Two things, X and Y, are attributionally similar when the attributes of X are similar to the attributes of Y. Two pairs, A:B and C:D, are relationally similar when the relations between A and B are similar to the relations between C and D. I’ve been thinking about the rules that govern attributional and relational similarity.
Let A:B::C:D be the assertion that A:B and C:D are relationally similar. The expression A:B::C:D is usually read as “A is to B as C is to D”. This is called a proportional analogy. Aristotle knew that proportional analogies obey certain logical rules:
(1) A:B::C:D → B:A::D:C
(2) A:B::C:D → A:C::B:D
From (1) and (2), we can derive:
A:B::C:D → C:D::A:B
More recently, these rules have been studied by Yves Lepage and others. Rule (1) seems clear, but rule (2) is sometimes odd. It seems that rule (2) is reasonable when the items (A, B, C, and D) are all of the same general type, but it is less reasonable when they are different types:
uncle:aunt::brother:sister → aunt:uncle::sister:brother [same types: kin, rule (1)]
uncle:aunt::brother:sister → uncle:brother::aunt:sister [same types: kin, rule (2)]
dog:bark::cow:moo → bark:dog::moo:cow [different types, rule (1)]
dog:bark::cow:moo → dog:cow::bark:moo [different types, rule (2)]
Let X~Y be the assertion that X and Y are attributionally similar. When X and Y have a very high degree of attributional similarity, we call them synonyms. I have argued that attributional similarity can be reduced to relational similarity, but not vice versa. Here is one way to do the reduction:
(3) X~Y = (by definition) for all Z, X:Z::Y:Z
In other words, X and Y are attributionally similar when, for all Z, the relations between X and Z are similar to the relations between Y and Z. This definition of attributional similarity results in a score of 83.75% on the TOEFL synonyms. (The paper is about tensors, not similarity measures, so it does not explain that the tensor is computing similarity by using definition (3).) Rules (1) and (2) give us:
X:Z::Y:Z → Z:X::Z:Y → Z:Z::X:Y [assuming X, Y, and Z are the same type?]
Hence:
X~Y = for all Z, Z:Z::X:Y
Transitivity seems plausible for proportional analogies:
(4) A:B::C:D & A:B::E:F → C:D::E:F
Now we have a little theorem:
Theorem: A~C & A:B::C:D → B~D
Proof:
- A~C [by assumption]
- A:B::C:D [by assumption]
- A:C::B:D [from 2 by rule (2)]
- for all X, A:X::C:X [from 1 by definition (3)]
- for all X, X:X::A:C [from 4 by rules (1) and (2)]
- for all X, X:X::B:D [from 3 and 5 by rule (4)]
- for all X, B:X::D:X [from 6 by rules (1) and (2)]
- B~D [from 7 by definition (3); QED]
I’m not sure about the significance of this, but I thought it was worth writing down.
This post was partly inspired by a blog post by Gustavo Lacerda. Suppose we have:
A = me
B = my lover
C = my lover’s past lovers
D = my lover’s past lovers’ lovers
Then A~C & A:B::C:D → B~D. If I am similar to my lover’s past lovers (A~C) and I am attracted by my lover like my lover’s past lovers are attracted by my lover’s past lovers’ lovers (A:B::C:D), then my lover should be similar to my lover’s past lovers’ lovers (B~D). Thus I am likely to be attracted by my lover’s past lovers’ lovers.
I believe that similarity is a matter of degree, but the above discussion assumes that it is binary (true/false).
Filed under: Computational Linguistics, Semantics | Tagged: analogy, logic, similarity, synonyms
It’s better than that: since lovers have mutual attraction, not only are you likely to be attracted to your lover’s past lovers’ lovers, but they likely to be attracted to you too!
Related:
(1) sorting out causes in friendship and romantic networks
(2) The limits of collaborative filtering?
(3) 2-Place and 1-Place Words
Like others I find your blog stimulating. Thank you.
I have a question regarding relational similarity.
First let me say that I work in applied semiotics from a psycho-social perspective. As such, I am not constrained by the limits of binary machines, and the thinking that it may entail :-)
Here’s the thing.
It seems to me that your definition of relational similarity is essentially binary as you seem to compare two pairs. Could there not be a third option when considering the sense-making process of human beings?
Taking the work of George KELLY (1955) for whom meaning is constructed by a triadic approach. This involves creating clusters (C1, C2, C3, …) of three significant elements to the person about a given topic. Then s/he is asked to say what features two of the elements have in common that the third does not, cf. http://en.wikipedia.org/wiki/Repertory_grid
When the person has given the “features” (F1, F2, F3, …), in having compared two elements in terms of a third, s/he is then asked to give the contrary feature (not-F1) to corresponding feature (F1). In this way you have a pair of words (e.g. F1 not-F1) relative to a third common element (e.g. C1). This is called a “construct”. (I hope that this rapid summary is more or less clear.)
Would you consider the Kellyian construct as being close to a “relational similarity” or not at all?
Like others I find your blog stimulating. Thank you.
Thanks!
It seems to me that your definition of relational similarity is essentially binary as you seem to compare two pairs. Could there not be a third option when considering the sense-making process of human beings?
I talk about this here: Beyond Proportional Analogy.
Thank you for your reply Peter.
I suspect we are not coming in, at what I modestly understand as the issue, from the same entry point,
I did read your piece on “beyond proportional analogy”. I readily admit that I may not have understood all of it.
However, if I may summarise, as a non-logician, my point in a more logician parlance.
Here goes :
A is to B as B is to A in terms of C
C is not-A:B
In my field the logic of the argument relies on the included middle postulate (see the works of the engineer-researcher Jean Louis Le Moigne) where C is the included middle to A:B.
I realise this non-Aristotelian logic may not be within your field of interest.
A is to B as B is to A in terms of C
C is not-A:B
I’m not sure what you’re saying here. Reading your first comment again, it seems to me that we might be talking about different things, because proportional analogies are about relations (such as Parent-Child(X,Y) or Tool-Purpose(X,Y)) but you are talking about features (such as Tall(X) or Red(X)). For example, consider the proportional analogy traffic:street::water:riverbed. This analogy might be seen as based on the relation Carried-Carrier(X,Y); that is, Carried-Carrier(traffic,street) and Carried-Carrier(water,riverbed) are both true. However, traffic and water have few features in common and street and riverbed have few features in common (maybe Moves(traffic) and Moves(water), but this is not very compelling). This is a fundamental property of analogies: They are based on relations, not features.
Perhaps I have misunderstood you. It might help if you could give some examples of A, B, and C, to illustrate your schema.