Name
Abstract | ||
|---|---|---|
Coecke, Sadrzadeh, and Clark [3] developed a compositional model of meaning for distributional semantics, in which each word in a sentence has a meaning vector and the distributional meaning of the sentence is a function of the tensor products of the word vectors. Abstractly speaking, this function is the morphism corresponding to the grammatical structure of the sentence in the category of finite dimensional vector spaces. In this paper, we provide a concrete method for implementing this linear meaning map, by constructing a corpus-based vector space for the type of sentence. Our construction method is based on structured vector spaces whereby meaning vectors of all sentences, regardless of their grammatical structure, live in the same vector space. Our proposed sentence space is the tensor product of two noun spaces, in which the basis vectors are pairs of words each augmented with a grammatical role. This enables us to compare meanings of sentences by simply taking the inner product of their vectors. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-94-007-7284-7_5 | IWCS '11 Proceedings of the Ninth International Conference on Computational Semantics |
Keywords | Field | DocType |
vector space,tensor product,noun,inner product | Tensor product,Vector space,Distributional semantics,Computer science,Atomic sentence,Noun,Artificial intelligence,Natural language processing,Basis (linear algebra),Sentence,Morphism | Journal |
Volume | ISSN | Citations |
abs/1101.0309 | Proceedings of the 9th International Conference on Computational
Semantics (2011) | 35 |
PageRank | References | Authors |
4.04 | 7 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Edward Grefenstette | 1 | 1743 | 80.65 |
| Mehrnoosh Sadrzadeh | 2 | 784 | 62.69 |
| Stephen Clark | 3 | 2369 | 162.42 |
| Bob Coecke | 4 | 912 | 104.22 |
| Stephen Pulman | 5 | 450 | 38.31 |