Abstract
The representation of word meaning in texts is a central problem in Computational Linguistics. Geometrical models represent lexical semantic information in terms of the basic co-occurrences that words establish each other in large-scale text collections. As recent works already address, the definition of methods able to express the meaning of phrases or sentences as operations on lexical representations is a complex problem, and a still largely open issue. In this paper, a perspective centered on Convolution Kernels is discussed and the formulation of a Partial Tree Kernel that integrates syntactic information and lexical generalization is studied. The interaction of such information and the role of different geometrical models is investigated on the question classification task where the state-of-the-art result is achieved.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 336-348 |
| Number of pages | 13 |
| Volume | 7181 LNCS |
| Edition | PART 1 |
| DOIs | |
| Publication status | Published - 2012 |
| Externally published | Yes |
| Event | 13th Annual Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2012 - New Delhi Duration: 11 Mar 2012 → 17 Mar 2012 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Number | PART 1 |
| Volume | 7181 LNCS |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 13th Annual Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2012 |
|---|---|
| City | New Delhi |
| Period | 11/3/12 → 17/3/12 |
Fingerprint
ASJC Scopus subject areas
- Computer Science(all)
- Theoretical Computer Science
Cite this
Distributional models and lexical semantics in convolution kernels. / Croce, Danilo; Filice, Simone; Basili, Roberto.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7181 LNCS PART 1. ed. 2012. p. 336-348 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7181 LNCS, No. PART 1).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Distributional models and lexical semantics in convolution kernels
AU - Croce, Danilo
AU - Filice, Simone
AU - Basili, Roberto
PY - 2012
Y1 - 2012
N2 - The representation of word meaning in texts is a central problem in Computational Linguistics. Geometrical models represent lexical semantic information in terms of the basic co-occurrences that words establish each other in large-scale text collections. As recent works already address, the definition of methods able to express the meaning of phrases or sentences as operations on lexical representations is a complex problem, and a still largely open issue. In this paper, a perspective centered on Convolution Kernels is discussed and the formulation of a Partial Tree Kernel that integrates syntactic information and lexical generalization is studied. The interaction of such information and the role of different geometrical models is investigated on the question classification task where the state-of-the-art result is achieved.
AB - The representation of word meaning in texts is a central problem in Computational Linguistics. Geometrical models represent lexical semantic information in terms of the basic co-occurrences that words establish each other in large-scale text collections. As recent works already address, the definition of methods able to express the meaning of phrases or sentences as operations on lexical representations is a complex problem, and a still largely open issue. In this paper, a perspective centered on Convolution Kernels is discussed and the formulation of a Partial Tree Kernel that integrates syntactic information and lexical generalization is studied. The interaction of such information and the role of different geometrical models is investigated on the question classification task where the state-of-the-art result is achieved.
UR - http://www.scopus.com/inward/record.url?scp=84858325371&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84858325371&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-28604-9_28
DO - 10.1007/978-3-642-28604-9_28
M3 - Conference contribution
AN - SCOPUS:84858325371
SN - 9783642286032
VL - 7181 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 336
EP - 348
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -