Abstract We introduce Incremental Semantic Analysis, a fully incremental word space model, and we... more Abstract We introduce Incremental Semantic Analysis, a fully incremental word space model, and we test it on longitudinal child-directed speech data. On this task, ISA outperforms the related Random Indexing algorithm, as well as a SVD-based technique. In addition, the model has interesting properties that might also be characteristic of the semantic space of children.
The paper presents SYMPAThy, a new approach to the extraction of Word Combinations. The approach ... more The paper presents SYMPAThy, a new approach to the extraction of Word Combinations. The approach is new in that it combines pattern-based (P-based) and syntax-based (S-based) methods in order to obtain an integrated and unified view of a lexeme’s combinatory potential.
We introduce Incremental Semantic Analy- sis, a fully incremental word space model, and we test i... more We introduce Incremental Semantic Analy- sis, a fully incremental word space model, and we test it on longitudinal child-directed speech data. On this task, ISA outperforms the related Random Indexing algorithm, as well as a SVD-based technique. In addi- tion, the model has interesting properties that might also be characteristic of the se- mantic space of children.
Abstract We introduce Incremental Semantic Analysis, a fully incremental word space model, and we... more Abstract We introduce Incremental Semantic Analysis, a fully incremental word space model, and we test it on longitudinal child-directed speech data. On this task, ISA outperforms the related Random Indexing algorithm, as well as a SVD-based technique. In addition, the model has interesting properties that might also be characteristic of the semantic space of children.
The paper presents SYMPAThy, a new approach to the extraction of Word Combinations. The approach ... more The paper presents SYMPAThy, a new approach to the extraction of Word Combinations. The approach is new in that it combines pattern-based (P-based) and syntax-based (S-based) methods in order to obtain an integrated and unified view of a lexeme’s combinatory potential.
We introduce Incremental Semantic Analy- sis, a fully incremental word space model, and we test i... more We introduce Incremental Semantic Analy- sis, a fully incremental word space model, and we test it on longitudinal child-directed speech data. On this task, ISA outperforms the related Random Indexing algorithm, as well as a SVD-based technique. In addi- tion, the model has interesting properties that might also be characteristic of the se- mantic space of children.
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Papers by Alessandro Lenci