Kernel Methods
Related Papers
Data-Defined Kernels for Parse Reranking Derived from Probabilistic Models
Previous research applying kernel meth- ods to natural language parsing have fo- cussed on proposing kernels over parse trees, which are hand-crafted based on do- main knowledge and computational con- …...
Domain Kernels for Word Sense Disambiguation
In this paper we present a supervised Word Sense Disambiguation methodol- ogy, that exploits kernel methods to model sense distinctions. In particular a combi- nation of kernel functions is adopted …...
Extracting Relations with Integrated Information Using Kernel Methods
Entity relation detection is a form of in- formation extraction that finds predefined relations between pairs of entities in text. This paper describes a relation detection approach that combines clues …...
Instance Based Lexical Entailment for Ontology Population
In this paper we propose an instance based method for lexical entailment and apply it to automatic ontology population from text. The approach is fully unsupervised and based on kernel …...
Semantic Role Labeling Systems for Arabic using Kernel Methods
There is a widely held belief in the natural lan- guage and computational linguistics commu- nities that Semantic Role Labeling (SRL) is a significant step toward improving important applications, e.g. …...
Syntactic and Semantic Kernels for Short Text Pair Categorization
Automatic detection of general relations between short texts is a complex task that cannot be carried out only relying on lan- guage models and bag-of-words. There- fore, learning methods to …...
Automatic Detection and Classification of Social Events
In this paper we introduce the new task of social event extraction from text. We distin- guish two broad types of social events depend- ing on whether only one or …...
Entity-Focused Sentence Simplification for Relation Extraction
Relations between entities in text have been widely researched in the natu- ral language processing and information- extraction communities. The region con- necting a pair of entities (in a parsed …...
Simplicity is Better: Revisiting Single Kernel PPI Extraction
It has been known that a combination of multiple kernels and addition of various resources are the best options for im- proving effectiveness of kernel-based PPI extraction methods. These supple- …...
Using Syntactic and Semantic Structural Kernels for Classifying Definition Questions in Jeopardy!
The last decade has seen many interesting ap- plications of Question Answering (QA) tech- nology. The Jeopardy! quiz show is certainly one of the most fascinating, from the view- points …...
UNITOR: Aspect Based Sentiment Analysis with Structured Learning
In this paper, the UNITOR system partici- pating in the SemEval-2014 Aspect Based Sentiment Analysis competition is pre- sented. The task is tackled exploiting Ker- nel Methods within the Support …...
ASM Kernel: Graph Kernel using Approximate Subgraph Matching for Relation Extraction
Kernel methods have been widely stud- ied in several natural language process- ing tasks such as relation extraction and sentence classification. In this work, we present a new graph kernel …...
Deep Learning in Semantic Kernel Spaces
AbstractKernel methods enable the direct usage of structured representations of textual data during language learning and inference tasks. Expressive kernels, such as Tree Kernels, achieve excellent performance in NLP. On …...
SenticNet 7: A Commonsense-based Neurosymbolic AI Framework for Explainable Sentiment Analysis
AbstractIn recent years, AI research has demonstrated enormous potential for the benefit of humanity and society. While often better than its human counterparts in classification and pattern recognition tasks, however, …...