Boosting Variant Recognition with Light Semantics
نویسندگان
چکیده
A reasonably simple, domain-independent, large-scale approach of lexictd semantics to paraphrase recognition is presented in this paper. It relies on the enrichment of morphosyntactic rules and the addition of fbur boolean syntactico-semantic features to a set of 1.,(}23 words. It results in a significant enhancement of precision of 30% with a slight decrease in recall of 10%.
منابع مشابه
Boosting recombined weak classifiers
Boosting is a set of methods for the construction of classifier ensembles. The differential feature of these methods is that they allow to obtain a strong classifier from the combination of weak classifiers. Therefore, it is possible to use boosting methods with very simple base classifiers. One of the most simple classifiers are decision stumps, decision trees with only one decision node. This...
متن کاملUnsupervised Learning of Boosted Tree Classifier Using Graph Cuts for Hand Pose Recognition
This study proposes an unsupervised learning approach for the task of hand pose recognition. Considering the large variation in hand poses, classification using a decision tree seems highly suitable for this purpose. Various research works have used boosted decision trees and have shown encouraging results for pose recognition. This work also employs a boosted classifier tree learned in an unsu...
متن کاملObject Recognition using Geometric Properties and a variant of Boosting
This paper describes an approach for learning object descriptions as combinations of simple features using labeled still images. The contribution of this paper is a new method for constructing geometric relations of simple features with the LPBoost algorithm. A full search for relevant geometric relations between simple features is rather impossible because of the computation time required. We ...
متن کاملBoosting Minimum Bayes Risk Discriminative Training
A new variant of AdaBoost is applied to a Minimum Bayes Risk discriminative training procedure that directly aims at reducing Word Error Rate for Automatic Speech Recognition. Both techniques try to improve the discriminative power of a classifier and we show that can be combined together to yield even better performance on a small vocabulary continuous speech recognition task. Our results also...
متن کاملDynamic Categorization of Semantics of Fashion Language: A Memetic Approach
Categories are not invariant. This paper attempts to explore the dynamic nature of semantic category, in particular, that of fashion language, based on the cognitive theory of Dawkins’ memetics, a new theory of cultural evolution. Semantic attributes of linguistic memes decrease or proliferate in replication and spreading, which involves a dynamic development of semantic category. More specific...
متن کامل