Evaluation of Different Similarity Measures for the Extraction of Multiword Units in a Reinforcement Learning Environment
نویسندگان
چکیده
In this paper, we present an application of Genetic Algorithms to extract Multiword Units (i.e. complex lexical units such as compound nouns, idiomatic expressions or phrase templates). For that purpose, a fitness function will be defined whose maximization will serve as a basis for the identification of pertinent word -grams (i.e ordered vectors of words) based on different similarity measures. Finally, we will provide an experiment realized over an English Linux Manual that evidences promising results.
منابع مشابه
A Geometric View of Similarity Measures in Data Mining
The main objective of data mining is to acquire information from a set of data for prospect applications using a measure. The concerning issue is that one often has to deal with large scale data. Several dimensionality reduction techniques like various feature extraction methods have been developed to resolve the issue. However, the geometric view of the applied measure, as an additional consid...
متن کاملA method for automatic extraction of multiword units representing business aspects from user reviews
The paper describes a semi-supervised approach to extracting multiword aspects of user-written reviews that belong to a given category. The method starts with a small set of seed words representing the target category, and calculates distributional similarity between the candidate and seed words. We compare three distributional similarity measures (Lin’s, Weeds’ and balAPinc), and a document re...
متن کاملEvaluation of Similarity Measures for Template Matching
Image matching is a critical process in various photogrammetry, computer vision and remote sensing applications such as image registration, 3D model reconstruction, change detection, image fusion, pattern recognition, autonomous navigation, and digital elevation model (DEM) generation and orientation. The primary goal of the image matching process is to establish the correspondence between two ...
متن کاملAn Empirical Comparison of Distance Measures for Multivariate Time Series Clustering
Multivariate time series (MTS) data are ubiquitous in science and daily life, and how to measure their similarity is a core part of MTS analyzing process. Many of the research efforts in this context have focused on proposing novel similarity measures for the underlying data. However, with the countless techniques to estimate similarity between MTS, this field suffers from a lack of comparative...
متن کاملHierarchical Functional Concepts for Knowledge Transfer among Reinforcement Learning Agents
This article introduces the notions of functional space and concept as a way of knowledge representation and abstraction for Reinforcement Learning agents. These definitions are used as a tool of knowledge transfer among agents. The agents are assumed to be heterogeneous; they have different state spaces but share a same dynamic, reward and action space. In other words, the agents are assumed t...
متن کامل