Is singular value decomposition useful for word similarity extraction?
نویسندگان
چکیده
In this paper, we analyze the behaviour of Singular Value Decomposition in a number of word similarity extraction tasks, namely acquisition of translation equivalents from comparable corpora. Special attention is paid to two different aspects: computational efficiency and extraction quality. The main objective of the paper is to describe several experiments comparing methods based on Singular Value Decomposition (SVD) to other strategies. The results lead us to conclude that SVD makes the extraction less computationally efficient and much less precise than other more basic models for the task of extracting translation equivalents from comparable corpora.
منابع مشابه
Automated Tumor Segmentation Based on Hidden Markov Classifier using Singular Value Decomposition Feature Extraction in Brain MR images
ntroduction: Diagnosing brain tumor is not always easy for doctors, and existence of an assistant that facilitates the interpretation process is an asset in the clinic. Computer vision techniques are devised to aid the clinic in detecting tumors based on a database of tumor c...
متن کاملComparing Different Properties Involved in Word Similarity Extraction
In this paper, we will analyze the behavior of several parameters, namely type of contexts, similarity measures, and word space models, in the task of word similarity extraction from large corpora. The main objective of the paper will be to describe experiments comparing different extraction systems based on all possible combinations of these parameters. Special attention will be paid to the co...
متن کاملDisguised Face Recognition by Using Local Phase Quantization and Singular Value Decomposition
Disguised face recognition is a major challenge in the field of face recognition which has been taken less attention. Therefore, in this paper a disguised face recognition algorithm based on Local Phase Quantization (LPQ) method and Singular Value Decomposition (SVD) is presented which deals with two main challenges. The first challenge is when an individual intentionally alters the appearance ...
متن کاملGraph Clustering by Hierarchical Singular Value Decomposition with Selectable Range for Number of Clusters Members
Graphs have so many applications in real world problems. When we deal with huge volume of data, analyzing data is difficult or sometimes impossible. In big data problems, clustering data is a useful tool for data analysis. Singular value decomposition(SVD) is one of the best algorithms for clustering graph but we do not have any choice to select the number of clusters and the number of members ...
متن کاملNoise Effects on Modal Parameters Extraction of Horizontal Tailplane by Singular Value Decomposition Method Based on Output Only Modal Analysis
According to the great importance of safety in aerospace industries, identification of dynamic parameters of related equipment by experimental tests in operating conditions has been in focus. Due to the existence of noise sources in these conditions the probability of fault occurrence may increases. This study investigates the effects of noise in the process of modal parameters identification b...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Language Resources and Evaluation
دوره 45 شماره
صفحات -
تاریخ انتشار 2011