نتایج جستجو برای: words

تعداد نتایج: 143046  

Journal: :International Journal of Foundations of Computer Science 2013

Journal: :Nature 2001

Journal: :Psychology of Women Quarterly 2013

Journal: :Archives of Disease in Childhood 1985

Journal: :BMJ 1994

Journal: :Bulletin of the Belgian Mathematical Society - Simon Stevin 2003

2008
Xiaolan Li Afzal Godil Asim Imdad Wagan

This paper presents a new method for 3D shape retrieval based on the bags-of-words model along with a weak spatial constraint. First, a two-pass sampling procedure is performed to extract the local shape descriptors, based on spin images, which are used to construct a shape dictionary. Second, the model is partitioned into different regions based on the positions of the words. Then each region ...

2014
Giorgos Tolias Teddy Furon Hervé Jégou

Image search systems based on local descriptors typically achieve orientation invariance by aligning the patches on their dominant orientations. Albeit successful, this choice introduces too much invariance because it does not guarantee that the patches are rotated consistently. This paper introduces an aggregation strategy of local descriptors that achieves this covariance property by jointly ...

2017
Carolina Fócil Arias Jorge Zúñiga Grigori Sidorov Ildar Z. Batyrshin Alexander F. Gelbukh

The 2017 Microblog Cultural Contextualization task consists in three challenges: (1) Content Analysis, (2) Microblog search, and (3) TimeLine illustration. This paper describes the use of cosine similarity, which is characterized by the comparison of similarity between two vectors of an inner product space. This research used two approaches: (1) word2vec and (2) Bag-of-Words (BoW) for extractin...

Journal: :Int. J. Comput. Proc. Oriental Lang. 2005
Wenliang Chen Jingbo Zhu Muhua Zhu Li Zhang Tianshun Yao

In this paper, we present a novel model for improving the performance of Domain Dictionary-based text categorization. The proposed model is named as Self-Partition Model(SPM). SPM can group the candidate words into the predefined clusters, which are generated according to the structure of Domain Dictionary. Using these learned clusters as features, we proposed a novel text representation. The e...

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