Results 161 to 170 of about 646,240 (193)

Quasi Cosine Similarity Metric Learning

2015
It is vital to select an appropriate distance metric for many learning algorithm. Cosine distance is an efficient metric for measuring the similarity of descriptors in classification task. However, the cosine similarity metric learning (CSML) [3] is not widely used due to the complexity of its formulation and time consuming.
Xiang Wu, Zhiguo Shi 0002, Lei Liu
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Query-Directed Probing LSH for Cosine Similarity

Proceedings of the Fifth International Conference on Network, Communication and Computing, 2016
Locality-sensitive hashing (LSH) considered as an efficient algorithm for large-scale similarity search has become increasingly popular. Recently, many of its variants have been applied widely in high-dimensional similarity search. To overcome the drawback of requirement for a large number of hash tables, researchers proposed the famous Multi-Probe LSH
Shengyingjie Liu, Jianwen Sun, Zhi Liu 0011, Xian Peng, Sanya Liu   +4 more
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Online and Batch Learning of Generalized Cosine Similarities

2009 Ninth IEEE International Conference on Data Mining, 2009
In this paper, we define an online algorithm to learn the generalized cosine similarity measures for kNN classification and hence a similarity matrix A corresponding to a bilinear form. In contrary to the standard cosine measure, the normalization is itself dependent on the similarity matrix which makes it impossible to use directly the algorithms ...
Ali Mustafa Qamar, Éric Gaussier
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The Cosine Similarity Technique for Removing the Redundancy Sample

2019 22nd International Symposium on Wireless Personal Multimedia Communications (WPMC), 2019
The k-nearest neighbor algorithm is one of the basic and simple classification algorithms that share a common limitation of the algorithm which requires more computation cost when the size of training data is enlarged. To solve this problem, a new method applied to the cosine similarity for reducing the size of the training data set is proposed.
Worasak Rueangsirarak, Teeravisit Laohapensaeng, Suppakarn Chansareewittaya, Anusorn Yodjaiphet   +3 more
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Improving Document Similarity Calculation Using Cosine-Similarity Graphs

2019
Data mining information using various indices and determining candidates that can be judged as having the same tendency based on similarity between documents is common. The accuracy of similarity largely depends on a sufficient amount of data and requires advanced analysis using natural language processing.
Yasunao Takano, Yusuke Iijima, Kou Kobayashi, Hiroshi Sakuta, Hiroki Sakaji, Masaki Kohana, Akio Kobayashi   +6 more
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Sentiment analysis using cosine similarity measure

2015 IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS), 2015
The opinion of other people is often a major factor influencing our decisions. For a consumer it affects purchase decisions and for a producer or a service provider it helps in making business decisions. Companies spend a lot of money and time on surveys for gathering the public opinion on products and services.
Saprativa Bhattacharjee, Anirban Das 0005, Ujjwal Bhattacharya, Swapan K. Parui, Sudipta Roy 0002   +4 more
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Cosine Similarity Metric Learning for Face Verification

2011
Face verification is the task of deciding by analyzing face images, whether a person is who he/she claims to be. This is very challenging due to image variations in lighting, pose, facial expression, and age. The task boils down to computing the distance between two face vectors. As such, appropriate distance metrics are essential for face verification
Hieu V. Nguyen, Li Bai 0001
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Cosine similarity for multiplex network summarization

Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2021
Athanasia Polychronopoulou, Fang Zhou, Zoran Obradovic   +2 more
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A Metaphor Detection Approach Using Cosine Similarity

2017
Metaphor is a prominent figure of speech. For their prevalence in text and speech, detection and analysis of metaphors are required for complete natural language understanding. This paper describes a novel method for identification of metaphors with word vectors.
Malay Pramanick, Pabitra Mitra
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Multivariate Multiscale Cosine Similarity Entropy

ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022
Hongjian Xiao, Theerasak Chanwimalueang, Danilo P. Mandic   +2 more
openaire   +2 more sources