Results 281 to 290 of about 52,386 (322)

Bagging to find better expansion words

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010), 2010
The supervised learning has been applied into the query expansion techniques, which trains a model to predict the “goodness” or “utility” of the expanded term to the retrieval system. There are many features to measure the relatedness between the expanded word and the query, which can be incorporated in the supervised learning to select the expanded ...
Bingqing Wang, Yaqian Zhou 0001, Xipeng Qiu, Qi Zhang 0001, Xuanjing Huang 0001   +4 more
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Generating Bags of Words from the Sums of Their Word Embeddings

2018
Many methods have been proposed to generate sentence vector representations, such as recursive neural networks, latent distributed memory models, and the simple sum of word embeddings (SOWE). However, very few methods demonstrate the ability to reverse the process – recovering sentences from sentence embeddings.
Lyndon White, Roberto Togneri, Wei Liu 0006, Mohammed Bennamoun   +3 more
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Fractal dimension of bag-of-visual words

Pattern Analysis and Applications, 2018
Scene recognition is an important and challenging problem in computer vision. One of the most used scene recognition methods is the bag-of-visual words. Despite the interesting results, this approach does not capture the detail richness of spatial information of the visual words on the image.
Lucas Correia Ribas, Diogo Nunes Gonçalves, Jonathan de Andrade Silva, Amaury Antônio de Castro Jr., Odemir Martinez Bruno, Wesley Nunes Gonçalves   +5 more
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Contextual Bag-of-Words for Visual Categorization

IEEE Transactions on Circuits and Systems for Video Technology, 2011
Bag-of-words (BOW), which represents an image by the histogram of local patches on the basis of a visual vocabulary, has attracted intensive attention in visual categorization due to its good performance and flexibility. Conventional BOW neglects the contextual relations between local patches due to its Naive Bayesian assumption.
Li, T Li, Teng, Mei, T Mei, Tao, Kweon, IS Kweon, In-So, Hua, XS Hua, Xian-Sheng   +3 more
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Context Dependent Bag of words generation

2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2013
Query spelling correction is a crucial component in modern text mining systems such as Question-answering systems and Sentiment Analysis systems where noise can affect the query matching score. In many existing query matching systems Bag of Words (BoW) generation method is used to generate candidates for noisy words.
Swapnil Ashok Jadhav, Durvasula V. L. N. Somayajulu, S. Nagesh Bhattu, R. B. V. Subramanyam, P. Suresh   +4 more
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A hybrid feature extraction approach for brain MRI classification based on Bag-of-words

Biomedical Signal Processing and Control, 2019
Magnetic resonance imaging (MRI) has attracted considerable attention in medical engineering community, since it is a non-invasive diagnostic technique and for its importance in medicine applications.
Wadhah Ayadi, W. Elhamzi, I. Charfi, Mohamed Atri   +3 more
semanticscholar   +1 more source

Word Segmentation of Micro Blogs with Bagging

2015
This paper describes the model we designed for the Chinese word segmentation Task of NLPCC 2015. We firstly apply a word-based perceptron algorithm to build the base segmenter. Then, we use a Bootstrap Aggregating model of bagging which improves the segmentation results consistently on the three tracks of closed, semi-open and open test.
Zhenting Yu, Xin-Yu Dai, Si Shen, Shujian Huang, Jiajun Chen 0001   +4 more
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Beyond bag of words

Proceedings of the 21st ACM international conference on Multimedia, 2013
Due to the semantic gap, the low-level features are not able to semantically represent images well. Besides, traditional semantic related image representation may not be able to cope with large inter class variations and are not very robust to noise.
Chunjie Zhang 0001, Shuhui Wang, Chao Liang 0001, Jing Liu 0001, Qingming Huang, Haojie Li, Qi Tian 0001   +6 more
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Recognizing Human Actions by a Bag of Visual Words

2013 IEEE International Conference on Systems, Man, and Cybernetics, 2013
In this paper a novel method for action recognition based on the bag of visual words approach is proposed. The main contribution is to model each action through a high level features vector computed as the histogram of the visual words: the visual words are extracted by analyzing global descriptors of the scene and their occurrences are evaluated ...
FOGGIA, PASQUALE, PERCANNELLA, Gennaro, SAGGESE, ALESSIA, VENTO, Mario   +3 more
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A “Bag” or a “Window” of Words for Information Filtering?

2008
Treating documents as bag of words is the norm in Information Filtering. Syntactic and semantic correlations between terms are ignored, or in other words, term independence is assumed. In this paper we challenge this common assumption. We use Nootropia, a user profiling model that uses a sliding window approach to capture term dependencies in a network
Nikolaos Nanas, Manolis Vavalis
openaire   +1 more source