| 1 |
A New Amharic Speech Emotion Dataset and Classification Benchmark ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 2 |
A Deep CNN Architecture with Novel Pooling Layer Applied to Two Sudanese Arabic Sentiment Datasets ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 3 |
A Novel Interval-Valued q-Rung Dual Hesitant Linguistic Multi-Attribute Decision-Making Method Based on Linguistic Scale Functions and Power Hamy Mean
|
|
|
|
In: Entropy; Volume 24; Issue 2; Pages: 166 (2022)
|
|
BASE
|
|
Show details
|
|
|
| 4 |
MKPM: Multi keyword-pair matching for natural language sentences
|
|
|
|
Abstract:
Sentence matching is widely used in various natural language tasks, such as natural language inference, paraphrase identification and question answering. For these tasks, we need to understand the logical and semantic relationship between two sentences. Most current methods use all information within a sentence to build a model and hence determine its relationship to another sentence. However, the information contained in some sentences may cause redundancy or introduce noise, impeding the performance of the model. Therefore, we propose a sentence matching method based on multi keyword-pair matching (MKPM), which uses keyword pairs in two sentences to represent the semantic relationship between them, avoiding the interference of redundancy and noise. Specifically, we first propose a sentence-pair-based attention mechanism sp-attention to select the most important word pair from the two sentences as a keyword pair, and then propose a Bi-task architecture to model the semantic information of these keyword pairs. The Bi-task architecture is as follows: 1. In order to understand the semantic relationship at the word level between two sentences, we design a word-pair task (WP-Task), which uses these keyword pairs to complete sentence matching independently. 2. We design a sentence-pair task (SP-Task) to understand the sentence level semantic relationship between the two sentences by sentence denoising. Through the integration of the two tasks, our model can understand sentences more accurately from the two granularities of word and sentence. Experimental results show that our model can achieve state-of-the-art performance in several tasks. Our source code is publicly available
|
|
URL: http://repository.essex.ac.uk/30636/
http://repository.essex.ac.uk/30636/1/Lu2021_Article_MKPMMultiKeyword-pairMatchingF.pdf
https://doi.org/10.1007/s10489-021-02306-5
|
|
BASE
|
|
Hide details
|
|
|
| 7 |
Additional file 1: of Change patterns of oncomelanid snail burden in areas within the Yangtze River drainage after the three gorges dam operated ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 8 |
Additional file 1: of Imported malaria cases in former endemic and non-malaria endemic areas in China: are there differences in case profile and time to response? ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 9 |
Additional file 1: of Change patterns of oncomelanid snail burden in areas within the Yangtze River drainage after the three gorges dam operated ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 10 |
Additional file 1: of Imported malaria cases in former endemic and non-malaria endemic areas in China: are there differences in case profile and time to response? ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 11 |
No Morphological Markers, No Problem: ERP Study Reveals Semantic Contribution to Distinct Neural Substrates Between Noun and Verb Processing in Online Sentence Comprehension
|
|
|
|
BASE
|
|
Show details
|
|
|
| 12 |
Additional file 1: of A case report of spontaneous abortion caused by Brucella melitensis biovar 3 ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 13 |
Additional file 1: of A case report of spontaneous abortion caused by Brucella melitensis biovar 3 ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 15 |
A Study on the Integration Risk Management for the Insurance Enterprises
|
|
|
|
In: Cross-Cultural Communication; Vol 4, No 3 (2008): Cross-Cultural Communication; 44-50 ; 1923-6700 ; 1712-8358 (2010)
|
|
BASE
|
|
Show details
|
|
|
|
|
