Sequence Classification
Hawkes processes for continuous time sequence classification : an application to rumour stance classification in Twitter
... Little work has been done on stance classifica- tion of rumour tweets. Qazvinian et al. (2011) in- troduced a system for classifying rumour tweets and Lukasik et al. (2015a) considered this problem in a setting where the ...
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Recurrent Residual Learning for Sequence Classification
... In this paper, we explore the possibility of lever- aging residual network to improve the performance of LSTM RNN. We show that direct adaptation of ResNet performs well in sequence classification. In ...
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Polymorphic malware detection using sequence classification methods and ensembles
... gene classification tools are optimized for and restricted to an alphabet of four letters (nucleic acids), we have selected the Strand gene sequence classifier for malware ...gene sequence ...
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Protein sequence classification using feature hashing
... protein sequence data are being ...protein sequence classification, usually results in prohibitively high dimensional input spaces, for large values of ...protein sequence ...
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Automatic interlinear glossing as two level sequence classification
... These results show that dividing glossing into two sequence classification tasks allows us to opti- mise manual work in developing new resources. A relatively small annotated corpus is used to model ...
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Sequence Classification in Data Mining With Pattern Based Item Sets
... ABSTRACT:-Sequence classification is an essential undertaking in information ...of sequence classification utilizing rules made out of intriguing examples found in a dataset of named sequences ...
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A multi granularity pattern based sequence classification framework for educational data
... Abstract—In many application domains, such as education, sequences of events occurring over time need to be studied in order to understand the generative process behind these sequences, and hence classify new examples. ...
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Guided Learning for Bidirectional Sequence Classification
... In this paper, we propose guided learning, a new learning framework for bidirectional sequence classification. The tasks of learn- ing the order of inference and training the local classifier are ...
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Sequence Classification with Human Attention
... Contributions We present a recurrent neural architecture with attention for sequence classi- fication tasks. The architecture jointly learns its parameters and an attention function, but can alternate between ...
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Iterative Recursive Attention Model for Interpretable Sequence Classification
... We test IRAM on two sentiment classification datasets. The first is the Stanford Sentiment Tree- bank (SST) (Socher et al., 2013), a dataset de- rived from movie reviews on Rotten Tomatoes and containing 11,855 ...
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DNA Sequence Classification by Convolutional Neural Network
... understood sequence to train machine learning models, we could use the trained models to predict profile of unknown ...several sequence based features including values from a position specific scoring ...
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GPCRTree: online hierarchical classification of GPCR function
... implement an alignment-independent representation of protein sequences and is also the first to classify sequences using a classifier specifically selected for each group of sib- ling nodes in the GPCR functional ...
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Model Metric Co-Learning for Time Series Classification.
... for sequence classification which learns in the model space – each data item (sequence) is represented by a predictive model from a carefully designed model ...
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Benchmarking of alignment free sequence comparison methods
... reference sequence data sets as well as four new data ...different sequence analysis scenarios: protein sequence classification, gene tree in- ference, regulatory sequence ...
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Quantum Inspired Complex Word Embedding
... tence classification tasks, one can perform projec- tive measurements onto the sentence representa- tion to determine the sentiment polarity; for sen- tence text similarity task, the amplitude of the in- ner ...
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Sequence Based Classification Scheme for the GenusLegionella Targeting the mip Gene
... In conclusion, the scheme was able to unambiguously dis- criminate among 39 of 40 species and correctly group 26 ad- ditional serogroups or reference strains within those species. Additionally, 102 wild strains isolated ...
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Prediction of plant promoters based on hexamers and random triplet pair analysis
... Using a different type of negative dataset in conjunc- tion with the same positive dataset (the previously used 305 promoters), we extracted features, trained our method, and performed a 5-fold cross validation test in ...
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UniTN End to End Discourse Parser for CoNLL 2016 Shared Task
... The PDTB corpus distributed to the shared task participants contains raw text and syntactic con- stituency and dependency parses. Besides the to- ken and part-of-speech tags, these resources are used to extract and ...
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Sentiment Classification: A Topic Sequence-Based Approach
... sentiment classification model based on topic sequence which refers to topics in descending order of their distribution ...topic sequence, which are used to construct topic co-occurrence matrices ...
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Report Writing
... The Body o~~" the Report The classification of the material in preparing the outline of the report will determine the sequence in which the different sections will be ordered.. The list [r] ...
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