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BITS_PILANI@DPIL-FIRE2016: Paraphrase Detection in Hindi Language using Syntactic Features of Phrase
2016
Forum for Information Retrieval Evaluation
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This paper focuses on using Machine Learning classification techniques for detecting paraphrases in Hindi language for the DPIL Task in Fire 2016. ...
A feature vector based approach has been used for detecting paraphrases. ...
The most common way of detecting paraphrases is modeling the problem as a classification problem. This paper implements a supervised classification model for detecting Paraphrases. ...
dblp:conf/fire/BhargavaBJS16
fatcat:b3ydxugro5ahnpefddw5zbtzbi
Sentence Level Paraphrase Identification System for Tamil Language
2018
International Journal of Darshan Institute on Engineering Research & Emerging Technology
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The aim is to detect sentence level plagiarism through paraphrase identification of sentences in Tamil. The sentences in Tamil language are processed using Tamil shallow parser. ...
Automatic detection of the paraphrase is a process which has immense applications like plagiarism detection and new event detection. ...
Plagiarism detection is the task which needs the paraphrase identification technique to detect the sentences which are paraphrases of others. ...
doi:10.32692/ijdi-eret/7.1.2018.1805
fatcat:zn3bpb4cpjffxgqoicc2qnvuaa
Predicting Human Metaphor Paraphrase Judgments with Deep Neural Networks
2018
Proceedings of the Workshop on Figurative Language Processing
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Our model is trained for a binary classification of paraphrase candidates, and then used to predict graded paraphrase acceptability. ...
Our corpus consists of 200 sets of 5 sentences, with each set containing one reference metaphorical sentence, and four ranked candidate paraphrases. ...
We test this model on two classification problems: (i) binary paraphrase classification and (ii) paraphrase ranking. ...
doi:10.18653/v1/w18-0906
dblp:conf/acl-figlang/BizzoniL18
fatcat:umv2x4owpvf65ngqi4jtroyqru
KEC@DPIL-FIRE2016: Detection of Paraphrases in Indian Languages (Tamil)
2016
Forum for Information Retrieval Evaluation
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Automatic paraphrase detection is an intellectual task which has immense applications like plagiarism detection, new event detection, etc. ...
The proposed approach utilizes machine learning algorithms like Support Vector Machine and Maximum Entropy for classification of given sentence pair. ...
tagging features in order to detect the paraphrase sentences. ...
dblp:conf/fire/ThangarajanKKJ16
fatcat:zlhrcmqzlrd2jhcj45hiif6ad4
Anuj@DPIL-FIRE2016: A Novel Paraphrase Detection Method in Hindi Language Using Machine Learning
[chapter]
2018
Lecture Notes in Computer Science
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At FIRE 2016, we have worked upon the problem of detecting paraphrases for the given Shared Task DPIL (Detecting Paraphrases in Indian Languages) in Hindi Language specifically. ...
In Natural Language Processing, two statements written using different words having same meaning is termed as paraphrasing. ...
Classification model includes the model training using the four machine learning algorithms. All the steps are described below. ...
doi:10.1007/978-3-319-73606-8_11
fatcat:daz4lassgrgjnem5t5momfd4ze
Modeling the Paraphrase Detection Task over a Heterogeneous Graph Network with Data Augmentation
2020
Information
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Paraphrase detection is a Natural-Language Processing (NLP) task that aims at automatically identifying whether two sentences convey the same meaning (even with different words). ...
Our approach, although simple, outperforms the best results reported for the paraphrase detection task in Portuguese, showing that graph structures may capture better the semantic relatedness among sentences ...
Besides that organization, the sentence pairs of the corpus are labeled with inference classification, as entailment, none, and paraphrase, as shown in Table 2 . ...
doi:10.3390/info11090422
fatcat:e5ou2a2325d3liatndvcczjz7y
How Well Sentence Embeddings Capture Meaning
2015
Proceedings of the 20th Australasian Document Computing Symposium on ZZZ - ADCS '15
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A SVM with a linear kernel is used to perform the classification using the sentence vectors as its input. ...
Depending on the model used for the embeddings this will vary -different models are suited for different down-stream applications. ...
It is a multiclass classification problem, rather than the binary decision problem of paraphrase detection. ...
doi:10.1145/2838931.2838932
dblp:conf/adcs/WhiteTLB15
fatcat:b756omor4jbynpdq6dtt4qdlei
A deep network model for paraphrase detection in short text messages
2018
Information Processing & Management
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2017 pre-print arXiv:1712.02820v1 fatcat:itwe3cdd55gkphzhzjjwu5hcjq
To cope with these challenges, we propose a novel deep neural network-based approach that relies on coarse-grained sentence modeling using a convolutional neural network and a long short-term memory model ...
This paper is concerned with paraphrase detection. ...
This similarity matrix is further used as features for the classification of the paraphrase detection problem. ...
doi:10.1016/j.ipm.2018.06.005
fatcat:okhjlegcxfcd5c2ywd73ie7er4
HIT2016@DPIL-FIRE2016: Detecting Paraphrases in Indian Languages based on Gradient Tree Boosting
2016
Forum for Information Retrieval Evaluation
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Detecting paraphrase is an important and challenging task. It can be used in paraphrases generation and extraction, machine translation, question and answer and plagiarism detection. ...
Since the same meaning of a sentence is expressed in another sentence using different words, it makes the traditional methods based on lexical similarity ineffective. ...
In Section 2, we ana lyze the problem of Detecting Paraphrases in Indian Languages, in troduce the model we used, and describe the features which the cl assifier uses. ...
dblp:conf/fire/KongCTHHQ16
fatcat:6tudpxqwurh3joi4ndeuoqoqsm
A Hybrid Model for Paraphrase Detection Combines pros of Text Similarity with Deep Learning
2019
International Journal of Computer Applications
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This paper proposes a hybrid model that combines the text similarity approach with deep learning approach in order to improve paraphrase detection. ...
Paraphrase detection (PD) is a very essential and important task in Natural language processing. ...
The proposed Hybrid Approach As shown in Figure. 1, the proposed model checks the Paraphrase detection between two sentences task through 3 steps. ...
doi:10.5120/ijca2019919011
fatcat:jjl3modl6vbn7kfuddibziantu
Methods for Detecting Paraphrase Plagiarism
[article]
2017
arXiv
pre-print
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/deletion and word and phrase reordering), and combined the methods into a paraphrase detection model. ...
In this paper, we approached the problem of paraphrase plagiarism by proposing methods for detecting the most common techniques (phenomena) used in paraphrasing texts (namely; lexical substitution, insertion ...
techniques used in paraphrasing texts, and combining the methods into a paraphrase detection model. ...
arXiv:1712.10309v1
fatcat:uufokkw73bd6tabowmbhqr6uni
NLP-NITMZ@DPIL-FIRE2016: Language Independent Paraphrases Detection
2016
Forum for Information Retrieval Evaluation
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Finally, these feature-set are trained using Probabilistic Neural Network (PNN) to detect the paraphrases. ...
In our approach, we used language independent feature-set to detect paraphrases in Indian languages. Features are mainly based on lexical based similarity. ...
Paraphrase detection is also used in plagiarism detection to detect the sentences which are paraphrases of each other. ...
dblp:conf/fire/SarkarSBPDG16
fatcat:rig2bbwhfjbthbn3mnx6vz4zdq
Towards Generalizable Sentence Embeddings
2016
Proceedings of the 1st Workshop on Representation Learning for NLP
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Further, our model's behaviour on paraphrase detection when trained with an increasing amount of labelled data is indicative of a generalizable model. ...
Our embeddings capture human intuition on similarity favorably than competing models, while we also show positive indications of transfer from the task of natural language inference to paraphrase detection ...
Figure 2 : 2 An overview of the models used in the experiments of this paper.
Figure 3 : 3 Precision-Recall curve for zero-shot paraphrase detection. ...
doi:10.18653/v1/w16-1628
dblp:conf/rep4nlp/TriantafillouKU16
fatcat:bpoek7umovhn3hn5g6w3soae7a
AMRITA_CEN$@$SemEval-2015: Paraphrase Detection for Twitter using Unsupervised Feature Learning with Recursive Autoencoders
2015
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)
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Our paraphrase detection system makes use of phrase-structure parse tree embeddings that are then provided as input to a conventional supervised classification model. ...
We explore using recursive autoencoders for SemEval 2015 Task 1: Paraphrase and Semantic Similarity in Twitter. ...
We would like again to convey our sincere gratitude towards Daniel Cer, who encouraged and motivated us throughout the final submission. ...
doi:10.18653/v1/s15-2008
dblp:conf/semeval/SundaramMP15
fatcat:kv6ty7gyrncv3dl4cioiydvv7q
Certainty factor model in paraphrase detection
2021
Pamukkale University Journal of Engineering Sciences
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We propose the use of certainty factor (CF) model in paraphrase detection. ...
A set of succeeding paraphrase detection features (generic and distance based features) is built by filtering and this set is used as evidences in CF model. ...
Briefly, in our approach, accepting the paraphrase detection problem as a classification problem, the features that are highlighted to be effective in classification by feature selection methods are used ...
doi:10.5505/pajes.2020.75350
fatcat:aw5geqmftnfrbpl4nbdpq3nrgq
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