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Learning to Recognize Ancillary Information for Automatic Paraphrase Identification
2016
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
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Previous work on Automatic Paraphrase Identification (PI) is mainly based on modeling text similarity between two sentences. ...
Engineering features for this new task is rather difficult, thus, we approach the problem by representing text with syntactic structures and applying tree kernels on them. ...
Table 2 : 2 Results on Paraphrase Identification. skip-gram model applied to the UkWaC corpus (Ba-
roni et al., 2009).
Table 4 : 4 PI classifier performance using ATC. ...
doi:10.18653/v1/n16-1129
dblp:conf/naacl/FiliceM16
fatcat:nho3yi3wdvd3zcsmllbpulq2n4
Exploring the Recent Trends of Paraphrase Detection
2019
International Journal of Computer Applications
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This study is to examine paraphrase detection (PD) for diagnostic purposes. ...
The performance of the selected researches is assessed by how accurate the F-measures are in detecting paraphrase in Microsoft Research Paraphrase Corpus (MSPR). ...
In [7] a software system that utilizes a recently developed lexico-syntactic method to the task of paraphrase identification was introduced. ...
doi:10.5120/ijca2019918317
fatcat:7sxb27g42bdclgmj3pyd7uefn4
SEMILAR: The Semantic Similarity Toolkit
2013
Annual Meeting of the Association for Computational Linguistics
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SEMILAR implements a number of algorithms for assessing the semantic similarity between two texts. ...
Furthermore, it offers facilities for manual se-mantic similarity annotation by experts through its component SEMILAT (a SEMantic simILarity Annotation Tool). ...
Acknowledgments This research was supported in part by Institute for Education Sciences under award R305A100875. ...
dblp:conf/acl/RusLBNS13
fatcat:eeltnqs6ezfi5k6aji2h7mr2ae
Paraphrase Identification on the Basis of Supervised Machine Learning Techniques
[chapter]
2006
Lecture Notes in Computer Science
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This paper presents a machine learning approach for paraphrase identification which uses lexical and semantic similarity information. ...
With the objective to increase the final performance of the system, we scrutinize the influence of the combination of lexical and semantic information, as well as techniques for classifier combination. ...
For perfect similarity match, sim lin has value 1 and for completely dissimilar words 0. ...
doi:10.1007/11816508_52
fatcat:pggqpzuudnfsbfl7kzl3i7yap4
A Novel Approach for Developing Paraphrase Detection System using Machine Learning
2021
International Journal of Computer Applications
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The proposed paraphrase detection system has achieved comparable performance with existing paraphrase detection systems. ...
Research Paraphrase (MSRP) Corpus and assessed on the same. ...
paraphrase identification. ...
doi:10.5120/ijca2021921389
fatcat:clya63hxdvfz3kpmszhrjmhc2i
A Hybrid Model for Paraphrase Detection Combines pros of Text Similarity with Deep Learning
2019
International Journal of Computer Applications
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Paraphrase detection (PD) is a very essential and important task in Natural language processing. ...
The goal of paraphrase detection is to check whether two statements written in natural language have the identical semantic or not. ...
A string metric is a metric that measures similarity or dissimilarity (distance) between two text strings for approximate string matching or comparison. ...
doi:10.5120/ijca2019919011
fatcat:jjl3modl6vbn7kfuddibziantu
Certainty factor model in paraphrase detection
2021
Pamukkale University Journal of Engineering Sciences
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The proposed CF model in paraphrase identification is realized by utilizing the renowned paraphrase corpus of Microsoft Research (MSRP) [2] that is stated to be a standard resource in paraphrase identification ...
Öz In this paper, we address the problem of uncertainty management in identification of paraphrase sentence pairs. ...
Determining Value-ranges of Evidences In identification of paraphrase sentence pairs, for each evidence an evidence value that is actually a similarity score in a predefined range is calculated for the ...
doi:10.5505/pajes.2020.75350
fatcat:aw5geqmftnfrbpl4nbdpq3nrgq
Extracting Lexically Divergent Paraphrases from Twitter
2014
Transactions of the Association for Computational Linguistics
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We present MULTIP (Multi-instance Learning Paraphrase Model), a new model suited to identify paraphrases within the short messages on Twitter. ...
We jointly model paraphrase relations between word and sentence pairs and assume only sentence-level annotations during learning. ...
Government is authorized to reproduce and distribute reprints for governmental purposes. ...
doi:10.1162/tacl_a_00194
fatcat:54bwppjf55asjmpi7cicq46vt4
Learning to Represent Bilingual Dictionaries
2019
Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)
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In the bilingual paraphrase identification task, we show that our model effectively associates sentences in different languages via a shared embedding space, and outperforms existing approaches in identifying ...
bilingual paraphrases. * Both authors contributed equally to this work. ...
Acknowledgement We thank the anonymous reviewers for their insightful comments. This work was supported in part by National Science Foundation Grant IIS-1760523. ...
doi:10.18653/v1/k19-1015
dblp:conf/conll/ChenTCCSZ19
fatcat:acovrv3wuzbtnnifgysnrkc63q
Learning to Represent Bilingual Dictionaries
[article]
2019
arXiv
pre-print
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Meanwhile, our model effectively addresses the bilingual paraphrase identification problem and significantly outperforms previous approaches. ...
The proposed model is trained to map the literal word definitions to the cross-lingual target words, for which we explore with different sentence encoding techniques. ...
Acknowledgement We thank the anonymous reviewers for their insightful comments. This work was supported in part by National Science Foundation Grant IIS-1760523. ...
arXiv:1808.03726v3
fatcat:q5gbxiu2nbfxzlf34yvqjvz2x4
Predicting Comprehension from Students' Summaries
[chapter]
2015
Lecture Notes in Computer Science
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To this end, our aim is to provide an automated solution for analyzing and predicting students' comprehension levels by extracting a combination of reading strategies and textual complexity factors from ...
We opted to use RBF kernels as the corresponding hyperparameters (the regularization constant C and the kernel hyperparameter γ) were optimized through Grid Search [26] . ...
applied on lexicalized ontologies [15] , more specifically Wu-Palmer distance applied on WOLF [16] , cosine similarity from Latent Semantic Analysis (LSA) [17] vector spaces, and Jensen-Shannon dissimilarity ...
doi:10.1007/978-3-319-19773-9_10
fatcat:5cawjgxquvdm7bfbtngspghrvm
Learning Antonyms with Paraphrases and a Morphology-Aware Neural Network
2017
Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)
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In this paper, we present a novel method for deriving antonym pairs using paraphrase pairs containing negation markers. ...
Government is authorized to reproduce and distribute reprints for Governmental purposes. ...
We would like to thank our anonymous reviewers for their thoughtful and helpful comments. ...
doi:10.18653/v1/s17-1002
dblp:conf/starsem/RajanaCAS17
fatcat:2lnueipczzbazjbztdjx3whgvi
A multi-cascaded model with data augmentation for enhanced paraphrase detection in short texts
2020
Information Processing & Management
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2019 pre-print arXiv:1912.12068v1 fatcat:uwxct2ktwnenxjjmpr6a3jq2jm
Paraphrase detection is an important task in text analytics with numerous applications such as plagiarism detection, duplicate question identification, and enhanced customer support helpdesks. ...
In this work, we present a data augmentation strategy and a multi-cascaded model for improved paraphrase detection in short texts. ...
paraphrase identification of news tweets in Arabic language. ...
doi:10.1016/j.ipm.2020.102204
fatcat:7ehvysetjrhmncciqfstqso6pi
Terminological paraphrase extraction from scientific literature based on predicate argument tuples
2012
Journal of information science
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Terminological paraphrases (TPs) are sentences or phrases that express the concepts of terminologies in a different form. ...
For evaluation, we constructed an evaluation collection for the TP recognition task by extracting TPs from a target literature database using the proposed method. ...
the tree kernel-based machine learning with support vector machines for binary classification. ...
doi:10.1177/0165551512459920
fatcat:cwkzqvttc5bbjd5h3oqegw7spa
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
This paper is concerned with paraphrase detection. ...
The ability to detect similar sentences written in natural language is crucial for several applications, such as text mining, text summarization, plagiarism detection, authorship authentication and question ...
Heilman and Smith [9] propose a tree edit model for paraphrase identification based on syntactic relations among words. ...
doi:10.1016/j.ipm.2018.06.005
fatcat:okhjlegcxfcd5c2ywd73ie7er4
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