3,020 research outputs found
Cross-view Embeddings for Information Retrieval
No full textTesis doctoral en Informática realizada por Parth Gupta bajo la supervisión del Dr. Paolo Rosso (Universitat Politècnica de València) y el Dr. Rafael E. Banchs (Institute for Infocomm Research, Singapore). La tesis se defendió en Valencia (España) el 26 de enero de 2017. El comité de doctorado estuvo compuesto por los siguientes doctores: Eneko Agirre (Universidad del País Vasco), Julio Gonzalo (Universidad Nacional de Educación a Distancia) y Jaap Kamps (Universidad de Amsterdam). La tesis obtuvo la calificación de sobresaliente Cum Laude.Ph.D. thesis in Computer Science written by Parth Gupta under the supervision of Dr. Paolo Rosso (Universitat Politècnica de València) and Dr. Rafael E. Banchs (Institute for Infocomm Research, Singapore). The thesis was defended in Valencia (Spain) on January 26, 2017. The doctoral committee comprised of the following doctors: Eneko Agirre (University of the Basque Country), Julio Gonzalo (Universidad Nacional de Educación a Distancia) and Jaap Kamps (University of Amsterdam). The thesis got the grade of outstanding Cum Laude
Data for Gupta et al., "Estimating the Meridional Extent of Adiabatic Mixing in the Stratosphere using Age-of-Air", JGR:Atmospheres,
No full textModel data and post-processed data supporting the creation of the manuscript "Estimating the Meridional Extent of Adiabatic Mixing in the Stratosphere using Age-of-Air" submitted to JGR:Atmospheres in August 2022.
1) The netCDF files created through post-processing of full model data in FORTRAN are shared in the /data/ directory. These file contains the zonal mean circulation statistics based on Gupta et al. (2020), age-of-air transport diagnostics based on Linz et al. (2021), and the novel \Gamma-\Theta circulation streamfunction introduced in this study. The /data/ directory also contains MATLAB .mat data files for the transport diagnostics obtained from WACCM. 150 days of actual GFDL-FV3 model data in the northern hemisphere, between 0.1 hPa-500 hPa pressure levels is also provided to support external computations and validation.
2) The Jupyter notebook used for final computation and figures production is provided in .ipynb, .html and .pdf formats in /code/. All the files referred to in the notebook are stored in the /data/ directory.
Corresponding author : Aman Gupta, [email protected], [email protected], [email protected]
Cross-language Plagiarism Detection over Continuous-space- and Knowledge Graph-based Representations of Language
No full textThis is the author’s version of a work that was accepted for publication in Knowledge-Based Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Knowledge-Based Systems 111 (2016) 87–99. DOI 10.1016/j.knosys.2016.08.004.Cross-language (CL) plagiarism detection aims at detecting plagiarised fragments of text among documents
in different languages. The main research question of this work is on whether knowledge graph
representations and continuous space representations can complement to each other and improve the
state-of-the-art performance in CL plagiarism detection methods. In this sense, we propose and evaluate
hybrid models to assess the semantic similarity of two segments of text in different languages. The proposed
hybrid models combine knowledge graph representations with continuous space representations
aiming at exploiting their complementarity in capturing different aspects of cross-lingual similarity. We
also present the continuous word alignment-based similarity analysis, a new model to estimate similarity
between text fragments. We compare the aforementioned approaches with several state-of-the-art
models in the task of CL plagiarism detection and study their performance in detecting different length
and obfuscation types of plagiarism cases. We conduct experiments over Spanish-English and GermanEnglish
datasets. Experimental results show that continuous representations allow the continuous word
alignment-based similarity analysis model to obtain competitive results and the knowledge-based document
similarity model to outperform the state-of-the-art in CL plagiarism detection.
© 2016 Elsevier B.V. All rights reserved.This research has been carried out in framework of the FPI-UPV pre-doctoral grant (No de registro - 3505) awarded to Parth Gupta and in the framework of the national projects DIANA-APPLICATIONS - Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01), and SomEMBED: SOcial Media language understanding - EMBEDing contexts (TIN2015-71147-C2-1-P). We would like to thank Martin Potthast, Daniel Ortiz-Martinez, and Luis A. Leiva for their support and comments during this research.Franco-Salvador, M.; Gupta, PA.; Rosso, P.; Banchs, R. (2016). Cross-language Plagiarism Detection over Continuous-space- and Knowledge Graph-based Representations of Language. Knowledge-Based Systems. 111:87-99. https://doi.org/10.1016/j.knosys.2016.08.004S879911
Corrigendum: Capital Inflows and House Prices: Aggregate and Regional Evidence from China
No full textIn the paper ‘Capital Inflows and House Prices: Aggregate and Regional Evidence from China’ by H. An, et al., printed in the December 2016 issue, there was a missing acknowledgement section for funding resources.
On page 451, the acknowledgement section should appear after the corresponding information as:
“Correspondence: Rakesh Gupta, Department of Accounting, Finance and Economics, Griffith Business School, Griffith University, Nathan Campus QLD 4111. [email protected]
*This work was financially supported by the Humanities and Social Science Foundation of Ministry of Education of China (16YJA790001).”
The author apologises for this error and any confusion it may have caused.No Full Tex
Alkylated benzimidazoles: Design, synthesis, docking, DFT analysis, ADMET property, molecular dynamics and activity against HIV and YFV
No full textA series of alkylated benzimidazole derivatives was synthesized and screened for their anti-HIV, anti-YFV, and broad-spectrum antiviral properties. The physicochemical parameters and drug-like properties of the compounds were assessed first, and then docking studies and MD simulations on HIV-RT allosteric sites were conducted to find the possible mode of their action. DFT analysis was also performed to confirm the nature of the hydrogen bonding interaction of active compounds. The in silico studies indicated that the molecules behaved like possible NNRTIs. The nature - polar or non-polar and position of the substituent present at fifth, sixth, and N-1 positions of the benzimidazole moiety played an important role in determining the antiviral properties of the compounds. Among the various compounds, 2-(5,6-dibromo-2-chloro-1H-benzimidazol-1-yl)ethan-1-ol (3a) showed anti-HIV activity with an appreciably low IC50 value as 0.386 × 10-5μM. Similarly, compound 2b, 3-(2-chloro-5-nitro-1H-benzimidazol-1-yl) propan-1-ol, showed excellent inhibitory property against the yellow fever virus (YFV) with EC50 value as 0.7824 × 10-2μM.sponsorship: The author Ritika Srivastava acknowledges financial support in the form of Research Fellowship from the UGC grant, University of Allahabad, Allahabad. Parth Sarthi Sen Gupta sincerely thanks IISER Berhampur, Odisha for postdoctoral fellowship. (IISER Berhampur, Odisha, UGC grant, University of Allahabad, Allahabad)status: Publishe
Methods for cross-language plagiarism detection
No full textThree reasons make plagiarism across languages to be on the rise: (i) speakers of under-resourced languages often consult documentation in a foreign language, (ii) people immersed in a foreign country can still consult material written in their native language, and (iii) people are often interested in writing in a language different to their native one. Most efforts for automatically detecting cross-language plagiarism depend on a preliminary translation, which is not always available.
In this paper we propose a freely available architecture for plagiarism detection across languages covering the entire process: heuristic retrieval, detailed analysis, and post-processing. On top of this architecture we explore the suitability of three cross-language similarity estimation models: Cross-Language Alignment-based Similarity Analysis (CL-ASA), Cross-Language Character n-Grams (CL-CNG), and Translation plus Monolingual Analysis (T + MA); three inherently different models in nature and required resources.
The three models are tested extensively under the same conditions on the different plagiarism detection sub-tasks—something never done before. The experiments show that T+MA produces the best results, closely followed by CL-ASA. Still CL-ASA obtains higher values of precision, an important factor in plagiarism detection when lesser user intervention is desired.Peer ReviewedPostprint (published version
Continuous Space Models for CLIR
No full text[EN] We present and evaluate a novel technique for learning cross-lingual continuous space models to aid cross-language information retrieval (CLIR). Our model, which is referred to as external-data composition neural network (XCNN), is based on a composition function that is implemented on top of a deep neural network that provides a distributed learning framework. Different from most existing models, which rely only on available parallel data for training, our learning framework provides a natural way to exploit monolingual data and its associated relevance metadata for learning continuous space representations of language. Cross-language extensions of the obtained models can then be trained by using a small set of parallel data. This property is very helpful for resource-poor languages, therefore, we carry out experiments on the English-Hindi language pair. On the conducted comparative evaluation, the proposed model is shown to outperform state-of-the-art continuous space models with statistically significant margin on two different tasks: parallel sentence retrieval and ad-hoc retrieval.We thank German Sanchis Trilles for helping in conducting experiments with machine translation. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the GeForce Titan GPU used for this research. The research of the first author was supported by FPI grant of UPV. The research of the third author is supported by the SomEMBED TIN2015-71147-C2-1-P MINECO research project and by the Generalitat Valenciana under the grant ALMAMATER (PrometeolI/2014/030).Gupta, P.; Banchs, R.; Rosso, P. (2017). Continuous Space Models for CLIR. Information Processing & Management. 53(2):359-370. https://doi.org/10.1016/j.ipm.2016.11.002S35937053
First person – Akash Gupta
No full textFirst Person is a series of interviews with the first authors of a selection of papers published in Biology Open, helping early-career researchers promote themselves alongside their papers. Akash Gupta is first author on ‘A novel and cost-effective ex vivo orthotopic model for the study of human breast cancer in mouse mammary gland organ culture’, published in BiO. Akash conducted the research described in this article while a PhD Scholar in Rajendra Mehta's lab at IIT Research Institute, Chicago, USA. He is now an assistant research scientist in the lab of Syreeta L. Tilghman at the University of Arizona, Department of Medicine, Tucson, USA, investigating drug efficacy modeling using human organoids culture for the treatment of cancers
Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing
No full textCross-language plagiarism detection attempts to identify and extract automatically plagiarism among documents in different languages. Plagiarized fragments can be translated verbatim copies or may alter their structure to hide the copying, which is known as paraphrasing and is more difficult to detect. In order to improve the paraphrasing detection, we use a knowledge graph-based approach to obtain and compare context models of document fragments in different languages. Experimental results in German-English and Spanish-English cross-language plagiarism detection indicate that our knowledge graph-based approach offers a better performance compared to other state-of-the-art models.The research has been carried out in the framework of the European Commission WIQ-EIIRSES (no. 269180) and DIANA-APPLICATIONS - Finding Hidden Knowledge in Texts:Applications (TIN2012-38603-C02-01) projects as well as the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems.Franco-Salvador, M.; Gupta, P.; Rosso, P. (2013). Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing. En Bridging Between Information Retrieval and Databases: PROMISE Winter School 2013, Bressanone, Italy, February 4-8, 2013. Revised Tutorial Lectures. Springer Verlag (Germany). 227-236. https://doi.org/10.1007/978-3-642-54798-0_12S227236Barrón-Cedeño, A., Vila, M., Martí, M., Rosso, P.: Plagiarism meets paraphrasing: insights for the next generation in automatic plagiarism detection. Computational Linguistics 39(4) (2013)Barrón-Cedeño, A.: On the mono- and cross-language detection of text re-use and plagiarism. Ph.D. thesis, Universitat Politènica de València (2012)Barrón-Cedeño, A., Rosso, P., Pinto, D., Juan, A.: On cross-lingual plagiarism analysis using a statistical model. In: Proc. of the ECAI 2008 Workshop on Uncovering Plagiarism, Authorship and Social Software Misuse, PAN 2008 (2008)Franco-Salvador, M., Gupta, P., Rosso, P.: Cross-language plagiarism detection using BabelNet’s statistical dictionary. Computación y Sistemas, Revista Iberoamericana de Computación 16(4), 383–390 (2012)Franco-Salvador, M., Gupta, P., Rosso, P.: Cross-language plagiarism detection using a multilingual semantic network. In: Serdyukov, P., Braslavski, P., Kuznetsov, S.O., Kamps, J., Rüger, S., Agichtein, E., Segalovich, I., Yilmaz, E. (eds.) ECIR 2013. LNCS, vol. 7814, pp. 710–713. Springer, Heidelberg (2013)Franco-Salvador, M., Gupta, P., Rosso, P.: Graph-based similarity analysis: a new approach to cross-language plagiarism detection. Journal of the Spanish Society of Natural Language Processing (Sociedad Espaola de Procesamiento del Languaje Natural) (50) (2013)Montes-y-Gómez, M., Gelbukh, A., López-López, A., Baeza-Yates, R.: Flexible comparison of conceptual graphs. In: Mayr, H.C., Lazanský, J., Quirchmayr, G., Vogel, P. (eds.) DEXA 2001. LNCS, vol. 2113, pp. 102–111. Springer, Heidelberg (2001)Gupta, P., Barrón-Cedeño, A., Rosso, P.: Cross-language high similarity search using a conceptual thesaurus. In: Catarci, T., Forner, P., Hiemstra, D., Peñas, A., Santucci, G. (eds.) CLEF 2012. LNCS, vol. 7488, pp. 67–75. 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Conf. on Computational Linguistics, COLING 2010, Beijing, China, pp. 997–1005 (2010)Potthast, M., Barrón-Cedeño, A., Stein, B., Rosso, P.: Cross-language plagiarism detection. Language Resources and Evaluation, Special Issue on Plagiarism and Authorship Analysis 45(1), 45–62 (2011)Potthast, M., Eiselt, A., Barrón-Cedeño, A., Stein, B., Rosso, P.: Overview of the 3rd int. competition on plagiarism detection. In: CLEF (Notebook Papers/Labs/Workshop) (2011)Potthast, M., Gollub, T., Hagen, M., Kiesel, J., Michel, M., Oberländer, A., Tippmann, M., Barrón-Cedeño, A., Gupta, P., Rosso, P., et al.: Overview of the 4th international competition on plagiarism detection. In: CLEF (Online Working Notes/Labs/Workshop) (2012)Pouliquen, B., Steinberger, R., Ignat, C.: Automatic linking of similar texts across languages. In: Proc. Recent Advances in Natural Language Processing III, RANLP 2003, pp. 307–316 (2003)Schmid, H.: Probabilistic part-of-speech tagging using decision trees. In: Proc. Int. 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