Relevant bibliographies by topics / Hybrid Question Answering

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Hybrid Question Answering'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Hybrid Question Answering"

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Vargas-Vera, M., and M. D. Lytras. "AQUA: hybrid architecture for question answering services." IET Software 4, no. 6 (2010): 418. http://dx.doi.org/10.1049/iet-sen.2010.0053.

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Sun, Yuan, and Tianci Xia. "A Hybrid Network Model for Tibetan Question Answering." IEEE Access 7 (2019): 52769–77. http://dx.doi.org/10.1109/access.2019.2911320.

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Abass, Ayatallah Gamal, Sameh Abd El-Ghany, and Ahmed Abo Elfetoh. "Improving Question Answering System based on a Hybrid Technique." Journal of Computer Science 14, no. 9 (2018): 1202–12. http://dx.doi.org/10.3844/jcssp.2018.1202.1212.

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Jelodar, Hamed, Yongli Wang, Ahamdreza Vajdi, et al. "A Hybrid Fuzzy System via Topic Model for Recommending Highlight Topics of CQA in Developer Communities." Journal of Circuits, Systems and Computers 29, no. 15 (2020): 2050248. http://dx.doi.org/10.1142/s0218126620502485.

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Question-answering (QA) websites supply a quickly growing source of useful information in numerous areas. These platforms present novel opportunities for online users to supply solutions, they also pose numerous challenges with the ever-growing size of the QA community. QA sites supply platforms for users to cooperate in the form of asking questions or giving answers. Stack Overflow is a massive source of information for both industry and academic practitioners, and its analysis can supply useful insights. Topic modeling of Stack Overflow is very beneficial for pattern discovery and behavior a
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Kim, Incheol. "Visual Experience-Based Question Answering with Complex Multimodal Environments." Mathematical Problems in Engineering 2020 (November 19, 2020): 1–18. http://dx.doi.org/10.1155/2020/8567271.

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This paper proposes a novel visual experience-based question answering problem (VEQA) and the corresponding dataset for embodied intelligence research that requires an agent to do actions, understand 3D scenes from successive partial input images, and answer natural language questions about its visual experiences in real time. Unlike the conventional visual question answering (VQA), the VEQA problem assumes both partial observability and dynamics of a complex multimodal environment. To address this VEQA problem, we propose a hybrid visual question answering system, VQAS, integrating a deep neu
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Lao, Mingrui, Yanming Guo, Nan Pu, Wei Chen, Yu Liu, and Michael S. Lew. "Multi-stage hybrid embedding fusion network for visual question answering." Neurocomputing 423 (January 2021): 541–50. http://dx.doi.org/10.1016/j.neucom.2020.10.071.

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Kundu, Dipankar, Rajat Kumar Pal, and Deba Prasad Mandal. "Topic sensitive hybrid expertise retrieval system in community question answering services." Knowledge-Based Systems 211 (January 2021): 106535. http://dx.doi.org/10.1016/j.knosys.2020.106535.

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Kundu, Dipankar, Rajat Kumar Pal, and Deba Prasad Mandal. "Preference enhanced hybrid expertise retrieval system in community question answering services." Decision Support Systems 129 (February 2020): 113164. http://dx.doi.org/10.1016/j.dss.2019.113164.

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Elalfy, Dalia, Walaa Gad, and Rasha Ismail. "A hybrid model to predict best answers in question answering communities." Egyptian Informatics Journal 19, no. 1 (2018): 21–31. http://dx.doi.org/10.1016/j.eij.2017.06.002.

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Kundu, Dipankar, Rajat Kumar Pal, and Deba Prasad Mandal. "Time-aware hybrid expertise retrieval system in community question answering services." Applied Intelligence 51, no. 10 (2021): 6914–31. http://dx.doi.org/10.1007/s10489-020-02177-2.

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Dissertations / Theses on the topic "Hybrid Question Answering"

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Bahmid, Rawan. "Hybrid Question Answering over Linked Data." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37976.

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The emergence of Linked Data in the form of knowledge graphs in RDF has been one of the most recent evolutions of the Semantic Web. This led to the development of question answering systems based on RDF and SPARQL to allow end users to access and benefit from these knowledge graphs. However, a lot of information on the Web is still unstructured, which restricts the ability of answering questions whose answer does not exist in a knowledge base. To tackle this issue, hybrid question answering has emerged as an important challenge. In fact, hybrid question answering entails the task of question a
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Usbeck, Ricardo. "Knowledge Extraction for Hybrid Question Answering." Doctoral thesis, Universitätsbibliothek Leipzig, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-225097.

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Since the proposal of hypertext by Tim Berners-Lee to his employer CERN on March 12, 1989 the World Wide Web has grown to more than one billion Web pages and still grows. With the later proposed Semantic Web vision,Berners-Lee et al. suggested an extension of the existing (Document) Web to allow better reuse, sharing and understanding of data. Both the Document Web and the Web of Data (which is the current implementation of the Semantic Web) grow continuously. This is a mixed blessing, as the two forms of the Web grow concurrently and most commonly contain different pieces of information. Mod
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Ramachandra, Rao Sanjay Kamath. "Question Answering with Hybrid Data and Models." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASS024.

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La recherche de réponses à des questions relève de deux disciplines : le traitement du langage naturel et la recherche d’information. L’émergence de l’apprentissage profond dans plusieurs domaines de recherche tels que la vision par ordinateur, le traitement du langage naturel etc. a conduit à l’émergence de modèles de bout en bout. Les travaux actuels de l’état de l’art en question-réponse (QR) visent à mettre en oeuvre de tels modèles. Dans le cadre du projet GoASQ, l’objectif est d’étudier, comparer et combiner différentes approches pour répondre à des questions formulées en langage naturel
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Usbeck, Ricardo [Verfasser], Klaus-Peter [Gutachter] Fähnrich, Philipp [Gutachter] Cimiano, Ngomo Axel-Cyrille [Akademischer Betreuer] Ngonga, and Klaus-Peter [Akademischer Betreuer] Fähnrich. "Knowledge Extraction for Hybrid Question Answering / Ricardo Usbeck ; Gutachter: Klaus-Peter Fähnrich, Philipp Cimiano ; Akademische Betreuer: Axel-Cyrille Ngonga Ngomo, Klaus-Peter Fähnrich." Leipzig : Universitätsbibliothek Leipzig, 2017. http://d-nb.info/1173734775/34.

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Usbeck, Ricardo. "Knowledge Extraction for Hybrid Question Answering." Doctoral thesis, 2016. https://ul.qucosa.de/id/qucosa%3A15647.

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Since the proposal of hypertext by Tim Berners-Lee to his employer CERN on March 12, 1989 the World Wide Web has grown to more than one billion Web pages and still grows. With the later proposed Semantic Web vision,Berners-Lee et al. suggested an extension of the existing (Document) Web to allow better reuse, sharing and understanding of data. Both the Document Web and the Web of Data (which is the current implementation of the Semantic Web) grow continuously. This is a mixed blessing, as the two forms of the Web grow concurrently and most commonly contain different pieces of information. Mod
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Aghaebrahimian, Ahmad. "Hybridní hluboké metody pro automatické odpovídání na otázky." Doctoral thesis, 2019. http://www.nusl.cz/ntk/nusl-393809.

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Title: Hybrid Deep Question Answering Author: Ahmad Aghaebrahimian Institute: Institute of Formal and Applied Linguistics Supervisor: RNDr. Martin Holub, Ph.D., Institute of Formal and Applied Lin- guistics Abstract: As one of the oldest tasks of Natural Language Processing, Question Answering is one of the most exciting and challenging research areas with lots of scientific and commercial applications. Question Answering as a discipline in the conjunction of computer science, statistics, linguistics, and cognitive science is concerned with building systems that automatically retrieve answers
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Book chapters on the topic "Hybrid Question Answering"

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Park, Seonyeong, Hyosup Shim, Sangdo Han, Byungsoo Kim, and G. G. Lee. "Multi-Source Hybrid Question Answering System." In Natural Language Dialog Systems and Intelligent Assistants. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19291-8_23.

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Gao, Peng, Hongsheng Li, Shuang Li, et al. "Question-Guided Hybrid Convolution for Visual Question Answering." In Computer Vision – ECCV 2018. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01246-5_29.

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Usbeck, Ricardo, Axel-Cyrille Ngonga Ngomo, Lorenz Bühmann, and Christina Unger. "HAWK – Hybrid Question Answering Using Linked Data." In The Semantic Web. Latest Advances and New Domains. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18818-8_22.

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Gupta, Poonam, and Vishal Gupta. "Hybrid Approach for Punjabi Question Answering System." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04960-1_12.

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Duong, Phuc H., Hien T. Nguyen, Duy D. Nguyen, and Hao T. Do. "A Hybrid Approach to Answer Selection in Question Answering Systems." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75429-1_16.

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Ofoghi, Bahadorreza, John Yearwood, and Ranadhir Ghosh. "A Hybrid Question Answering Schema Using Encapsulated Semantics in Lexical Resources." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11941439_160.

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Cortes, Eduardo G., Vinicius Woloszyn, and Dante A. C. Barone. "When, Where, Who, What or Why? A Hybrid Model to Question Answering Systems." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99722-3_14.

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Rani, Monika, Maybin K. Muyeba, and O. P. Vyas. "A Hybrid Approach Using Ontology Similarity and Fuzzy Logic for Semantic Question Answering." In Smart Innovation, Systems and Technologies. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07353-8_69.

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Liang, Huaizhong, Kaibiao Lin, and Shunzhi Zhu. "Short Text Similarity Hybrid Algorithm for a Chinese Medical Intelligent Question Answering System." In Technology-Inspired Smart Learning for Future Education. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5390-5_11.

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Liang, Zhengzhong, Yiyun Zhao, and Mihai Surdeanu. "Using the Hammer only on Nails: A Hybrid Method for Representation-Based Evidence Retrieval for Question Answering." In Lecture Notes in Computer Science. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72113-8_22.

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Conference papers on the topic "Hybrid Question Answering"

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Grau, Brigitte, and Anne-Laure Ligozat. "A Corpus for Hybrid Question Answering Systems." In Companion of the The Web Conference 2018. ACM Press, 2018. http://dx.doi.org/10.1145/3184558.3191540.

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Diederich, J., and D. L. Long. "Efficient question answering in a hybrid system." In 1991 IEEE International Joint Conference on Neural Networks. IEEE, 1991. http://dx.doi.org/10.1109/ijcnn.1991.170447.

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Delmonte, Rodolfo. "Hybrid systems for information extraction and question answering." In the Workshop. Association for Computational Linguistics, 2006. http://dx.doi.org/10.3115/1629808.1629811.

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Chung, Euisok, Soojong Lim, Yi-Gyu Hwang, and Myung-Gil Jang. "Hybrid named entity recognition for question-answering system." In Interspeech 2004. ISCA, 2004. http://dx.doi.org/10.21437/interspeech.2004-45.

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Sherkat, Ehsan, and Mojgan Farhoodi. "A hybrid approach for question classification in Persian automatic question answering systems." In 2014 4th International eConference on Computer and Knowledge Engineering (ICCKE). IEEE, 2014. http://dx.doi.org/10.1109/iccke.2014.6993377.

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Gao, Tiantian, Paul Fodor, and Michael Kifer. "High Accuracy Question Answering via Hybrid Controlled Natural Language." In 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI). IEEE, 2018. http://dx.doi.org/10.1109/wi.2018.0-112.

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Balakrishna, Mithun, Steven Werner, Marta Tatu, Tatiana Erekhinskaya, and Dan Moldovan. "K-Extractor: Automatic Knowledge Extraction for Hybrid Question Answering." In 2016 IEEE Tenth International Conference on Semantic Computing (ICSC). IEEE, 2016. http://dx.doi.org/10.1109/icsc.2016.30.

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Ma, Rongqiang, Jian Zhang, Miao Li, Lei Chen, and Jin Gao. "Hybrid answer selection model for non-factoid question answering." In 2017 International Conference on Asian Language Processing (IALP). IEEE, 2017. http://dx.doi.org/10.1109/ialp.2017.8300620.

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Harzig, Philipp, Christian Eggert, and Rainer Lienhart. "Visual Question Answering With a Hybrid Convolution Recurrent Model." In ICMR '18: International Conference on Multimedia Retrieval. ACM, 2018. http://dx.doi.org/10.1145/3206025.3206054.

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Cheng, Hao, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, and Jianfeng Gao. "UnitedQA: A Hybrid Approach for Open Domain Question Answering." In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.acl-long.240.

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