Academic literature on the topic 'Slot Filling'
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Journal articles on the topic "Slot Filling"
Dai, Yinpei, Yichi Zhang, Hong Liu, Zhijian Ou, Yi Huang, and Junlan Feng. "Elastic CRFs for Open-Ontology Slot Filling." Applied Sciences 11, no. 22 (November 12, 2021): 10675. http://dx.doi.org/10.3390/app112210675.
Full textKhan, Bakhtiar, Faisal Khan, Wasiq Ullah, Muhammad Umair, and Shahid Hussain. "Slot Filling Factor Calculation and Electromagnetic Performance of Single Phase Electrically Excited Flux Switching Motors." Applied Computational Electromagnetics Society 35, no. 8 (October 7, 2020): 922–28. http://dx.doi.org/10.47037/2020.aces.j.350811.
Full textLee, Sang Yul, and Sang Yong Lee. "Filling and Solidification Characteristics during Thixoforming of Copper Rotor for the Electrical Motors." Solid State Phenomena 116-117 (October 2006): 652–55. http://dx.doi.org/10.4028/www.scientific.net/ssp.116-117.652.
Full textLee, Sang Yul, and Sang Yong Lee. "A Study on the Microstructural Defects in Slots of Thixoformed Copper Rotor." Solid State Phenomena 116-117 (October 2006): 300–303. http://dx.doi.org/10.4028/www.scientific.net/ssp.116-117.300.
Full textRoca, Surya, Sophie Rosset, José García, and Álvaro Alesanco. "A Study on the Impacts of Slot Types and Training Data on Joint Natural Language Understanding in a Spanish Medication Management Assistant Scenario." Sensors 22, no. 6 (March 18, 2022): 2364. http://dx.doi.org/10.3390/s22062364.
Full textLim, Jungwoo, Suhyune Son, Songeun Lee, Changwoo Chun, Sungsoo Park, Yuna Hur, and Heuiseok Lim. "Intent Classification and Slot Filling Model for In-Vehicle Services in Korean." Applied Sciences 12, no. 23 (December 5, 2022): 12438. http://dx.doi.org/10.3390/app122312438.
Full textAdel, Heike, and Hinrich Schuetze. "Type-aware Convolutional Neural Networks for Slot Filling." Journal of Artificial Intelligence Research 66 (September 28, 2019): 297–339. http://dx.doi.org/10.1613/jair.1.11725.
Full textDietz, Armin, Antonino Oscar Di Tommaso, Fabrizio Marignetti, Rosario Miceli, and Claudio Nevoloso. "Enhanced Flexible Algorithm for the Optimization of Slot Filling Factors in Electrical Machines." Energies 13, no. 5 (February 26, 2020): 1041. http://dx.doi.org/10.3390/en13051041.
Full textSun, Rui, Lu Rao, and Xingfa Zhou. "A Joint Model of Natural Language Understanding for Human-Computer Conversation in IoT." Wireless Communications and Mobile Computing 2022 (August 21, 2022): 1–10. http://dx.doi.org/10.1155/2022/2074035.
Full textCheng, Shih Ping, Chang Chou Hwang, and Chia Ming Chang. "Design Techniques for Reducing Cogging Torque in SPM Motors Using Shifted Slot Opening." Applied Mechanics and Materials 284-287 (January 2013): 692–96. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.692.
Full textDissertations / Theses on the topic "Slot Filling"
Pink, Glen Alan. "Slot Filling." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/17055.
Full textKim, Joo-Kyung. "Linguistic Knowledge Transfer for Enriching Vector Representations." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1500571436042414.
Full textNovotný, Jiří. "Analýza možností zvýšení účinnosti asynchronních motorů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220919.
Full textChen, Chung Chen, and 陳鍾誠. "XML Retrieval - A Slot-Filling Approach." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/28440213557073524161.
Full text國立臺灣大學
資訊工程學研究所
90
Extensible Markup Language (XML) is widely used in data exchanging and knowledge representation. A retrieval system that understands the content of XML documents is strongly desired. In order to improve the efficiency of XML retrieval systems, we design a set of methods based on a ontology called slot-tree, and use the slot-tree to help the XML retrieval process. One problem for us to building smart computer is that computer cannot understand natural language as good as human. This is called the semantic gap between human and computer. For XML retrieval systems, semantic gap lies on both the query side and document side. The semantic gap in query side is due to the difficulty for human to write structuralized query. The semantic gap in document side is due to the difficulty for computer to understand XML documents. In order to reduce semantic gaps, we design a XML retrieval system based on the slot-tree ontology. The slot-tree ontology is an object-based knowledge representation. First, we design the slot-tree ontology to represent the inner structure of an object. Next, we design a slot-filling algorithm that maps XML documents into the slot-tree ontology in order to catch the semantics. After that, we design a XML retrieval system to reduce the semantic gap based on the slot-tree ontology and slot-filling algorithm. The system contains a slot-based query interface, a semantic retrieval model for XML, and a program that extract summary for browsing. However, the construction of slot-tree is not an easy job, so we design a slot-mining algorithm to construct slot-tree automatically. Slot-mining algorithm is a statistical approach that based on the correlation analysis between tags and words. The highly correlated terms are filled into the slot-tree as values. This algorithm eases the construction process of slot-tree. Two XML collections are used as the test bed of our XML retrieval system, one about butterflies and another about proteins. We found that our XML retrieval system is easy to use and performs well in the retrieval effectiveness and the quality of browsing. Besides, the slot-mining algorithm can fill important words into each slot. However, the mining result should be modified in order to improve the quality of slot-tree. Finally, we conclude our contribution on XML retrieval and compare our methods to some other methods. A qualitative analysis is given in the last chapter. After that, we propose our direction for the future research.
Lo, Kuo-Lung, and 羅國隆. "Ink Drop Filling by a Slot Coating Die for an Electrowetting Display Panel." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/r2wfdx.
Full textBooks on the topic "Slot Filling"
Ultimate Vegetarian Slow Cooker Cookbook: 200 Flavorful and Filling Meatless Recipes That Prep Fast and Cook Slow. Arcas Publishing, 2016.
Find full textEastman, B. R. Bimbofication of Wing Mao: From Nerd to Slut, an Interracial Asian Lust Tale of Rear Action, Stuffing and Filling. Independently Published, 2017.
Find full textJones, Michael, Norman Qureshi, and Kim Rajappan. Atrial fibrillation. Edited by Patrick Davey and David Sprigings. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199568741.003.0116.
Full textBook chapters on the topic "Slot Filling"
Liu, In-Mao. "A slot-filling model of sentence comprehension." In Cognitive Processing of the Chinese and the Japanese Languages, 101–12. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-015-9161-4_6.
Full textLiu, Shudong, Peijie Huang, Zhanbiao Zhu, Hualin Zhang, and Jianying Tan. "Cross-domain Slot Filling with Distinct Slot Entity and Type Prediction." In Natural Language Processing and Chinese Computing, 517–28. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88480-2_41.
Full textTang, Yanxi, Jianzong Wang, Xiaoyang Qu, Nan Zhang, and Jing Xiao. "D-GHNAS for Joint Intent Classification and Slot Filling." In Web and Big Data, 794–807. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60259-8_58.
Full textLiu, Gaoshuo, Shenggen Ju, and Yu Chen. "Binary Label-Aware Transfer Learning for Cross-Domain Slot Filling." In Neural Information Processing, 359–68. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-92270-2_31.
Full textChen, Zheng, Suzanne Tamang, Adam Lee, Xiang Li, Marissa Passantino, and Heng Ji. "Top-Down and Bottom-Up: A Combined Approach to Slot Filling." In Information Retrieval Technology, 300–309. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17187-1_29.
Full textKong, Junsheng, Yi Cai, Da Ren, and Zilu Li. "Deep Multi-task Learning with Cross Connected Layer for Slot Filling." In Natural Language Processing and Chinese Computing, 308–17. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32236-6_27.
Full textWu, Tongtong, Meng Wang, Huan Gao, Guilin Qi, and Weizhuo Li. "Zero-Shot Slot Filling via Latent Question Representation and Reading Comprehension." In PRICAI 2019: Trends in Artificial Intelligence, 123–36. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29894-4_10.
Full textKale, Mihir, and Aditya Siddhant. "MixOut: A Simple Yet Effective Data Augmentation Scheme for Slot-Filling." In Lecture Notes in Electrical Engineering, 279–88. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8395-7_21.
Full textWakabayashi, Kei, Johane Takeuchi, and Mikio Nakano. "Segmentation-Based Formulation of Slot Filling Task for Better Generative Modeling." In Lecture Notes in Electrical Engineering, 17–31. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-5538-9_2.
Full textWeichselbraun, Albert, Roger Waldvogel, Andreas Fraefel, Alexander van Schie, and Philipp Kuntschik. "Slot Filling for Extracting Reskilling and Upskilling Options from the Web." In Natural Language Processing and Information Systems, 279–90. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08473-7_25.
Full textConference papers on the topic "Slot Filling"
Lu, Hengtong, Zhuoxin Han, Caixia Yuan, Xiaojie Wang, Shuyu Lei, Huixing Jiang, and Wei Wu. "Slot Transferability for Cross-domain Slot Filling." In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.findings-acl.440.
Full textYu, Mengshi, Jian Liu, Yufeng Chen, Jinan Xu, and Yujie Zhang. "Cross-Domain Slot Filling as Machine Reading Comprehension." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/550.
Full textDou, Quansheng, and Panpan Cui. "Slot Filling Using En-Training." In 2019 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). IEEE, 2019. http://dx.doi.org/10.1109/cyberc.2019.00053.
Full textShin, Youhyun, Kang Min Yoo, and Sang-goo Lee. "Slot Filling with Delexicalized Sentence Generation." In Interspeech 2018. ISCA: ISCA, 2018. http://dx.doi.org/10.21437/interspeech.2018-1808.
Full textYan, Yang, Junda Ye, Zhongbao Zhang, and Liwen Wang. "AISFG: Abundant Information Slot Filling Generator." In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.naacl-main.308.
Full textJiang, Chengyue, Zijian Jin, and Kewei Tu. "Neuralizing Regular Expressions for Slot Filling." In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.emnlp-main.747.
Full textPapanikolaou, Yannis, Marlene Staib, Justin Joshua Grace, and Francine Bennett. "Slot Filling for Biomedical Information Extraction." In Proceedings of the 21st Workshop on Biomedical Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.bionlp-1.7.
Full textGoo, Chih-Wen, Guang Gao, Yun-Kai Hsu, Chih-Li Huo, Tsung-Chieh Chen, Keng-Wei Hsu, and Yun-Nung Chen. "Slot-Gated Modeling for Joint Slot Filling and Intent Prediction." In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/n18-2118.
Full textGeorgiadou, Despoina, Vassilios Diakoloukas, Vassilios Tsiaras, and Vassilios Digalakis. "ClockWork-RNN Based Architectures for Slot Filling." In Interspeech 2017. ISCA: ISCA, 2017. http://dx.doi.org/10.21437/interspeech.2017-1075.
Full textDao, Mai Hoang, Thinh Hung Truong, and Dat Quoc Nguyen. "Intent Detection and Slot Filling for Vietnamese." In Interspeech 2021. ISCA: ISCA, 2021. http://dx.doi.org/10.21437/interspeech.2021-618.
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