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| | ==QA== | | ==QA== |
| | ===2014-08-22=== | | ===2014-08-22=== |
| − | '''desin:'''
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| − | 1. a more detailed design of question classification
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| − | 2. a more detailed design of keyword compensation
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| − | 3. a more detailed design of word normalization, word expansion
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| − | '''PPT''' [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/3/3c/%E9%98%85%E8%AF%BB.pdf]
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| − | '''learn'''
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| − | * the word weight that computed using preme
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| − | * the translate model for similarity of word
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| − | * Queston answering with subgraph embeddings to learn the relation and entity matrix
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| − | '''paper:'''
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| − | 1 Zhang, Guangzhi, et al. "The Architecture of ProMe Instant Question Answering System." Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2013 International Conference on. IEEE, 2013.
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| − | 2 Park, Jungyeul, Jong Gun Lee, and Beatrice Daille. "UNPMC: Naive approach to extract keyphrases from scientific articles." Proceedings of the 5th international workshop on semantic evaluation. Association for Computational Linguistics, 2010.
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| − | 3.Guangyou Zhou, Li Cai, Jun Zhao, and Kang Liu. 2011. Phrase-based translation model for question retrieval in community question answer archives. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1 (HLT '11), Vol. 1. Association for Computational Linguistics, Stroudsburg, PA, USA, 653-662.
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| − | 4. Lei Zou, Ruizhe Huang, Haixun Wang, Jeffrey Xu Yu, Wenqiang He, and Dongyan Zhao. 2014. Natural language question answering over RDF: a graph data driven approach. In Proceedings of the 2014 ACM SIGMOD international conference on Management of data (SIGMOD '14). ACM, New York, NY, USA, 313-324. DOI=10.1145/2588555.2610525 http://doi.acm.org/10.1145/2588555.2610525
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| − | 4. Shekarpour, Saeedeh, et al. "SINA: Semantic interpretation of user queries for question answering on interlinked data." Web Semantics: Science, Services and Agents on the World Wide Web 2014).
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| − | 5. Bordes, Antoine, Sumit Chopra, and Jason Weston. "Question Answering with Subgraph Embeddings." arXiv preprint arXiv:1406.3676 (2014).
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| − | 6. Choi, Erik, Vanessa Kitzie, and Chirag Shah. "A machine learning-based approach to predicting success of questions on social question-answering." (2013).
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| − | 7. iphaine Dalmas, Bonnie Webber, Answer comparison in automated question answering, Journal of Applied Logic, Volume 5, Issue 1, March 2007, Pages 104-120, ISSN 1570-8683, http://dx.doi.org/10.1016/j.jal.2005.12.002.
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| − | 8. Zhou, Guangyou, et al. "Statistical Machine Translation Improves Question Retrieval in Community Question Answering via Matrix Factorization." ACL (1). 2013.
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| − | 9. Sherzod Hakimov, Hakan Tunc, Marlen Akimaliev, and Erdogan Dogdu. 2013. Semantic question answering system over linked data using relational patterns. In Proceedings of the Joint EDBT/ICDT 2013 Workshops (EDBT '13). ACM, New York, NY, USA, 83-88. DOI=10.1145/2457317.2457331 http://doi.acm.org/10.1145/2457317.2457331
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| − | 10. Wu, Youzheng, et al. "Leveraging Social Q&A Collections for Improving Complex Question Answering." Computer Speech & Language (2014).
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| − | 11. Giannone, Cristina, Valentina Bellomaria, and Roberto Basili. "A HMM-based approach to question answering against linked data." Proceedings of the Question Answering over Linked Data lab (QALD-3) at CLEF (2013).
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| | ==RNN== | | ==RNN== |
1. "Efficient Estimation of Word Representations in Vector Space". Tomas Mikolov
2. Distributed Representations ofWords and Phrases and their Compositionality. Tomas Mikolov
3. Deep Learning Embeddings for Discontinuous Linguistic Units
