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Data sets I have developed and used in my research.
The code is an implementation of the paper http://www.aclweb.org/anthology/C14-1220 using tensorflow.
The CNN architecture implemented is inspired be Nguyen et al. 2015
In this project, we provide our implementations of a word-level and sentence-level combined Bidirectional GRU network (BGRU+2ATT).
In this project, we provide our implementations of CNN [Zeng et al., 2014] and PCNN [Zeng et al.,2015] and their extended version with sentence-level attention scheme [Lin et al., 2016] .
NYT10 is originally released by the paper "Sebastian Riedel, Limin Yao, and Andrew McCallum. Modeling relations and their mentions without labeled text."
Relation extraction on an open-domain knowledge base
Accompanying repository for our EMNLP 2017 paper. It contains the code to replicate the experiments and the pre-trained models for sentence-level relation extraction.
Convolutional Neural Network for Relation Extraction
Presentation for EMNLP 2015
Course Material. 20th European Summer School in Logic, Language
and Information (ESSLLI 2008), Freie und Hansestadt Hamburg,
Germany, 4–15 August 2008
Some of the tools listed below are discussed in detail in the "Seven Layers of Social Media Analytics" book. Applications (no programming skills required) DiscoverText: http://www.screencast.com/t/VKLqaekPz Demographics Pro: http://www.demographicspro.com/ NodeXL: https://nodexl.codeplex.com/ Twitonomy: http://www.twitonomy.com/ RapidMiner: http://docs.rapidminer.com/studio/how-to/cloud-connectivity/twitter.html KPI6: https://www.kpi6.com/ Talend: http://www.datalytyx.com/twitter-sentiment-analysis-using-talend/ KNIME: https://www.knime.org/blog/knime-twitter-nodes Pentaho: http://www.patlaf.com/query-twitter-api-with-pentaho-pdi-kettle/ iScience Maps: http://maps.iscience.deusto.es/ Nexalogy: https://nexalogy.com/ Tools/Scripts/Modules (require programming skills) Twarc: https://github.com/edsu/twarc Twitter for…