I2R-NUS team submitted two results with the full system and the partial system for diagnosis purpose. Dani Yogatama defended his Ph. We consider three particular domains — political campaigns, the scientific community, and the judiciary — using our models and develop the necessary tools to evaluate our assumptions and hypotheses. He is an assistant professor at the Toyota Technological Institute at Chicago. He is a data scientist at Civis Analytics.
The model reveals latent factions, or groups of individuals whom we expect to collaborate more closely within their faction, cite within the faction using language distinct from citation outside the faction, and be largely understandable through the language used when cited from without. He is a lecturer at the University of Edinburgh. We evaluate the resulting representation’s usefulness in attaching opinionated documents to arguments and its consistency with human judgements about positions. Dani Yogatama defended his Ph. Variants of our model lead to improved predictive accuracy of citations given texts and texts given authors. Yanchuan Sim, Bryan R. ARK researchers and alumni are leaders in natural language processing, machine learning, and computational social science.
For Entity Linking, we analyze IR approaches and SVM classification in the disambiguation stage and develop a supervised learner for combining these approaches.
Lastly, topic modeling is used to model the semantic topics of the articles. He is an assistant professor at the Toyota Technological Institute at Chicago.
Firstly, expanding acronyms can effectively reduce the ambiguity of the acronym mentions. To make this idea concrete, we consider the societally important decisions of the Supreme Court of the United States.
We consider three particular domains — political campaigns, the scientific community, and the judiciary — using our models and develop the necessary tools to evaluate our assumptions and hypotheses.
The model reveals latent factions, or groups of individuals whom we expect to collaborate more closely within their faction, cite within the faction using language distinct from citation outside the faction, and be largely understandable through the language used when cited from without.
We introduce a probabilistic model of some of the important aspects of that process: Entity linking maps name mentions in the documents to entries in a knowledge base through resolving the name variations and ambiguities. Jungo KasaiUW Ph. Humans write lawyers submit briefs, legislators draft bills, scientists publish papers, teenagers tweet, and politicians give speeches which are first written by their speechwriters for a multitude of purposes.
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He is a data scientist at Civis Analytics. We conduct an exploratory data analysis on the ACL Anthology.
In this thesis, I propose a framework for text analysis based on the idea that yigatama production is a strategic process dependent on author’s social attributes and his beliefs about audience responses.
In this paper, we propose a supervised learning algorithm to expand more complicated acronyms encountered, which leads to In clustering step, three clustering algorithms: In each of these domains, our models yield better response prediction accuracy and provide an interpretable means of investigating the underlying processes. He is a research scientist at DeepMind. He is a research scientist at Semantic Machines. We introduce a generative model positing latent topics and cross-cutting positions that gives special treatment to person mentions and opinion words.
After performing validation and robustness checks, we fit the model using presidential candidates’ speeches from and Choosing the right things to say is a complex process and requires significant effort.
SmithJing Jiang. We apply a domain-informed Bayesian HMM to infer yogagama proportions of ideologies each candidate uses in each campaign.
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Despite the sparsity of user stances, users may provide rich side information, for example, users may write arguments to back up their stances, interact with each other, and provide biographical information.
Following, we use the Supreme Court as a case study to incorporate utility functions into models of text. He is head of research at Unbabel. She is a research scientist at Expedia. The model dami novel in that it incorporates entity context, surface features, first-order dependencies among attribute-parts, and a notion of noise. AcreeJustin H. Extensive past work in quantitative political science provides a framework for empirically modeling the decisions of justices and how they relate to text.
Sarah DreierUW post-doc.
In this paper, we propose three advancements for entity linking. Throughout this proposal, we will present several examples of strategic behavior and how we can model it computationally. Yanchuan Sim, Thesiw A. Elizabeth ClarkUW Ph.