Ofir Press , UW Ph. We introduce a generative model positing latent topics and cross-cutting positions that gives special treatment to person mentions and opinion words. SAGE is an algorithm for learning sparse representations of text you can read more about it here. We introduce a probabilistic model of some of the important aspects of that process: Throughout this proposal, we will present several examples of strategic behavior and how we can model it computationally. Nelson Liu , UW undergraduate.
The results are validated against a set of preregistered, domain expert authored hypotheses. We frame the authoring process as a decision theoretic problem — the observed text is the result of an author maximizing her utility. The social attributes of an author deeply influence and bias his language production; while authors are motivated to evoke responses from his audience. In this work, we propose an integrated model to leverage side information. For Entity Linking, we analyze IR approaches and SVM classification in the disambiguation stage and develop a supervised learner for combining these approaches. She is a research scientist at Expedia. Extensive past work in quantitative political science provides a framework for empirically modeling the decisions of justices and how they relate to text.
Secondly, as entity linking annotation is expensive and labor intensive, to automate the annotation process without compromise of accuracy, we propose an instance selection strategy to effectively utilize the automatically generated annotation. After performing validation and robustness checks, we fit the model using presidential candidates’ speeches from and Shay Cohen defended his Ph.
Sarah DreierUW post-doc.
We develop a model to identify ideological cues in political text. Lucy LinUW Ph. These advancements give statistical significant improvement to entity linking individually. Jeju Island, Korea abstract bibtex paper slides We present a statistical model for canonicalizing named entity mentions into a table whose rows represent entities and whose columns yogataka attributes or parts of attributes.
LTI PhD Thesis Defense: Dani Yogatama
The model is novel in that it incorporates entity context, surface features, first-order dependencies among attribute-parts, and a notion of noise. Yanchuan Sim, Noah A. He is a researcher at AI2. Ofir PressUW Ph. Barcelona, Catalonia, Spain abstract bibtex paper Entity linking maps name mentions in the documents to entries in a knowledge base through resolving the name variations and ambiguities.
Our proposed method is a regression-based latent factor model which jointly models user arguments, interactions, and attributes. In this paper, we propose three advancements for entity linking. Yanchuan Sim, Bryan R. Lastly, we discuss methods and challenges to characterize authors’ strategic behavior in the domains of scientific community and judicial politics.
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.
Waleed Ammar defended his Ph. Tae Yano defended her Ph.
Gregory Diamos – Et In Arcadia Ego
He is a post-doctoral researcher at the University of Massachusetts at Amherst. Smith dain, Jing Jiang. However, most current work does not address an important problem: Lastly, topic modeling is used to model the semantic topics of the articles.
Furthermore, according to our error analysis, quite some errors are caused due to the different Wikipedia version is used, which hinder our system to show significant better performance. He is a lecturer at the University of Edinburgh. Elizabeth ClarkUW Ph.
hi. i am yanchuan.
People write everyday — articles, blogs, emails — with a purpose and an audience in mind. Entity linking maps name mentions in the documents to entries in a knowledge base through resolving the name variations and ambiguities.
ARK researchers and alumni are leaders in natural language processing, machine learning, and computational social science. Tal AugustUW Ph. He is an assistant professor at the University of Massachusetts at Amherst.
CoMeT | Speaker Profile
We apply a ykgatama Bayesian HMM to infer the proportions of ideologies each candidate uses in each campaign. He is head of research at Unbabel. He is an assistant professor at Georgetown University.