Wlodek Zadrozny


2019

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UVA Wahoos at SemEval-2019 Task 6: Hate Speech Identification using Ensemble Machine Learning
Murugesan Ramakrishnan | Wlodek Zadrozny | Narges Tabari
Proceedings of the 13th International Workshop on Semantic Evaluation

With the growth in the usage of social media, it has become increasingly common for people to hide behind a mask and abuse others. We have attempted to detect such tweets and comments that are malicious in intent, which either targets an individual or a group. Our best classifier for identifying offensive tweets for SubTask A (Classifying offensive vs. nonoffensive) has an accuracy of 83.14% and a f1- score of 0.7565 on the actual test data. For SubTask B, to identify if an offensive tweet is targeted (If targeted towards an individual or a group), the classifier performs with an accuracy of 89.17% and f1-score of 0.5885. The paper talks about how we generated linguistic and semantic features to build an ensemble machine learning model. By training with more extracts from different sources (Facebook, and more tweets), the paper shows how the accuracy changes with additional training data.

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Topological Data Analysis for Discourse Semantics?
Ketki Savle | Wlodek Zadrozny | Minwoo Lee
Proceedings of the 13th International Conference on Computational Semantics - Student Papers

In this paper we present new results on applying topological data analysis to discourse structures. We show that topological information, extracted from the relationships between sentences can be used in inference, namely it can be applied to the very difficult legal entailment given in the COLIEE 2018 data set. Previous results of Doshi and Zadrozny (2018) and Gholizadeh et al. (2018) show that topological features are useful for classification. The applications of computational topology to entailment are novel in our view provide a new set of tools for discourse semantics: computational topology can perhaps provide a bridge between the brittleness of logic and the regression of neural networks. We discuss the advantages and disadvantages of using topological information, and some open problems such as explainability of the classifier decisions.

2018

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Causality Analysis of Twitter Sentiments and Stock Market Returns
Narges Tabari | Piyusha Biswas | Bhanu Praneeth | Armin Seyeditabari | Mirsad Hadzikadic | Wlodek Zadrozny
Proceedings of the First Workshop on Economics and Natural Language Processing

Sentiment analysis is the process of identifying the opinion expressed in text. Recently, it has been used to study behavioral finance, and in particular the effect of opinions and emotions on economic or financial decisions. In this paper, we use a public dataset of labeled tweets that has been labeled by Amazon Mechanical Turk and then we propose a baseline classification model. Then, by using Granger causality of both sentiment datasets with the different stocks, we shows that there is causality between social media and stock market returns (in both directions) for many stocks. Finally, We evaluate this causality analysis by showing that in the event of a specific news on certain dates, there are evidences of trending the same news on Twitter for that stock.

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UNCC QA: Biomedical Question Answering system
Abhishek Bhandwaldar | Wlodek Zadrozny
Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering

In this paper, we detail our submission to the BioASQ competition’s Biomedical Semantic Question and Answering task. Our system uses extractive summarization techniques to generate answers and has scored highest ROUGE-2 and Rogue-SU4 in all test batch sets. Our contributions are named-entity based method for answering factoid and list questions, and an extractive summarization techniques for building paragraph-sized summaries, based on lexical chains. Our system got highest ROUGE-2 and ROUGE-SU4 scores for ideal-type answers in all test batch sets. We also discuss the limitations of the described system, such lack of the evaluation on other criteria (e.g. manual). Also, for factoid- and list -type question our system got low accuracy (which suggests that our algorithm needs to improve in the ranking of entities).

2017

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SentiHeros at SemEval-2017 Task 5: An application of Sentiment Analysis on Financial Tweets
Narges Tabari | Armin Seyeditabari | Wlodek Zadrozny
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

Sentiment analysis is the process of identifying the opinion expressed in text. Recently it has been used to study behavioral finance, and in particular the effect of opinions and emotions on economic or financial decisions. SemEval-2017 task 5 focuses on the financial market as the domain for sentiment analysis of text; specifically, task 5, subtask 1 focuses on financial tweets about stock symbols. In this paper, we describe a machine learning classifier for binary classification of financial tweets. We used natural language processing techniques and the random forest algorithm to train our model, and tuned it for the training dataset of Task 5, subtask 1. Our system achieves the 7th rank on the leaderboard of the task.

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Towards Semantic Modeling of Contradictions and Disagreements: A Case Study of Medical Guidelines
Wlodek Zadrozny | Hossein Hematialam | Luciana Garbayo
IWCS 2017 — 12th International Conference on Computational Semantics — Short papers

2001

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Conversational Sales Assistant for Online Shopping
Margo Budzikowska | Joyce Chai | Sunil Govindappa | Veronika Horvath | Nanda Kambhatla | Nicolas Nicolov | Wlodek Zadrozny
Proceedings of the First International Conference on Human Language Technology Research

2000

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A Tool for Automated Revision of Grammars for NLP Systems
Nanda Kambhatla | Wlodek Zadrozny
Sixth Applied Natural Language Processing Conference

1994

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NL Understanding with a Grammar of Constructions
Wlodek Zadrozny | Marcin Szummer | Stanislaw Jarecki | David E. Johnson | Leora Morgenstern
COLING 1994 Volume 2: The 15th International Conference on Computational Linguistics

1992

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On compositional semantics
Wlodek Zadrozny
COLING 1992 Volume 1: The 14th International Conference on Computational Linguistics

1991

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Semantics of Paragraphs
Wlodek Zadrozny | Karen Jensen
Computational Linguistics, Volume 17, Number 2, June 1991

1990

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Expressive Power of Grammatical Formalisms
Alexis Manaster-Ramer | Wlodek Zadrozny
COLING 1990 Volume 3: Papers presented to the 13th International Conference on Computational Linguistics