Proceedings of the conference. Association for Computational Linguistics. Meeting最新文献_第7页

Measuring idiosyncratic interests in children with autism. 测量自闭症儿童的特殊兴趣。

Proceedings of the conference. Association for Computational Linguistics. Meeting Pub Date : 2015-07-01 DOI: 10.3115/v1/p15-2035

Masoud Rouhizadeh, Emily Prud'hommeaux, Jan van Santen, Richard Sproat

引用次数: 5

An Extension of BLANC to System Mentions. BLANC对系统提及的扩展。

Proceedings of the conference. Association for Computational Linguistics. Meeting Pub Date : 2014-06-01 DOI: 10.3115/v1/P14-2005

Xiaoqiang Luo, Sameer Pradhan, Marta Recasens, Eduard Hovy

引用次数: 36

Scoring Coreference Partitions of Predicted Mentions: A Reference Implementation. 预测提及的评分参考分区:参考实现。

Proceedings of the conference. Association for Computational Linguistics. Meeting Pub Date : 2014-06-01 DOI: 10.3115/v1/P14-2006

Sameer Pradhan, Xiaoqiang Luo, Marta Recasens, Eduard Hovy, Vincent Ng, Michael Strube

{"title":"Scoring Coreference Partitions of Predicted Mentions: A Reference Implementation.","authors":"Sameer Pradhan, Xiaoqiang Luo, Marta Recasens, Eduard Hovy, Vincent Ng, Michael Strube","doi":"10.3115/v1/P14-2006","DOIUrl":"https://doi.org/10.3115/v1/P14-2006","url":null,"abstract":"The definitions of two coreference scoring metrics- B3 and CEAF-are underspecified with respect to predicted, as opposed to key (or gold) mentions. Several variations have been proposed that manipulate either, or both, the key and predicted mentions in order to get a one-to-one mapping. On the other hand, the metric BLANC was, until recently, limited to scoring partitions of key mentions. In this paper, we (i) argue that mention manipulation for scoring predicted mentions is unnecessary, and potentially harmful as it could produce unintuitive results; (ii) illustrate the application of all these measures to scoring predicted mentions; (iii) make available an open-source, thoroughly-tested reference implementation of the main coreference evaluation measures; and (iv) rescore the results of the CoNLL-2011/2012 shared task systems with this implementation. This will help the community accurately measure and compare new end-to-end coreference resolution algorithms.","PeriodicalId":74541,"journal":{"name":"Proceedings of the conference. Association for Computational Linguistics. Meeting","volume":"2014 ","pages":"30-35"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3115/v1/P14-2006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35225788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 185

Interpretable Semantic Vectors from a Joint Model of Brain- and Text-Based Meaning. 大脑和文本意义联合模型中的可解释语义向量

Proceedings of the conference. Association for Computational Linguistics. Meeting Pub Date : 2014-06-01 DOI: 10.3115/v1/p14-1046

Alona Fyshe, Partha P Talukdar, Brian Murphy, Tom M Mitchell

引用次数: 0

Evaluation of SPARQL query generation from natural language questions. 评估从自然语言问题生成的SPARQL查询。

Proceedings of the conference. Association for Computational Linguistics. Meeting Pub Date : 2013-09-01

K Bretonnel Cohen, Jin-Dong Kim

引用次数: 0

Topic Modeling Based Classification of Clinical Reports. 基于主题建模的临床报告分类。

Proceedings of the conference. Association for Computational Linguistics. Meeting Pub Date : 2013-08-01

Efsun Sarioglu, Kabir Yadav, Hyeong-Ah Choi

{"title":"Topic Modeling Based Classification of Clinical Reports.","authors":"Efsun Sarioglu, Kabir Yadav, Hyeong-Ah Choi","doi":"","DOIUrl":"","url":null,"abstract":"Electronic health records (EHRs) contain important clinical information about patients. Some of these data are in the form of free text and require preprocessing to be able to used in automated systems. Efficient and effective use of this data could be vital to the speed and quality of health care. As a case study, we analyzed classification of CT imaging reports into binary categories. In addition to regular text classification, we utilized topic modeling of the entire dataset in various ways. Topic modeling of the corpora provides interpretable themes that exist in these reports. Representing reports according to their topic distributions is more compact than bag-of-words representation and can be processed faster than raw text in subsequent automated processes. A binary topic model was also built as an unsupervised classification approach with the assumption that each topic corresponds to a class. And, finally an aggregate topic classifier was built where reports are classified based on a single discriminative topic that is determined from the training dataset. Our proposed topic based classifier system is shown to be competitive with existing text classification techniques and provides a more efficient and interpretable representation.","PeriodicalId":74541,"journal":{"name":"Proceedings of the conference. Association for Computational Linguistics. Meeting","volume":"2013 ","pages":"67-73"},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10544137/pdf/nihms-1932324.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41165188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0