PKU @ CLSciSumm-17: Citation Contextualization
نویسندگان
چکیده
This report gives a brief introduction of our participation in CL-SciSumm 2017 Task 1A. We demonstrate some data analysis and point out the difficulty of this task. Then we report both unsupervised and supervised methods with their performances on 2016 and 2017 testset, from which efficiency of different features can be estimated.
منابع مشابه
CIST@CLSciSumm-17: Multiple Features Based Citation Linkage, Classification and Summarization
This paper describes our methods and experiments applied for CLSciSumm-17. We try Convolutional Neural Network, word vectors and sentence similarities for citation linkage. For facet classification, we explore more useful features, rules, SVM and Fusion method. We use the linear combination of five classical features and DPPs based diversity sampling method to compute the structured summary. Te...
متن کاملUniversity of Mannheim @ CLSciSumm-17: Citation-Based Summarization of Scientific Articles Using Semantic Textual Similarity
The number of publications is rapidly growing and it is essential to enable fast access and analysis of relevant articles. In this paper, we describe a set of methods based on measuring semantic textual similarity, which we use to semantically analyze and summarize publications through other publications that cite them. We report the performance of our approach in the context of the third CL-Sc...
متن کاملLaSTUS/TALN @ CLSciSumm-17: Cross-document Sentence Matching and Scientific Text Summarization Systems
In recent years there has been an increasing interest in approaches to scientific summarization that take advantage of the citations a research paper has received in order to extract its main contributions. In this context, the CL-SciSumm 2017 Shared Task has been proposed to address citation-based information extraction and summarization. In this paper we present several systems to address thr...
متن کاملIdentifying Referenced Text in Scientific Publications by Summarisation and Classification Techniques
This report describes our contribution to the 2nd Computational Linguistics Scientific Document Summarization Shared Task (CLSciSumm 2016), which asked to identify the relevant text span in a reference paper that corresponds to a citation in another document that cites this paper. We developed three different approaches based on summarisation and classification techniques. First, we applied a m...
متن کاملNJUST @ CLSciSumm-17
This paper introduces NJUST system which is applied in the CLSciSumm 2017 Shared Task at the BIRNDL 2017 Workshop. The training corpus contains 10 articles of training set, 10 articles of development set and 10 articles of test set from CL-SciSumm 2016. Articles were created by randomly sampling documents from the ACL Anthology corpus and selecting their citing papers. In Task 1A, we utilize di...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2017