A Graphical Citation Browser for the ACL Anthology
Navigation in large scholarly paper collections is tedious and not well supported in most scientific digital libraries. We describe a novel browser-based graphical tool implemented using HTML5 Canvas. It displays citation information extracted from the paper text to support useful navigation. The tool is implemented using a client/server architecture. A citation graph of the digital library is built in the memory of the server. On the client side, egdes of the displayed citation (sub)graph surrounding a document are labeled with keywords signifying the kind of citation made from one document to another. These keywords were extracted using NLP tools such as tokenizer, sentence boundary detection and part-of-speech tagging applied to the text extracted from the original PDF papers (currently 22,500). By clicking on an egde, the user can inspect the corresponding citation sentence in context, in most cases even also highlighted in the original PDF layout. The system is publicly accessible as part of the ACL Anthology Searchbench.
Code (0)
등록된 구현이 없습니다.
Tasks
Boundary DetectionPart-Of-Speech TaggingSentenceSimilar Papers 제목 키워드 기반
Geographic Citation Gaps in NLP Research
In a fair world, people have equitable opportunities to education, to conduct scientific research, to publish, and to get credit for their work, regardless of where they live. However, it is common knowledge among resear…
Examining Citations of Natural Language Processing Literature
We extracted information from the ACL Anthology (AA) and Google Scholar (GS) to examine trends in citations of NLP papers. We explore questions such as: how well cited are papers of different types (journal articles, con…
ArticlesSentiment AnalysisSentiment ClassificationStructural Scaffolds for Citation Intent Classification in Scientific Publications
Identifying the intent of a citation in scientific papers (e.g., background information, use of methods, comparing results) is critical for machine reading of individual publications and automated analysis of the scienti…
ARCCitation Intent ClassificationClassificationGeneral Classification+4SChuBERT: Scholarly Document Chunks with BERT-encoding boost Citation Count Prediction
Predicting the number of citations of scholarly documents is an upcoming task in scholarly document processing. Besides the intrinsic merit of this information, it also has a wider use as an imperfect proxy for quality w…
Citation PredictionPredictionSChuBERT: Scholarly Document Chunks with BERT-encoding boost Citation Count Prediction.
Predicting the number of citations of scholarly documents is an upcoming task in scholarly document processing. Besides the intrinsic merit of this information, it also has a wider use as an imperfect proxy for quality w…
Citation PredictionPrediction