@inbook{211854b0d6b842929d68a6f9c9de2d41,
title = "Topic-aware visual citation tracing via enhanced term weighting for efficient literature retrieval",
abstract = "{\textcopyright} Springer International Publishing AG 2017. Efficient retrieval of scientific literature related to a certain topic plays a key role in research work. While little has been done on topic-enabled citation filtering in traditional citation tracing, this paper presents visual citation tracing of scientific papers with document topics taken into consideration. Improved term selection and weighting are employed for mining the most relevant citations. A variation of the TF-IDF scheme, which uses external domain resources as references is proposed to calculate the term weighting in a particular domain. Moreover document weight is also incorporated in the calculation of term weight from a group of citations. A simple hierarchical word weighting method is also presented to handle keyword phrases. A visual interface is designed and implemented to interactively present the citation tracks in chord diagram and Sankey diagram.",
keywords = "Citation tracing, Data management, Ontology, TF-IDF, Term weighting, Text mining, Visualization",
author = "Youbing Zhao and Hui Wei and Shaopeng Wu and Farzad Parvinzamir and Zhikun Deng and Xia Zhao and Nikolaos Ersotelos and Feng Dong and Gordon Clapworthy and Enjie Liu",
year = "2017",
doi = "10.1007/978-3-319-62911-7_5",
language = "English",
isbn = "9783319629100",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "79--101",
booktitle = "Communications in Computer and Information Science",
address = "Germany",
}