@misc{haslhofer2013semantic,
  abstract = {Tags assigned by users to shared content can be ambiguous. As a possible solution, we propose semantic tagging as a collaborative process in which a user selects and associates Web resources drawn from a knowledge context. We applied this general technique in the specific context of online historical maps and allowed users to annotate and tag them. To study the effects of semantic tagging on tag production, the types and categories of obtained tags, and user task load, we conducted an in-lab within-subject experiment with 24 participants who annotated and tagged two distinct maps. We found that the semantic tagging implementation does not affect these parameters, while providing tagging relationships to well-defined concept definitions. Compared to label-based tagging, our technique also gathers positive and negative tagging relationships. We believe that our findings carry implications for designers who want to adopt semantic tagging in other contexts and systems on the Web.},
  author = {Haslhofer, Bernhard and Robitza, Werner and Lagoze, Carl and Guimbretiere, Francois},
  interhash = {84516aa456894b6d6adf86abd2386656},
  intrahash = {a653f1a0a1ac5084e80757ec277b1184},
  note = {cite arxiv:1304.1636Comment: 10 pages},
  title = {Semantic Tagging on Historical Maps},
  url = {http://arxiv.org/abs/1304.1636},
  year = 2013
}

@inproceedings{aya2005citation,
  abstract = {Citation analysis has been used to study various aspects of scholarly communication. In general, these studies have not differentiated among the multiple reasons for citations. However, authors cite other works for a number of reasons including demonstrating knowledge of the field, establishing the placement of the citing work in the field, comparing and criticizing other works, and paying homage to seminal work by pioneers in the field. In this paper, we present a number of applications in which distinguishing among authors' motivations for citations might be useful and present a machine learning approach to automatically classifying citations according to these motivations. Our approach to citation classification makes use of the structure and the argumentative nature of the scientific papers. We present the results of experiments we ran on papers in the computer science field. The results are encouraging and give us hope that we can use our citation classifier in analyzing large corpora of scientific papers.},
  author = {Aya, Selcuk and Lagoze, Carl and Joachims, Thorsten},
  booktitle = {Proceedings of the International Conference on Knowledge Management},
  chapter = 24,
  doi = {10.1142/9789812701527_0024},
  eprint = {http://www.worldscientific.com/doi/pdf/10.1142/9789812701527_0024},
  interhash = {f35b1f099571f3f134186ff407ee5fee},
  intrahash = {d30bac9f744e0473499f1d15d55258b8},
  month = oct,
  pages = {287--298},
  publisher = {World Scientific Publishing},
  title = {Citation Classification and its Applications},
  url = {http://www.worldscientific.com/doi/abs/10.1142/9789812701527_0024},
  year = 2005
}

@inproceedings{aya2005citation,
  abstract = {Citation analysis has been used to study various aspects of scholarly communication. In general, these studies have not differentiated among the multiple reasons for citations. However, authors cite other works for a number of reasons including demonstrating knowledge of the field, establishing the placement of the citing work in the field, comparing and criticizing other works, and paying homage to seminal work by pioneers in the field. In this paper, we present a number of applications in which distinguishing among authors' motivations for citations might be useful and present a machine learning approach to automatically classifying citations according to these motivations. Our approach to citation classification makes use of the structure and the argumentative nature of the scientific papers. We present the results of experiments we ran on papers in the computer science field. The results are encouraging and give us hope that we can use our citation classifier in analyzing large corpora of scientific papers.},
  author = {Aya, Selcuk and Lagoze, Carl and Joachims, Thorsten},
  booktitle = {Proceedings of the International Conference on Knowledge Management},
  chapter = 24,
  doi = {10.1142/9789812701527_0024},
  eprint = {http://www.worldscientific.com/doi/pdf/10.1142/9789812701527_0024},
  interhash = {f35b1f099571f3f134186ff407ee5fee},
  intrahash = {d30bac9f744e0473499f1d15d55258b8},
  month = oct,
  pages = {287--298},
  publisher = {World Scientific Publishing},
  title = {Citation Classification and its Applications},
  url = {http://www.worldscientific.com/doi/abs/10.1142/9789812701527_0024},
  year = 2005
}