Sonja Maier
Sebastian Rönnau
ABSTRACT
Most editors do not allow for accessing different documents programatically. High-level version operations like change aggregation are also seldomly supported.
In this paper, we introduce a model-based approach for keeping track of changes in documents, which makes use of the specific structure of a document format. The approach enables new functionality, such as a REST-based web service to access documents and document diffs, the semantic lifting of changes and the visualization thereof.
The approach was initially introduced to better keep track of changes in Google Docs, but can also be applied to other document types and in other contexts.
- Google Drive. http://drive.google.com.Google Scholar
- Google Drive API. http://developers.google.com/drive.Google Scholar
- Barabucci, G., Borghoff, U. M., Iorio, A. D., and Maier, S. Document changes: modeling, detection, storage and visualization (DChanges 2013). In Proc. ACM Symposium on Document Engineering 2013 (DocEng 2013) (2013), ACM, pp. 281--282.Google ScholarDigital Library
- Barabucci, G., Borghoff, U. M., Iorio, A. D., Maier, S., and Munson, E. V. Document changes: modeling, detection, storage and visualization (DChanges 2014). In Proc. ACM Symposium on Document Engineering 2014 (DocEng 2014) (2014), ACM, pp. 207--208.Google ScholarDigital Library
- Beck, F., Burch, M., Diehl, S., and Weiskopf, D. The state of the art in visualizing dynamic graphs. In EuroVis - STAR 2014 (2014), Eurographics - European Association for Computer Graphics.Google Scholar
- Kehrer, T., Kelter, U., and Taentzer, G. A rule-based approach to the semantic lifting of model differences in the context of model versioning. In Proc. 2011 26th IEEE/ACM Intl. Conference on Automated Software Engineering (ASE 2011) (2011), IEEE Computer Society, pp. 163--172.Google ScholarDigital Library
- Koegel, M., Herrmannsdoerfer, M., Li, Y., Helming, J., and David, J. Comparing state- and operation-based change tracking on models. In Proc. 14th IEEE Intl. Enterprise Distributed Object Computing Conference (2010), IEEE Computer Society, pp. 163--172.Google ScholarDigital Library
- Maier, S., and Minas, M. Recording, processing, and visualizing changes in diagrams. In IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2015, Atlanta, USA, 18-22 October 2015, Proceedings (2015).Google ScholarCross Ref
- Myers, E. W. An O(ND) difference algorithm and its variations. Algorithmica 1, 2 (1986), 251--266.Google ScholarCross Ref
- Stephan, M., and Cordy, J. R. A survey of methods and applications of model comparison.Google Scholar
- Wang, D., Olson, J. S., Zhang, J., Nguyen, T., and Olson, G. M. DocuViz: visualizing collaborative writing. In Proc. 33rd Annual ACM Conference on Human Factors in Computing Systems, CHI 2015, Seoul, Republic of Korea, April 18-23, 2015 (2015), ACM, pp. 1865--1874.Google ScholarDigital Library
Index Terms
- A REST-based Document Model for Collaborative Editing of Documents
Recommendations
Sub-document Timestamping of Web Documents
SIGIR '15: Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information RetrievalKnowledge about a (Web) document's creation time has been shown to be an important factor in various temporal information retrieval settings. Commonly, it is assumed that such documents were created at a single point in time. While this assumption may ...
User-Defined Template for Identifying Document Type and Extracting Information from Documents
ICDAR '99: Proceedings of the Fifth International Conference on Document Analysis and RecognitionAn automatic document entry system is described that identifies the type of document and extracts textual information, such as titles or authors, from semi-formatted document images. The system registers documents, offers easy retrieval of documents ...
Automatic knowledge extraction from OCR documents using hierarchical document analysis
RACS '18: Proceedings of the 2018 Conference on Research in Adaptive and Convergent SystemsIndustries can improve their business efficiency by analyzing and extracting relevant knowledge from large numbers of documents. Knowledge extraction manually from large volume of documents is labor intensive, unscalable and challenging. Consequently ...
Comments