MOVING tools, services and demos

MOVING platform demo. The MOVING platform enables its users to improve their information literacy by training how to exploit data and text mining methods in their daily research tasks. The faceted search allows users to retrieve various kinds of documents such as scientific articles, books, video lectures, and metadata. The graph visualisation highlights the relations among the documents and related entities (authors, organisations, etc.) and enables users to explore the results in an alternative way to the classical list, as browsing a long list of documents and reading parts of their content to locate the needed information can be a mentally exhausting task. Soon the platform will be publicly available at https://moving.mz.test.tu-dresden.de/ (Currently the access is limited to the network of TU Dresden. We can provide access to interested parties outside of the TUD network via a VPN connection; for this, please contact Sebastian Gottfried – sebastian.gottfried@tu-dresden.de).


WevQuery – A scalable system for testing hypotheses about web interaction patterns. Remotely stored user interaction logs give access to a wealth of data generated by large numbers of users which can be used to understand if interactive systems meet the expectations of designers. Unfortunately, detailed insight into users’ interaction behaviour still requires a high degree of expertise. WevQuery allows designers to test their hypotheses about users’ behaviour by using a graphical notation to define the interaction patterns designers are seeking. WevQuery is scalable as the queries can then be executed against large user interaction datasets by employing the MapReduce paradigm. This way WevQuery provides designers effortless access to harvest users’ interaction patterns, removing the burden of low-level interaction data analysis. You can find more information regarding the system and download it under: https://github.com/aapaolaza/WevQuery


SciFiS – A Search Engine for Scientific Figures.SciFiS – A Search Engine for Scientific Figures Scientific figures like bar charts, pie charts, maps, scatter plots, or similar infographics often include valuable textual information, which is not present in the surrounding text. A new tool developed by the ZBW Knowledge Discovery Research Group enables the search in such infographics and thus offers new ways to access publications. A public prototype allows the search for infographics in open access publications taken from EconBiz. The prototype can be accessed at http://broca.informatik.uni-kiel.de:20080/ and more information about this research can be found at http://www.kd.informatik.uni-kiel.de/en/research/software/text-extraction.


Interactive online demo with audio and video analysis results in lecture and non-lecture videos. CERTH released an interactive online demo linking lecture videos, using general purpose concepts that were produced from textual analysis of their transcripts, with non-lecture videos, using their visual analysis results such as automatically detected shots, scenes, and visual concepts. You can access the demo at: http://multimedia2.iti.gr/moving-project/lecture-video-linking-demo/results.html (best viewed with Firefox).


Scientific Paper Recommendation using Sparse Title Data. The system delivers recommended scientific papers in economics based on what a social media user tweeted. It profiles papers as well as tweets using our novel method HCF-IDF (Hierarchical Concept Frequency Inverse Document Frequency). HCF-IDF extracts semantic concepts from texts and applies spreading activation based on a hierarchical thesaurus, which is freely available in many different domains. Spreading activation enables to extract relevant semantic concepts which are not mentioned in texts and mitigates shortness and sparseness of texts. The novel method HCF-IDF demonstrated the best performance in a larger user experiment published at JCDL’16. In this demo, you may compare the two different configurations, HCF-IDF using only titles of papers and HCF-IDF using both titles and full-texts of papers. Different from the traditional methods, HCF-IDF can provide competitive recommendations already using only titles.
http://amygdala.informatik.uni-kiel.de/Demo/TwitterAccount


Related tools and demos by the MOVING partners

Text Extraction from Scholarly Figures. Scholarly figures are data or visualizations like bar charts, pie charts, line graphs, maps, scatter plots or similar figures. Text extraction from scholarly figures is useful in many application scenarios, since text in scholarly figures often contains information that is not present in the surrounding text. We derived a generic pipeline for text extraction from the analysis of the wide research area on text extraction from figures and implemented in total over 20 methods for the six sequential steps of the pipeline.
http://www.kd.informatik.uni-kiel.de/en/research/software/text-extraction


VIDEO ANALYSIS 4ALLInteractive on-line video analysis service lets you upload videos via a web interface, and it performs shot/scene segmentation and visual concept detection (several times faster than real-time; uses our new concept detection engine). Results are displayed in an interactive user interface, which allows navigating through the video structure (shots, scenes), viewing the concept detection results for each shot, and searching by concepts within the video. Try this service now!