The concept of rankings is ubiquitous; it exists in nearly all domains. Essentially, rankings allow focusing on a small subset of an exhaustively full list - usually a few top or bottom entries are of interest. Such small subsets represent the essence of the available data, worthwhile to look into. Entity rankings share core characteristics; yet, for different entity types and fields it is hard to derive meaningful rankings in a fully automated way. This projects develops algorithms and tools to generated a large-scale repository of entity rankings, which is automatically populated and maintained. It captures entities, their properties and relations
from many different fields. We call it Pantheon.
It enables rich services to users and applications, for ad-hoc information demands, real-time event delivery, and deeper analytical insights.
The Pantheon project is funded by the DFG under project MI 1794/1-1 and MI 1794/1-2.
Here is a video demonstrating the use of rankings for exploring the contents of a knowledge base (here, we used Yago): Link to YouTube Video
You can try it out yourself, please visit: https://dbis-demo.cs.uni-kl.de/pantheon/
The ranking generation is realized using Apache Spark and is publicly available at https://git.cs.uni-kl.de/dbis-public/pantheon/pantheon-ranking-generator
We have published training data and relevance assessments of our recent work on mining interesting categorical values.
- MSc. Gajendra Doniparthi
- Prof. Dr.-Ing. Sebastian Michel
- Dr.-Ing. Evica Milchevski
- Dr.-Ing. Kiril Panev
- Dr.-Ing. Koninika Pal
- MSc. Nico Schäfer
- Evica Milchevski and Sebastian Michel. Distributed Similarity Joins over Top-K Rankings. EDBT, 2020.
- Kiril Panev, Sebastian Michel. Concept and Computation of Ranking-based Dominance. Inf. Syst. 84: 174-188 (2019)
- Koninika Pal and Sebastian Michel: Learning Interesting Attributes for Automated Data Categorization. 30th International Conference on Scientific and Statistical Database Management (SSDBM). Bolzano-Bozen, Italy, July 9-11, 2018.
- Kiril Panev and Sebastian Michel: Exploring Pros and Cons of Ranked Entities with COMPETE. 5th International Workshop on Exploratory Search in Databases and the Web (ExploreDB), Co-located with SIGMOD/PODS 2018, Houston, TX, USA, June 15th, 2018. pdf
- Koninika Pal and Sebastian Michel. LSH-Based Probabilistic Pruning of Inverted Indices for Sets and Ranked Lists.
20th International Workshop on the Web and Databases (WebDB 2017), Chicago, IL, USA, 2017, co-located with SIGMOD. pdf
- Kiril Panev, Nico Weisenauer, Sebastian Michel.
Reverse Engineering Top-k Join Queries. Datenbanksysteme für Business, Technologie und Web (BTW 2017), Stuttgart, Germany.
- Koninika Pal and Sebastian Michel. Efficient Similarity Search across Top-k Lists under the Kendall's Tau Distance. Conference on Scientific and Statistical Database Management (SSDBM), Budapest, Hungary, 2016. pdf
- Kiril Panev, Sebastian Michel. Reverse Engineering Top-k Database Queries with PALEO. 19th International Conference on Extending Database Technology (EDBT), Bordeaux, France, March 2016. [pdf]
- Koninika Pal, Sebastian Michel. A Data Mining Approach to Choosing Categorical Attributes for Ranked Lists. 19th International Conference on Extending Database Technology (EDBT), Bordeaux, France, March 2016. Poster track.
- Evica Milchevski, Sebastian Michel. Quantifying Likelihood of Change through Update Propagation across Top-k Rankings. 19th International Conference on Extending Database Technology (EDBT), Bordeaux, France, March 2016. Poster track.
- Kiril Panev, Evica Milchevski, Sebastian Michel. Computing Similar Entity Rankings via Reverse Engineering of Top-k Database Queries. 4th International Workshop on Keyword Search and Data Exploration on Structured Data (KEYS), co-located with ICDE, Helsinki, Finland, 2016. pdf (copyright IEEE)
- Fabian Reinartz, Koninika Pal, Sebastian Michel. Mining Entity Rankings. Datenbankspektrum, 2016. DOI:10.1007/s13222-015-0205-2
- Evica Milchevski, Avishek Anand, Sebastian Michel. The Sweet Spot between Inverted Indices and Metric-Space Indexing for Top-K-List Similarity Search. 18th International Conference on Extending Database Technology (EDBT), Brussels, Belgium, 2015. [slides]
- Koninika Pal, Sebastian Michel. An LSH Index for Computing Kendall's Tau over Top-k Lists. 17th International workshop on the Web and Databases(WebDB 2014) co-located with ACM SIGMOD 2014, Utah, USA, 2014.
- Evica Ilieva, Aleksandar Stupar, Sebastian Michel. The Essence of Knowledge (Bases) through Entity Rankings. 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013), San Francisco, USA, 2013. Poster track.
- Foteini Alvanaki, Evica Ilieva, Sebastian Michel, Aleksandar Stupar. Interesting Event Detection through Hall of Fame Rankings. Third ACM SIGMOD Workshop on Databases and Social Networks (DBSOCIAL 2013), in conjunction with SIGMOD 2013, New York, NY, USA.
- Foteini Alvanaki, Sebastian Michel. A Thin Monitoring Layer for Top-k Aggregation Queries over a Database. Third ACM SIGMOD Workshop on Databases and Social Networks (DBRank 2013), in conjunction with VLDB 2013, Riva del Garda, Trento, Italy. pdf