Issue Downloads
On the Hardness and Approximation of Euclidean DBSCAN
DBSCAN is a method proposed in 1996 for clustering multi-dimensional points, and has received extensive applications. Its computational hardness is still unsolved to this date. The original KDD‚96 paper claimed an algorithm of O(n log n) ”average ...
BonXai: Combining the Simplicity of DTD with the Expressiveness of XML Schema
While the migration from DTD to XML Schema was driven by a need for increased expressivity and flexibility, the latter was also significantly more complex to use and understand. Whereas DTDs are characterized by their simplicity, XML Schema Documents ...
Efficient SimRank-Based Similarity Join
Graphs have been widely used to model complex data in many real-world applications. Answering vertex join queries over large graphs is meaningful and interesting, which can benefit friend recommendation in social networks and link prediction, and so on. ...
Query Nesting, Assignment, and Aggregation in SPARQL 1.1
Answering aggregate queries is a key requirement of emerging applications of Semantic Technologies, such as data warehousing, business intelligence, and sensor networks. To fulfil the requirements of such applications, the standardization of SPARQL 1.1 ...
Detecting Inclusion Dependencies on Very Many Tables
Detecting inclusion dependencies, the prerequisite of foreign keys, in relational data is a challenging task. Detecting them among the hundreds of thousands or even millions of tables on the web is daunting. Still, such inclusion dependencies can help ...
DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN
At SIGMOD 2015, an article was presented with the title “DBSCAN Revisited: Mis-Claim, Un-Fixability, and Approximation” that won the conference’s best paper award. In this technical correspondence, we want to point out some inaccuracies in the way ...
