K-Join: Knowledge-Aware Similarity Join

Fast top-k similarity join for SimRank

SimRank is a well-studied similarity measure between two nodes in a network. However, evaluating SimRank of all nodes in a network is not only time-consuming but also not pragmatic, since users are only interested in the most similar pairs in many real-world applications. This paper focuses on topk similarity join based on SimRank. In this work, we first present an incremental algorithm for com...

Streaming Similarity Self-Join

We introduce and study the problem of computing the similarity self-join in a streaming context (sssj), where the input is an unbounded stream of items arriving continuously. The goal is to find all pairs of items in the stream whose similarity is greater than a given threshold. The simplest formulation of the problem requires unbounded memory, and thus, it is intractable. To make the problem f...

Top-k Similarity Join over Multi-valued Objects

The top-k similarity joins have been extensively studied and used in a wide spectrum of applications such as information retrieval, decision making, spatial data analysis and data mining. Given two sets of objects U and V, a top-k similarity join returns k pairs of most similar objects from U×V. In the conventional model of top-k similarity join processing, an object is usually regarded as a po...

k-Arbiter Join Operation

k-Arbiter is a useful concept for solving the distributed h-out of-k resources allocation problem. The distributed h-out of-k resources allocation algorithms based on k-arbiter have the benefits of high fault-tolerance and low communication cost. However, according to the definition of k-arbiter, it is required to have a non-empty intersection among any (k+1) quorums in a k-arbiter. Consequentl...

Similarity Join Algorithms: An Introduction