The general problem of answering top-k queries can be modeled using lists of data items sorted by their local scores. The most efficient algorithm proposed so far for answering top-k queries over sorted lists is the Threshold Algorithm (TA). However, TA may still incur a lot of useless accesses to the lists. In this paper, we propose two new algorithms which stop much sooner. First, we propose ...

Driven by many real applications, graph pattern matching has attracted a great deal of attention recently. Consider that a twigpattern matching may result in an extremely large number of matches in a graph; this may not only confuse users by providing too many results but also lead to high computational costs. In this paper, we study the problem of top-k tree pattern matching; that is, given a ...

The general problem of answering top-k queries can be modeled using lists of objects sorted by their local scores. Fagin et al. proposed the “middleware cost” for a top-k query algorithm, and proposed the efficient sequential Threshold Algorithm (TA). However, since the size of the dataset can be incredible huge, the middleware cost of sequential TA may be intolerable. So, in this paper, we pro...

We introduce a diversified top-k partial MaxSAT problem, a combination of partial MaxSAT problem and enumeration problem. Given a partial MaxSAT formula F and a positive integer k, the diversified top-k partial MaxSAT is to find k maximal solutions for F such that the k maximal solutions satisfy the maximum number of soft clauses of F . This problem can be widely used in many applications inclu...

Consider a binary classification problem in which the learner is given a labeled training set, an unlabeled test set, and is restricted to choosing exactly k test points to output as positive predictions. Problems of this kind—transductive precision@k— arise in many applications. Previous methods solve these problems in two separate steps, learning the model and selecting k test instances by th...

We present an index for top-k most frequent document retrieval whose space is |CSA|+o(n)+D log n D+O(D) bits, and its query time is O(log k log 2+ n) per reported document, where D is the number of documents, n is the sum of lengths of the documents, and |CSA| is the space of the compressed suffix array for the documents. This improves over previous results for this problem, whose space complex...

In recent years, crowdsourcing has emerged as a new computing paradigm for bridging the gap between humanand machine-based computation. As one of the core operations in data retrieval, we study topk queries with crowdsourcing, namely crowd-enabled topk queries . This problem is formulated with three key factors, latency, monetary cost , and quality of answers . We first aim to design a novel fr...

Top-k dominating queries combine the natural idea of selecting the k best items with a comprehensive “goodness” criterion based on dominance. A point p1 dominates p2 if p1 is as good as p2 in all attributes and is strictly better in at least one. Existing works address the problem in settings where data objects are multidimensional points. However, there are domains where we only have access to...

Measuring the semantic meaning between words is an important issue because it is the basis for many applications, such as word sense disambiguation, document summarization, and so forth. Although it has been explored for several decades, most of the studies focus on improving the effectiveness of the problem, i.e., precision and recall. In this paper, we propose to address the efficiency issue,...

Graph pattern matching has been widely used in e.g., social data analysis. A number of matching algorithms have been developed that, given a graph pattern Q and a graph G, compute the set M(Q,G) of matches of Q in G. However, these algorithms often return an excessive number of matches, and are expensive on large real-life social graphs. Moreover, in practice many social queries are to find mat...