Efficient Processing of Ranked Queries with Sweeping Selection

Wen, Jie; Ester, Martin

doi:10.1007/11564126_54

Cited by 5 publications

(6 citation statements)

References 18 publications

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“…This paper's setting poses no in-place requirement, and our algorithms are not limited to two dimensions. The idea of layered skyline has also been used in the literature as part of an indexing method for topk queries [15]. In this paper, we focus on computing the skyline layers efficiently and on applying them in sizeconstrained skyline queries, which have not been studied in the literature.…”

Section: Definitions and Propertiesmentioning

confidence: 99%

“…If S i is empty, which indicates that p dominates all points previously in S i , fpg will be used as the new S i and S tmp will be inserted into S after the new S i (lines 12-13). Otherwise, the procedure AdjustSkyOrd will be called to adjust the subsets after S i in S (lines [15][16] in case S tmp is not empty, and p will be added into S i (line 17). If p does not belong to any S i in S, fpg will be appended to S (lines [19][20].…”

Section: Basic Algorithmmentioning

confidence: 99%

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Flexible and Efficient Resolution of Skyline Query Size Constraints

Jensen

Zhang

2011

IEEE Trans. Knowl. Data Eng.

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Given a set of multidimensional points, a skyline query returns the interesting points that are not dominated by other points. It has been observed that the actual cardinality (s) of a skyline query result may differ substantially from the desired result cardinality (k), which has prompted studies on how to reduce s for the case where k < s. This paper goes further by addressing the general case where the relationship between k and s is not known beforehand. Due to their complexity, the existing pointwise ranking and set-wide maximization techniques are not well suited for this problem. Moreover, the former often incurs too many ties in its ranking, and the latter is inapplicable for k > s. Based on these observations, the paper proposes a new approach, called skyline ordering, that forms a skyline-based partitioning of a given data set such that an order exists among the partitions. Then, set-wide maximization techniques may be applied within each partition. Efficient algorithms are developed for skyline ordering and for resolving size constraints using the skyline order. The results of extensive experiments show that skyline ordering yields a flexible framework for the efficient and scalable resolution of arbitrary size constraints on skyline queries.Index Terms-Skyline queries, query processing, database management.

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Section: Definitions and Propertiesmentioning

confidence: 99%

Section: Basic Algorithmmentioning

confidence: 99%

Flexible and Efficient Resolution of Skyline Query Size Constraints

Jensen

Zhang

2011

IEEE Trans. Knowl. Data Eng.

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“…Li et al proposed RankSQL [22] that integrates ranking in database systems on both the logical algebra level and the physical implementation level. Furthermore, Jin et al proposed KNN-based and Gridbased sweeping approach for top-k query [23]. In [17], Xin et al proposed a new computational model, called Rank Cube.…”

Section: Experiments 2 (Comparison With Existing Top-k Algorithms)mentioning

confidence: 99%

Dominant Graph: An Efficient Indexing Structure to Answer Top-K Queries

Zou

Chen

2008

2008 IEEE 24th International Conference on Data Engineering

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Given a record set D and a query score function F, a top-k query returns k records from D, whose values of function F on their attributes are the highest. In this paper, we investigate the intrinsic connection between top-k queries and dominant relationship between records, and based on which, we propose an efficient layer-based indexing structure, Dominant Graph (DG), to improve the query efficiency. Specifically, DG is built offline to express the dominant relationship between records and top-k query is implemented as a graph traversal problem, i.e. Traveler algorithm. We prove theoretically that the size of search space (that is the number of retrieved records from the record set to answer top-k query) in our basic algorithm is directly related to the cardinality of skyline points in the record set (see Theorem 3.2). Based on the cost analysis, we propose the optimization technique, pseudo record, to improve the search efficiency. In order to handle the top-k query in the high dimension record set, we also propose N-Way Traveler algorithm. Finally, extensive experiments demonstrate that our proposed methods have significant improvement over its counterparts, including both classical and state art of top-k algorithms. For example, the search space in our algorithm is less than 5 of that 5 in AppRI [1], one of state art of top-k algorithms. Furthermore, our method can support any aggregate monotone query function.

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“…As a fundamental operator in database management, rankaware query has been studied extensively in recent years. In general, the ranking query returns top k tuples with minimal ranking scores (or maximal ranking scores under different contexts) by employing a user-defined scoring function [7,9,12,21,26,26]. There exist many kinds of scoring Figure 1: An example of ranking queries functions for rank-aware queries, among which the linear model is one of the most widely adopted models [9,21,26].…”

Section: Introductionmentioning

confidence: 99%

Reverse k-ranks query

2014

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Finding matching customers for a given product based on individual user's preference is critical for many applications, especially in e-commerce. Recently, the reverse top-k query is proposed to return a number of customers who regard a given product as one of the k most favorite products based on a linear model. Although a few "hot" products can be returned to some customers via reverse top-k query, a large proportion of products (over 90%, as our example illustrates, see Figure 2) cannot find any matching customers. Inspired by this observation, we propose a new kind of query (R-kRanks) which finds for a given product, the topk customers whose rank for the product is highest among all customers, to ensure 100% coverage for any given product, no matter it is hot or niche. Not limited to e-commerce, the concept of customer-product can be extended to a wider range of applications, such as dating and job-hunting. Unfortunately, existing approaches for reverse top-k query cannot be used to handle R-kRanks conveniently due to infeasibility of getting enough elements for the query result. Hence, we propose three novel approaches to efficiently process R-kRanks query, including one tree-based method and two batch-pruning-based methods. Analysis of theoretical and experimental results on real and synthetic data sets illustrates the efficacy of the proposed methods.

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Efficient Processing of Ranked Queries with Sweeping Selection

Cited by 5 publications

References 18 publications

Flexible and Efficient Resolution of Skyline Query Size Constraints

Flexible and Efficient Resolution of Skyline Query Size Constraints

Dominant Graph: An Efficient Indexing Structure to Answer Top-K Queries

Reverse k-ranks query

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