Efficient skyline evaluation over partially ordered domains

Zhang, Shiming; Mamoulis, Nikos; Cheung, David W.; Kao, Ben

doi:10.14778/1920841.1920996

Cited by 18 publications

(10 citation statements)

References 24 publications

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“…The winnow operator is also implicit in skyline queries, which supports only LOWEST and HIGHEST preferences based on the Preference Algebra described in Kießling (2002). Methods for calculating skylines over partially ordered data have also started to emerge as in Zhang et al (2010).…”

Section: Pareto Composition and Bmo-setmentioning

confidence: 99%

Interactive Exploration of Multi-Dimensional Information Spaces with Preference Support

Papadakos

2014

SIGIR Forum

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Users access large amounts of information resources mainly through search functions, where they type a few keywords and the web search or query engine returns a linear list of hits. While this is often satisfactory for focalized search, it does not provide enough support for exploratory information needs. Faceted and Dynamic Taxonomies (FDT) is a highly prevalent model for exploratory search, which allows users to get an overview of the information space and offer them various groupings of the results based on their attributes, metadata, or other dynamically mined information, enabling them to gradually restrict their focus through clicks and locate low ranked resources. The enrichment of such mechanisms with preferences could be proven useful for exploratory tasks. However, the current preference-based approaches seem to ignore the fact that users should be acquainted with the information space and the available choices for describing effectively their preferences. In this dissertation we extend the interaction model of FDT with preference actions that allow users to express their preferences interactively, gradually, and in a simple way. We introduce a preference framework appropriate for information spaces comprising resources described by attributes whose values can be hierarchically valued and/or multi-valued. We define the language, its semantics and the required algorithms. The framework supports preference inheritance in the hierarchies, automatic conflict resolution, as well as preference composition. Subsequently, we enrich the FDT model with preference actions and we propose logical optimizations and methods for exploiting the intrinsic characteristics of the FDT-based interaction, aiming at making it applicable to large amounts of information. We present the design and the implementation of the web-based system Hippalus, which realizes the extended interaction model. Regarding user benefits, we theoretically analyze user gain in terms of the number and difficulty of choices, and we describe and analyze three user-based evaluations. The first investigates the degree of effectiveness of preferences when users are not aware of the available choices. We found that only 20% of the users managed to express effective preferences without knowing the available choices. The second comparatively evaluates FDT with other exploratory models, and shows that the majority of users preferred FDT, was more satisfied by FDT and achieved higher rates of task completion with FDT. The last one evaluates the preference-enriched FDT as realized by Hippalus. The results were impressive. Even in a very small dataset, with the preference-enriched FDT all users successfully completed all tasks in 1/3 of the time and with 1/3 of the actions in comparison to the plain FDT. Moreover all of the users preferred the preference-enriched interfac. Available: http://www.ics.forth.gr/_publications/Papadakos_Dissertation.pdf.

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Section: Pareto Composition and Bmo-setmentioning

confidence: 99%

Interactive Exploration of Multi-Dimensional Information Spaces with Preference Support

Papadakos

2014

SIGIR Forum

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“…Both techniques use an Lp norm (Euclidean distance in particular) as the measure of diversity between skyline points. This choice may be problematic in the following cases: i) the dimensions correspond to attributes that are difficult to combine (e.g., price and quality), ii) the skyline is computed over a partially-ordered domain [37], and iii) the points' attributes are non-numerical values, e.g., when operating over a document collection where the attributes may be terms, q-grams or topics. Under such circumstances, a multidimensional index can not be used, rendering the techniques infeasible or even inapplicable.…”

Section: Related Workmentioning

confidence: 99%

SkyDiver

Valkanas

Papadopoulos

Gunopulos

2013

Proceedings of the 16th International Conference on Extending Database Technology

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Skyline queries have attracted considerable attention by the database community during the last decade, due to their applicability in a series of domains. However, most existing works tackle the problem from an efficiency standpoint, i.e., returning the skyline as quickly as possible. The user is then presented with the entire skyline set, which may be in several cases overwhelming, therefore requiring manual inspection to come up with the most informative data points. To overcome this shortcoming, we propose a novel approach in selecting the k most diverse skyline points, i.e., the ones that best capture the different aspects of both the skyline and the dataset they belong to. We present a novel formulation of diversification which, in contrast to previous proposals, is intuitive, because it is based solely on the domination relationships among points. Consequently, additional artificial distance measures (e.g., Lp norms) among skyline points are not required. We present efficient approaches in solving this problem and demonstrate the efficiency and effectiveness of our approach through an extensive experimental evaluation with both real-life and synthetic data sets.

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“…The methods proposed in [2,7,5,8] are the most relevant to our work. Chan et al [2] presented three algorithms for evaluating skyline queries with partially ordered attributes.…”

Section: Related Workmentioning

confidence: 99%

“…In addition, TSS is able to handle dynamic skyline queries. Because existing methods for skyline with partially ordered domains either use stronger notions of dominance, which generate false positives, or require expensive dominance checks, Zhang et al [8] introduced two methods, which do not have these drawbacks. The first mechanism employs an appropriate mapping of a partial order to a total order, inspired by the lattice theorem and an off-theshelf skyline algorithm.…”

Section: Related Workmentioning

confidence: 99%

Caching support for skyline query processing with partially-ordered domains

Hsueh

Zimmermann

2012

Proceedings of the 20th International Conference on Advances in Geographic Information Systems

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The results of skyline queries performed on data sets with partially-ordered domains vary depending on users' preference profiles specified for the partially-ordered domains. Existing work has addressed the issue of handling each individual query with some efficiency. However, processing large volumes of such queries for online applications with low response time is still very challenging. In this paper, we introduce a novel approach, termed CSS, to reduce the latency by caching query results with their unique user preferences. Of paramount importance in this case is that cached queries with compatible preference profiles need to be utilized. For this purpose, we introduce a similarity measure that establishes the level of a relation of a new query to each of the previously cached queries and profiles. The similarity measure allows the cached entries to be effectively ordered according to descending values; hence, query processing can start with the most promising candidates. If a new query is only partially answerable from the cache, the proposed method pursues a second optimization step. The query processor utilizes the partial result sets and augments them by performing less expensive constraint skyline queries guided by constraint violations between different query preference profiles. Extensive experiments are presented to demonstrate the performance and utility of our novel approach.

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Efficient skyline evaluation over partially ordered domains

Cited by 18 publications

References 24 publications

Interactive Exploration of Multi-Dimensional Information Spaces with Preference Support

Interactive Exploration of Multi-Dimensional Information Spaces with Preference Support

SkyDiver

Caching support for skyline query processing with partially-ordered domains

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