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Temporal Conditional preference queries on Streams 1

28th International Conference on Database and Expert Systems Applications (DEXA)

作者： Ribeiro, Marcos Roberto Barioni, Maria Camila N. de Amo, Sandra Roncancio, Claudia Labbe, Cyril Inst Fed Minas Gerais Bambui Brazil Univ Fed Uberlandia Uberlandia MG Brazil Univ Grenoble Alpes CNRS Grenoble INP LIG F-38000 Grenoble France

ISBN: (数字)9783319644684

ISBN: (纸本)9783319644684;9783319644677

preference queries on data streams have been proved very useful for many application areas. Despite of the existence of research studies dedicated to this issue, they lack to support the use of an important implicit information of data streams, the temporal preferences. In this paper we define new operators and an algorithm for the efficient evaluation of temporal conditional preference queries on data streams. We also demonstrate how the proposed operators can be translated to the Continuous Query Language (CQL). The experiments performed show that our proposed operators have considerably superior performance when compared to the equivalent operations in CQL.

关键词： Data streams preference queries Temporal preferences

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preference queries with Ceteris Paribus Semantics for Linked Data

Preference Queries with Ceteris Paribus Semantics for Linked...

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OnTheMove (OTM) Federated Conference

作者： Rosati, Jessica Di Noia, Tommaso Lukasiewicz, Thomas De Leone, Renato Maurino, Andrea Polytech Univ Bari Via Orabona 4 I-70125 Bari Italy Univ Camerino Sch Sci & Technol I-62032 Camerino MC Italy Univ Milano Bicocca I-20126 Milan Italy Univ Oxford Oxford OX1 3QD England

ISBN: (纸本)9783319261485;9783319261478

User preferences play a central role in supporting complex and multifactorial decision processes. Every personalized information filtering system should exploit a preferences model of the user in order to match her interests as much as possible. In a Linked Open Data (LOD) setting, the problem is twofold. On the one hand, there is the need of a standard way to represent complex preferences. On the other hand, we need tools able to query LOD datasets by taking into account user's preferences. In this paper, we propose a vocabulary to represent statements formulated in terms of ceteris paribus semantics. We then show (i) how to represent a CP-net by means of this vocabulary and (ii) how to embed such compact preference model in a SPARQL 1.1 query in order to access semantic data in a personalized way.

关键词： User preferences Ceteris paribus CP-nets Linked data preference queries SPARQL

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Quantifying the competitiveness of a dataset in relation to general preferences

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VLDB JOURNAL 2024年第1期33卷 231-250页

作者： Mouratidis, Kyriakos Li, Keming Tang, Bo Singapore Management Univ Sch Comp & Informat Syst Singapore Singapore Southern Univ Sci & Technol Dept Comp Sci & Engn Shenzhen Peoples R China Southern Univ Sci & Technol Res Inst Trustworthy Autonomous Syst Dept Comp Sci & Engn Shenzhen Peoples R China

Typically, a specific market (e.g., of hotels, restaurants, laptops, etc.) is represented as a multi-attribute dataset of the available products. The topic of identifying and shortlisting the products of most interest to a user has been well-explored. In contrast, in this work we focus on the dataset, and aim to assess its competitiveness with regard to different possible preferences. We define measures of competitiveness, and represent them in the form of a heat-map in the domain of preferences. Our work finds application in market analysis and in business development. These applications are further enhanced when the competitiveness heat-map is used in tandem with information on user preferences (which can be readily derived by existing methods). Interestingly, our study also finds side-applications with strong practical relevance in the area of multi-objective querying. We propose a suite of algorithms to efficiently produce the heat-map, and conduct case studies and an empirical evaluation to demonstrate the practicality of our work.

关键词： Heat-map preference queries Multi-dimensional data Market analysis

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Table Union Search with preferences 49

Table Union Search with Preferences

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Joint Workshops at the 49th International Conference on Very Large Data Bases, VLDBW 2023

作者： Mirzaei, Hamed Rafiei, Davood University of Alberta 2-32 Athabasca Hall EdmontonAB Canada

We study the problem of Table Union Search (TUS) in the presence of preferences. The notion of unionability, as studied in the literature, is too coarse to be effective in down-stream tasks. We introduce preferences for table unionability, as a way to reduce the search space and focus on rows and columns that are important for the follow-up operations. We show how these preferences can be efficiently implemented and how they can improve the performance of some down-stream tasks. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Column Unionability Information Retrieval preference queries Table Augmentation Table Union Search Table Unionability

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A Survey on Selectivity Estimation for preference Database queries 11

A Survey on Selectivity Estimation for Preference Database Q...

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11th International Baltic Conference on Databases and Information Systems (Baltic DBandIS)

作者： Endres, Markus Univ Augsburg Inst Comp Sci D-86135 Augsburg Germany

ISBN: (纸本)9781614994589

Skyline query processing and the more general preference queries become reality in current database systems. preference queries select those tuples from a database that are optimal with respect to a set of designated preference attributes. In a Skyline query these preferences only refer to minimum and maximum, whereas the more general approach of preference queries allow a more granular specification of user wishes as well as the specification of the relative importance of individual preferences. The incorporation of preferences into practical relational database engines necessitates an efficient and effective selectivity estimation module: A better understanding of the preference selectivity is useful for better design of algorithms and necessary to extend a database query optimizer's cost model to accommodate preference queries. This paper presents a survey on selectivity and cardinality estimation for arbitrary preference queries. The paper presents current approaches and discusses their advantages and disadvantages, such that one could decide which model should be used in a database engine to estimate optimization costs.

关键词： preference queries skyline selectivity cardinality optimization

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Combining RDF and SPARQL with CP-theories to reason about preferences in a Linked Data setting

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SEMANTIC WEB 2020年第3期11卷 391-419页

作者： Anelli, Vito Walter De Leone, Renato Di Noia, Tommaso Lukasiewicz, Thomas Rosati, Jessica Polytech Univ Bari DEI Bari Italy Univ Camerino Sch Sci & Technol Camerino Italy Univ Oxford Dept Comp Sci Oxford England

preference representation and reasoning play a central role in supporting users with complex and multi-factorial decision processes. In fact, user tastes can be used to filter information and data in a personalized way, thus maximizing their expected utility. Over the years, many frameworks and languages have been proposed to deal with user preferences. Among them, one of the most prominent formalism to represent and reason with (qualitative) conditional preferences (CPs) are conditional preference theories (CP-theories). In this paper, we show how to combine them with Semantic Web technologies in order to encode in a standard SPARQL 1.1 query the semantics of a set of CP statements representing user preferences by means of RDF triples that refer to a "preference" OWL ontology. In particular, here we focus on context-uniform conditional (cuc) acyclic CP-theories [Artif. Intell. 175 2011, 1053-1091]. The framework that we propose allows a standard SPARQL client to query Linked Data datasets, and to order the results of such queries relative to a set of user preferences.

关键词： preferences ceteris paribus CP-theories CP-nets Linked Data preference queries SPARQL DBpedia

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preference-driven Control over Incompleteness of Knowledge Graph Query Answers 20

Preference-driven Control over Incompleteness of Knowledge G...

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12th ACM Conference on Web Science (WebSci)

作者： Affeldt, Till Mennicke, Stephan Balke, Wolf-Tilo TU Braunschweig Inst Informat Syst Braunschweig Germany

ISBN: (纸本)9781450379892

Entities in today's knowledge graphs do not only differ in their property values but also in the schematic structures they are represented by. Given their extraction-based foundation, it is quite common that in practical knowledge base instances totally unrelated graph structures describe entities of the same type. Hence, operators for handling such heterogeneity are mandatory when designing a robust query language for knowledge graphs. While SPARQL does offer optional patterns for this purpose, their query answers often suffer from an unintuitive matching behavior. In contrast, preference semantics seem to be a much more intuitive and still robust way of expressing how the optimal query result may look like. While preferences over data value domains are already applied for graph data, we argue for structural preferences to achieve fine-grained control of heterogeneity in the query answers. Therefore, we propose a new operator for SPARQL, enabling the expression of structural as well as some value preferences. Equipped with a Pareto-style semantics, we give examples of how to model preferences with the new operator. Our prototypical implementation allows for evaluating several encodings of the new construct at DBpedia's SPARQL endpoint.

关键词： knowledge graphs incompleteness preference queries SPARQL

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Optimization of Skyline queries in dynamic contexts

Optimization of Skyline queries in dynamic contexts

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作者： Alami, Karim

学位级别：博士

Les requêtes de préférence sont des outils intéressants pour calculer des sous-ensembles représentatifs d'ensembles de données en entrée ou pour classer les tuples en fonction des préférences des utilisateurs. Dans cette thèse, nous abordons principalement l'optimisation des requêtes Skyline, une classe spéciale des requêtes de préférence, dans des contextes dynamiques. Dans une première partie, nous abordons la maintenance incrémentale de la structure d'indexation multidimensionnelle NSC qui a été démontrée efficace pour répondre aux requêtes skyline dans un contexte statique. Plus précisément, nous abordons (i) le cas des données dynamiques, c'est-à-dire que des tuples sont insérés ou supprimés à tout moment, et (ii) le cas des données en streaming, c'est-à-dire que les tuples sont insérés et écartés après un intervalle de temps spécifique. En cas de données dynamiques, nous repensons la structure et proposons des procédures pour gérer efficacement les insertions et les suppressions. En cas de données en streaming, nous proposons MSSD un pipeline de données qui gère les données par lot et maintient NSCt une variation de NSC. Dans une deuxième partie, nous abordons le cas des ordres dynamiques, c'est-à-dire que certains ou tous les attributs de l'ensemble de données sont catégoriques et chaque utilisateur exprime son propre ordre partiel sur le domaine de ces attributs. Nous proposons des algorithmes parallèles évolutifs qui décomposent une requête en un ensemble de sous-requêtes et traitent chaque sous-requête indépendamment. Pour optimiser davantage, nous proposons la matérialisation partielle des sous-requêtes et introduisons le problème de la sélection de sous-requêtes en fonction d'un coût. preference queries are interesting tools to compute small representatives of datasets or to rank tuples based on the users’ preferences. In this thesis, we mainly focus on the optimization of Skyline queries, a special class of preference queries, in dynamic contexts. In a

关键词： Optimisation Bases de données Algorithmes Requêtes de préférences Skyline Structure d'indexation Optimization Databases Algorithms preference queries Skyline Index structures

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SCSA: Evaluating skyline queries in incomplete data

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APPLIED INTELLIGENCE 2019年第5期49卷 1636-1657页

作者： Gulzar, Yonis Alwan, Ali A. Abdullah, Radhwan Mohamed Xin, Qin Swidan, Marwa B. Int Islamic Univ Malaysia Dept Comp Sci Kulliyyah Informat & Commun Technol Kuala Lumpur 53100 Malaysia Univ Mosul Div Basic Sci Coll Agr & Forestry Mosul Iraq Univ Putra Malaysia Fac Comp Sci & Informat Technol Serdang 43400 Malaysia Univ Faroe Islands Fac Sci & Technol Torshavn Denmark

Skyline queries have been extensively incorporated in various contemporary database applications. The list includes but is not limited to multi-criteria decision-making systems, decision support systems, and recommendation systems. Due to its great benefits and wide application range, many skyline algorithms have already been proposed in numerous data settings. Nonetheless, most researchers presume the completion of data meaning that all data item values are available. Since this assumption cannot be sustained in a large number of real-world database applications, the existing algorithms are rather inadequate to be directly applied on a database with incomplete data. In such cases, processing skyline queries on incomplete data incur exhaustive pairwise comparisons between data items, which may lead to loss of the transitivity property of the skyline technique. Losing the transitivity property may in turn give rise to the problem of cyclic dominance. In order to address these issues, we propose a new skyline algorithm called Sorting-based Cluster Skyline Algorithm (SCSA) that combines the sorting and partitioning techniques and simplifies the skyline computation on an incomplete datnset. These two techniques help boost the skyline process and avoid many unnecessary pairwise comparisons between data items to prune the dominated data items. The comprehensive experiments carried out on both synthetic and real-life datasets demonstrate the effectiveness and versatility of our approach as compared to the currently used approaches.

关键词： Skyline Skyline queries Incomplete data Missing data preference queries Query processing

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StreamPref: a query language for temporal conditional preferences on data streams

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JOURNAL OF INTELLIGENT INFORMATION SYSTEMS 2019年第2期53卷 329-360页

Over recent years, several studies regarding preference queries over data streams have been developed in database and artificial intelligence research fields. preference queries are useful in many decision making application areas, such as e-commerce, financial analysis, and content personalization. In this article, we explore new aspects of temporal conditional preference queries (tcp-queries) for the StreamPref query language. Tcp-queries allow the user to express how past instants of a data stream can influence the preference of a user at a present instant. In order to increase the utility of the StreamPref query language, we propose herein new operators that allow dealing with subsequences and filtering of sequences by length. To validate our proposal we present a detailed complexity analysis and an extensive set of experiments with synthetic and real datasets, which corroborate the efficiency of the algorithms and the utility of the new operators.

关键词： Data streams preference queries Temporal preferences Query language Operators

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