Journal articles: 'Group-query'

1

Deng, Ke, Shazia Sadiq, Xiaofang Zhou, Hu Xu, Gabriel Pui Cheong Fung, and Yansheng Lu. "On Group Nearest Group Query Processing." IEEE Transactions on Knowledge and Data Engineering 24, no. 2 (February 2012): 295–308. http://dx.doi.org/10.1109/tkde.2010.230.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Haryanto, Anasthasia Agnes, David Taniar, and Kiki Maulana Adhinugraha. "Group Reverse kNN Query optimisation." Journal of Computational Science 11 (November 2015): 205–21. http://dx.doi.org/10.1016/j.jocs.2015.09.006.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Shan, Jing, Derong Shen, Tiezheng Nie, Yue Kou, and Ge Yu. "Searching overlapping communities for group query." World Wide Web 19, no. 6 (December 2, 2015): 1179–202. http://dx.doi.org/10.1007/s11280-015-0378-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Li, Yafei, Rui Chen, Lei Chen, and Jianliang Xu. "Towards Social-Aware Ridesharing Group Query Services." IEEE Transactions on Services Computing 10, no. 4 (July 1, 2017): 646–59. http://dx.doi.org/10.1109/tsc.2015.2508440.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Lukasiewicz, Thomas, Maria Vanina Martinez, Gerardo I. Simari, and Oana Tifrea-Marciuska. "Ontology-Based Query Answering with Group Preferences." ACM Transactions on Internet Technology 14, no. 4 (December 17, 2014): 1–24. http://dx.doi.org/10.1145/2677207.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Sharma, Anjali, and Ajay Kr. Singh. "CBIR through CDH using Query by Group." International Journal of Computer Trends and Technology 28, no. 1 (October 25, 2015): 21–27. http://dx.doi.org/10.14445/22312803/ijctt-v28p106.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Zhou, Yinglian, and Jifeng Chen. "Time Series Geographic Social Network Dynamic Preference Group Query." International Journal of Information Systems in the Service Sector 13, no. 4 (October 2021): 18–39. http://dx.doi.org/10.4018/ijisss.2021100102.

Full text

Abstract:

Driven by experience and social impact of the new life, user preferences continue to change over time. In order to make up for the shortcomings of existing geographic social network models that often cannot obtain user dynamic preferences, a time-series geographic social network model was constructed to detect user dynamic preferences, a dynamic preference value model was built for user dynamic preference evaluation, and a dynamic preferences group query (DPG) was proposed in this paper . In order to optimize the efficiency of the DPG query algorithm, the UTC-tree index user timing check-in record is designed. UTC-tree avoids traversing all user check-in records in the query, accelerating user dynamic preference evaluation. Finally, the DPG query algorithm is used to implement a well-interacted DPG query system. Through a large number of comparative experiments, the validity of UTC-tree and the scalability of DPG query are verified.

APA, Harvard, Vancouver, ISO, and other styles

8

Liu, Jia, Wei Chen, Ziyang Chen, Lin Liu, Yuhong Wu, Kaiyu Liu, Amar Jain, and Yasser H. Elawady. "Optimized Query Algorithms for Top- K Group Skyline." Wireless Communications and Mobile Computing 2022 (January 4, 2022): 1–11. http://dx.doi.org/10.1155/2022/3404906.

Full text

Abstract:

Skyline query is a typical multiobjective query and optimization problem, which aims to find out the information that all users may be interested in a multidimensional data set. Multiobjective optimization has been applied in many scientific fields, including engineering, economy, and logistics. It is necessary to make the optimal decision when two or more conflicting objectives are weighed. For example, maximize the service area without changing the number of express points, and in the existing business district distribution, find out the area or target point set whose target attribute is most in line with the user’s interest. Group Skyline is a further extension of the traditional definition of Skyline. It considers not only a single point but a group of points composed of multiple points. These point groups should not be dominated by other point groups. For example, in the previous example of business district selection, a single target point in line with the user’s interest is not the focus of the research, but the overall optimality of all points in the whole target area is the final result that the user wants. This paper focuses on how to efficiently solve top- k group Skyline query problem. Firstly, based on the characteristics that the low levels of Skyline dominate the high level points, a group Skyline ranking strategy and the corresponding SLGS algorithm on Skyline layer are proposed according to the number of Skyline layer and vertices in the layer. Secondly, a group Skyline ranking strategy based on vertex coverage is proposed, and corresponding VCGS algorithm and optimized algorithm VCGS+ are proposed. Finally, experiments verify the effectiveness of this method from two aspects: query response time and the quality of returned results.

APA, Harvard, Vancouver, ISO, and other styles

9

Yang, De-Nian, Yi-Ling Chen, Wang-Chien Lee, and Ming-Syan Chen. "On social-temporal group query with acquaintance constraint." Proceedings of the VLDB Endowment 4, no. 6 (March 2011): 397–408. http://dx.doi.org/10.14778/1978665.1978671.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Liu, Yongshan, Xiang Gong, Dehan Kong, Tianbao Hao, and Xiaoqi Yan. "Research on Group Reverse Farthest Neighbour Query Algorithm." Journal of Physics: Conference Series 1624 (October 2020): 042011. http://dx.doi.org/10.1088/1742-6596/1624/4/042011.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Zhao, Xiangguo, Zhen Zhang, Hong Huang, and Xin Bi. "Social-aware spatial keyword top-k group query." Distributed and Parallel Databases 38, no. 3 (May 8, 2020): 601–23. http://dx.doi.org/10.1007/s10619-020-07292-0.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Wei, Xian Min. "Design and Implementation of Dynamic Query Component Based on Neural Network." Advanced Materials Research 171-172 (December 2010): 736–39. http://dx.doi.org/10.4028/www.scientific.net/amr.171-172.736.

Full text

Abstract:

This paper analyzed the principles of learning and associative memoryof artificial neural network, while combining with component-based software engineering (CBSE) development ideas, and designed dynamic data query component. To Innovatively and effectively combinate neural network (Instar rule) with the data query concretely. Dynamic data query components mainly consist of five group elements, in addition to system interface group element as a characteristic group element, the other as functional group elements. Under control flow, around the user's service request to analyze data profiling and query information feedback. In addition, dynamic data query component of internal work processes is briefly described. The design will be of practical value for the database management system.

APA, Harvard, Vancouver, ISO, and other styles

13

Moutafis, Panagiotis, George Mavrommatis, Michael Vassilakopoulos, and Antonio Corral. "Efficient Group K Nearest-Neighbor Spatial Query Processing in Apache Spark." ISPRS International Journal of Geo-Information 10, no. 11 (November 11, 2021): 763. http://dx.doi.org/10.3390/ijgi10110763.

Full text

Abstract:

Aiming at the problem of spatial query processing in distributed computing systems, the design and implementation of new distributed spatial query algorithms is a current challenge. Apache Spark is a memory-based framework suitable for real-time and batch processing. Spark-based systems allow users to work on distributed in-memory data, without worrying about the data distribution mechanism and fault-tolerance. Given two datasets of points (called Query and Training), the group K nearest-neighbor (GKNN) query retrieves (K) points of the Training with the smallest sum of distances to every point of the Query. This spatial query has been actively studied in centralized environments and several performance improving techniques and pruning heuristics have been also proposed, while, a distributed algorithm in Apache Hadoop was recently proposed by our team. Since, in general, Apache Hadoop exhibits lower performance than Spark, in this paper, we present the first distributed GKNN query algorithm in Apache Spark and compare it against the one in Apache Hadoop. This algorithm incorporates programming features and facilities that are specific to Apache Spark. Moreover, techniques that improve performance and are applicable in Apache Spark are also incorporated. The results of an extensive set of experiments with real-world spatial datasets are presented, demonstrating that our Apache Spark GKNN solution, with its improvements, is efficient and a clear winner in comparison to processing this query in Apache Hadoop.

APA, Harvard, Vancouver, ISO, and other styles

14

Fan, Liyue, Luca Bonomi, Cyrus Shahabi, and Li Xiong. "Optimal group route query: Finding itinerary for group of users in spatial databases." GeoInformatica 22, no. 4 (October 2018): 845–67. http://dx.doi.org/10.1007/s10707-018-0331-8.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

SONG, Xiao-Yu, Cheng-Cheng YU, Huan-Liang SUN, and Jing-Ke XU. "GRkNN: Group Reverse k-Nearest-Neighbor Query in Spatial Databases." Chinese Journal of Computers 33, no. 12 (May 23, 2011): 2229–38. http://dx.doi.org/10.3724/sp.j.1016.2010.02229.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Liu, Guliu, Lei Li, Guanfeng Liu, and Xindong Wu. "Social Group Query Based on Multi-Fuzzy-Constrained Strong Simulation." ACM Transactions on Knowledge Discovery from Data 16, no. 3 (June 30, 2022): 1–27. http://dx.doi.org/10.1145/3481640.

Full text

Abstract:

Traditional social group analysis mostly uses interaction models, event models, or other social network analysis methods to identify and distinguish groups. This type of method can divide social participants into different groups based on their geographic location, social relationships, and/or related events. However, in some applications, it is necessary to make more specific restrictions on the members and the interactions between members of the group. Generally, Graph Pattern Matching (GPM) technique is used to solve this problem. However, the existing GPM methods rarely consider the rich contextual information of nodes and edges to measure the credibility between members. In this article, first, a social group query problem that needs to consider the trust between members of the group is proposed. Then, to solve this problem, a multi-fuzzy-constrained strong simulation matching model is proposed based on multi-constrained simulation, and a Strong Simulation GPM algorithm (NTSS) based on the exploration of pattern Node Topological ordered sequence is proposed. Aiming at the inefficiency of the NTSS algorithm when pattern graph with multiple nodes with zero in-degree and the problem of repeated calculation of matching edges shared by multiple matching subgraphs, two optimization strategies are proposed. Finally, we conduct verification experiments on the effectiveness and efficiency of the NTSS algorithm and the algorithms with the optimization strategies on four social network datasets in real applications. Experimental results show that the NTSS algorithm is significantly better than the existing multi-constrained GPM algorithm, and the NTSS_Inv_EdgC algorithm, which combines two optimization strategies, greatly improves the efficiency of the NTSS algorithm.

APA, Harvard, Vancouver, ISO, and other styles

17

Mingan, Qu. "Group Marriage and Promiscuity in Chinese Primitive Society: A Query." Chinese Sociology & Anthropology 35, no. 3 (April 2003): 69–84. http://dx.doi.org/10.2753/csa0009-4625350369.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Song, Xiaoxu, Bin Wang, Xiaochun Yang, Jing Qin, Liang Zhao, and Lianqiang Niu. "SGEQ: A New Social Group Enlarging Query With Size Constraints." IEEE Access 8 (2020): 193608–20. http://dx.doi.org/10.1109/access.2020.3032987.

Full text

APA, Harvard, Vancouver, ISO, and other styles

19

Fazzinga, Bettina, Thomas Lukasiewicz, Maria Vanina Martinez, Gerardo I. Simari, and Oana Tifrea-Marciuska. "Ontological query answering under many-valued group preferences in Datalog+/–." International Journal of Approximate Reasoning 93 (February 2018): 354–71. http://dx.doi.org/10.1016/j.ijar.2017.11.008.

Full text

APA, Harvard, Vancouver, ISO, and other styles

20

Hu, Xiaocheng, Yufei Tao, Yi Yang, and Shuigeng Zhou. "Semi-Group Range Sum Revisited: Query-Space Lower Bound Tightened." Algorithmica 80, no. 4 (April 3, 2017): 1315–29. http://dx.doi.org/10.1007/s00453-017-0307-3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

21

Guo, Ya Hong, Xu Liu, and Qian Qian Ren. "A Grouping Cache Based Joins Query Algorithm in MANET." Advanced Materials Research 532-533 (June 2012): 914–18. http://dx.doi.org/10.4028/www.scientific.net/amr.532-533.914.

Full text

Abstract:

Aiming at the problem of joins query in MANET, we proposed a grouping cache mechanism, which builds grouping cache considering the features of data. The proposed mechanism can implement the cooperating cache between groups and update cache information dynamically, which leads to the improvement of query hit ratio and decrease of response time. Based on the grouping cache, a novel joins query algorithm is presented. The algorithm optimizes the query plan using dynamic programming scheme. Then it constructs an optimal execution plan for each sub join query with available cache data taken into account. Simulation results indicated that the group-based cache mechanism can improve the hit ratio, reduce query response time and conserve energy of the network efficiently.

APA, Harvard, Vancouver, ISO, and other styles

22

Copeland, Daniel, and Jamie Pommersheim. "Quantum query complexity of symmetric oracle problems." Quantum 5 (March 7, 2021): 403. http://dx.doi.org/10.22331/q-2021-03-07-403.

Full text

Abstract:

We study the query complexity of quantum learning problems in which the oracles form a group G of unitary matrices. In the simplest case, one wishes to identify the oracle, and we find a description of the optimal success probability of a t-query quantum algorithm in terms of group characters. As an application, we show that Ω(n) queries are required to identify a random permutation in Sn. More generally, suppose H is a fixed subgroup of the group G of oracles, and given access to an oracle sampled uniformly from G, we want to learn which coset of H the oracle belongs to. We call this problem coset identification and it generalizes a number of well-known quantum algorithms including the Bernstein-Vazirani problem, the van Dam problem and finite field polynomial interpolation. We provide character-theoretic formulas for the optimal success probability achieved by a t-query algorithm for this problem. One application involves the Heisenberg group and provides a family of problems depending on n which require n+1 queries classically and only 1 query quantumly.

APA, Harvard, Vancouver, ISO, and other styles

23

Kumar, Ram, Kuldeep Narayan Tripathi, and Subhash Chander Sharma. "Optimal Query Expansion Based on Hybrid Group Mean Enhanced Chimp Optimization Using Iterative Deep Learning." Electronics 11, no. 10 (May 12, 2022): 1556. http://dx.doi.org/10.3390/electronics11101556.

Full text

Abstract:

The internet is surrounded by uncertain information which necessitates the usage of natural language processing and soft computing techniques to extract the relevant documents. The relevant results are retrieved using the query expansion technique which is mainly formulated using the machine learning or deep learning concepts in the existing literature. This paper presents a hybrid group mean-based optimizer-enhanced chimp optimization (GMBO-ECO) algorithm for pseudo-relevance-based query expansion, whereby the actual queries are expanded with their related keywords. The hybrid GMBO-ECO algorithm mainly expands the query based on the terms that have a strong interrelationship with the actual query. To generate the word embeddings, a Word2Vec paradigm is used which learns the word association from large text corpora. The useful context in the text is identified using the improved iterative deep learning framework which determines the user’s intent for the current web search. This step reduces the mismatch of the words and improves the performance of query retrieval. The weak terms are eliminated and the candidate query terms for optimal query expansion are improved via an Okapi measure and cosine similarity techniques. The proposed methodology has been compared to the state-of-the-art methods with and without a query expansion approach. Moreover, the proposed optimal query expansion technique has shown a substantial improvement in terms of a normalized discounted cumulative gain of 0.87, a mean average precision of 0.35, and a mean reciprocal rank of 0.95. The experimental results show the efficiency of the proposed methodology in retrieving the appropriate response for information retrieval. The most common applications for the proposed method are search engines.

APA, Harvard, Vancouver, ISO, and other styles

24

Shakeel, Asif. "An improved query for the hidden subbroup problem." Quantum Information and Computation 14, no. 5&6 (May 2014): 467–92. http://dx.doi.org/10.26421/qic14.5-6-6.

Full text

Abstract:

The Hidden Subgroup Problem (HSP) is at the forefront of problems in quantum algorithms. In this paper, we introduce a new query, the \textit{character} query, generalizing the well-known phase kickback trick that was first used successfully to efficiently solve Deutsch's problem. An equal superposition query with $\vert 0 \rangle$ in the response register is typically used in the ``standard method" of single-query algorithms for the HSP. The proposed character query improves over this query by maximizing the success probability of subgroup identification under a uniform prior, for the HSP in which the oracle functions take values in a finite abelian group. We apply our results to the case when the subgroups are drawn from a set of conjugate subgroups and obtain a success probability greater than that found by Moore and Russell.

APA, Harvard, Vancouver, ISO, and other styles

25

Yi, Ke, Feifei Li, Graham Cormode, Marios Hadjieleftheriou, George Kollios, and Divesh Srivastava. "Small synopses for group-by query verification on outsourced data streams." ACM Transactions on Database Systems 34, no. 3 (August 2009): 1–42. http://dx.doi.org/10.1145/1567274.1567277.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Pan, Jie, Frédéric Magoulès, and Yann Le Biannic. "Implementing and Optimizing Multiple Group by Query in a MapReduce Approach." Journal of Algorithms & Computational Technology 4, no. 2 (June 2010): 183–205. http://dx.doi.org/10.1260/1748-3018.4.2.183.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

Li, Jiajia, Xiufeng Xia, Xiangyu Liu, Botao Wang, Dahai Zhou, and Yunzhe An. "Probabilistic group nearest neighbor query optimization based on classification using ELM." Neurocomputing 277 (February 2018): 21–28. http://dx.doi.org/10.1016/j.neucom.2017.05.095.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Eich, Marius, Pit Fender, and Guido Moerkotte. "Efficient generation of query plans containing group-by, join, and groupjoin." VLDB Journal 27, no. 5 (August 17, 2017): 617–41. http://dx.doi.org/10.1007/s00778-017-0476-3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Vaidyanathan, Rekha, Sujoy Das, and Namita Srivastava. "Query Expansion based on Central Tendency and PRF for Monolingual Retrieval." International Journal of Information Retrieval Research 6, no. 4 (October 2016): 30–50. http://dx.doi.org/10.4018/ijirr.2016100103.

Full text

Abstract:

Query Expansion is the process of selecting relevant words that are closest in meaning and context to that of the keyword(s) of query. In this paper, a statistical method of automatically selecting contextually related words for expansion, after identifying a pattern in their score, is proposed. Words appearing in top 10 relevant document is given a score w.r.t partitions they appear in. Proposed statistical method, identifies a pattern of central tendency in the high scores and selects the right group of words for query expansion. The objective of the method is to keep the expanded query with minimum words (light), and still give statistically significant MAP values compared to the original query. Experimental results show 17-21% improvement of MAP over the original unexpanded query as baseline but achieves a performance similar to that of the state of the art query expansion models - Bo1 and KL. FIRE 2011 Adhoc English and Hindi data for 50 topics each were used for experiments with Terrier as the Retrieval Engine.

APA, Harvard, Vancouver, ISO, and other styles

30

Leeuwen, Wilco v., Thomas Mulder, Bram van de Wall, George Fletcher, and Nikolay Yakovets. "AvantGraph query processing engine." Proceedings of the VLDB Endowment 15, no. 12 (August 2022): 3698–701. http://dx.doi.org/10.14778/3554821.3554878.

Full text

Abstract:

We demonstrate AvantGraph, a graph query processing engine developed by the Database group at TU Eindhoven. Designed for efficient processing of both subgraph matching and navigational graph queries, AvantGraph encompasses innovation in three key areas: the planner, the cardinality estimator, and the execution engine. We present demonstration scenarios covering a wide range of workloads across diverse domains which (1) provides deep insights into the core challenges of complex graph query processing and (2) showcases corresponding critical optimizations via "under-the-hood" operational insights of AvantGraph's key components.

APA, Harvard, Vancouver, ISO, and other styles

31

Zwölf, C. M., N. Moreau, Y. A. Ba, and M. L. Dubernet. "Citation of evolving data in distributed asynchronous infrastructures." Proceedings of the International Astronomical Union 15, S350 (April 2019): 392–93. http://dx.doi.org/10.1017/s174392131900783x.

Full text

Abstract:

AbstractThe VAMDC Consortium intended to find a way for users to cite the datasets accessed through the infrastructure. The Research Data Alliance Data citation working group provided the researchers and data centres communities with a recommendation to identify and cite dynamic data. This recommendation perfectly matched the VAMDC needs: the proposed solution relies on a query centric view and the set-up of a Query Store. Data should be stored in a versioned time-stamped manner and accessed through queries. The Query Store we implemented for VAMDC is interlinked with Zenodo. Since Zenodo is indexed in OpenAIRE and since the latter implements Scholix, VAMDC indirectly implements Scholix via its Query Store. The paper outlines the successes and limitations of the above approach.

APA, Harvard, Vancouver, ISO, and other styles

32

Li, Jincao, and Ming Xu. "A parametric approximation algorithm for spatial group keyword queries." Intelligent Data Analysis 25, no. 2 (March 4, 2021): 305–19. http://dx.doi.org/10.3233/ida-195071.

Full text

Abstract:

With the application of big data, various queries arise for information retrieval. Spatial group keyword queries aim to find a set of spatial objects that cover the query keywords and minimize a goal function such as the total distance between the objects and the query point. This problem is widely found in database applications and is known to be NP-hard. Efficient algorithms for solving this problem can only provide approximate solutions, and most of these algorithms achieve a fixed approximation ratio (the upper bound of the ratio of an approximate goal value to the optimal goal value). Thus, to obtain a self-adjusting algorithm, we propose an approximation algorithm for achieving a parametric approximation ratio. The algorithm makes a trade-off between the approximation ratio and time consumption enabling the users to assign arbitrary query accuracy. Additionally, it runs in an on-the-fly manner, making it scalable to large-scale applications. The efficiency and scalability of the algorithm were further validated using benchmark datasets.

APA, Harvard, Vancouver, ISO, and other styles

33

Guo, Jingjing, and Jiacong Sun. "Secure and Practical Group Nearest Neighbor Query for Location-Based Services in Cloud Computing." Security and Communication Networks 2021 (September 25, 2021): 1–17. http://dx.doi.org/10.1155/2021/5686506.

Full text

Abstract:

Group nearest neighbor (GNN) query enables a group of location-based service (LBS) users to retrieve a point from point of interests (POIs) with the minimum aggregate distance to them. For resource constraints and privacy concerns, LBS provider outsources the encrypted POIs to a powerful cloud server. The encryption-and-outsourcing mechanism brings a challenge for the data utilization. However, as previous work from k − anonymity technique leaks all contents of POIs and returns an answer set with redundant communication cost, the LBS system cannot work properly with those privacy-preserving schemes. In this paper, we illustrate a secure group nearest neighbor query scheme, which is referred to as SecGNN. It supports the GNN query with n n ≥ 3 LBS users and assures the data privacy and query privacy. Since SecGNN only achieves linear search complexity, an efficiency enhanced scheme (named Sec GNN + ) is introduced by taking advantage of the KD-tree data structure. Specifically, we convert the GNN problem to the nearest neighbor problem for their centroid, which can be computed by anonymous veto network and Burmester–Desmedt conference key agreement protocols. Furthermore, the Sec GNN + scheme is introduced from the KD-tree data structure and a designed tool, which supports the computation of inner products over ciphertexts. Finally, we run experiments on a real-database and a random database to evaluate the performance of our SecGNN and Sec GNN + schemes. The experimental results show the high efficiency of our proposed schemes.

APA, Harvard, Vancouver, ISO, and other styles

34

Bellala, Gowtham, Suresh K. Bhavnani, and Clayton Scott. "Group-Based Active Query Selection for Rapid Diagnosis in Time-Critical Situations." IEEE Transactions on Information Theory 58, no. 1 (January 2012): 459–78. http://dx.doi.org/10.1109/tit.2011.2169296.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Zhao, Yawei, Tinghuai Ma, and Feng Liu. "Research on Index Technology for Group-by Aggregation Query in XML Cube." Information Technology Journal 9, no. 1 (December 15, 2009): 116–23. http://dx.doi.org/10.3923/itj.2010.116.123.

Full text

APA, Harvard, Vancouver, ISO, and other styles

36

Dong, Yihan, Liu Chang, Jingwen Luo, and Jia Wu. "A Routing Query Algorithm Based on Time-Varying Relationship Group in Opportunistic Social Networks." Electronics 10, no. 13 (July 2, 2021): 1595. http://dx.doi.org/10.3390/electronics10131595.

Full text

Abstract:

With the fast development of IoT and 5G technologies, opportunity social networks composed of portable mobile devices have become a hot research topic in recent years. However, arbitrary node movement in opportunity networks and the absence of end-to-end pathways make node communication unstable. At the same time, the problem of ignoring human social preferences and relying on wrong message relay nodes lead to a low data transmission rate and high network overhead. Based on the above issues, we propose a time-varying relationship groups-based routing query algorithm for mobile opportunity networks (Time-varying Relationship Groups, TVRGs). Firstly, we construct the relationship groups based on the time-varying characteristics according to the intimacy between users. Secondly, we calculate the importance of nodes by their connectivity time and communication frequency. Finally, we find the suitable message relay nodes according to the similarity of node weights and their action trajectories and design the routing query algorithm accordingly. The simulation results show that the algorithm can vastly improve the message query success rate, effectively improve the data transmission efficiency, and reduce the average delay and system overhead compared with the existing routing algorithms.

APA, Harvard, Vancouver, ISO, and other styles

37

Zhang, Lin, Chao Jin, Hai-ping Huang, Xiong Fu, and Ru-chuan Wang. "A Trajectory Privacy Preserving Scheme in the CANNQ Service for IoT." Sensors 19, no. 9 (May 12, 2019): 2190. http://dx.doi.org/10.3390/s19092190.

Full text

Abstract:

Nowadays, anyone carrying a mobile device can enjoy the various location-based services provided by the Internet of Things (IoT). ‘Aggregate nearest neighbor query’ is a new type of location-based query which asks the question, ‘what is the best location for a given group of people to gather?’ There are numerous, promising applications for this type of query, but it needs to be done in a secure and private way. Therefore, a trajectory privacy-preserving scheme, based on a trusted anonymous server (TAS) is proposed. Specifically, in the snapshot queries, the TAS generates a group request that satisfies the spatial K-anonymity for the group of users—to prevent the location-based service provider (LSP) from an inference attack—and in continuous queries, the TAS determines whether the group request needs to be resent by detecting whether the users will leave their secure areas, so as to reduce the probability that the LSP reconstructs the users’ real trajectories. Furthermore, an aggregate nearest neighbor query algorithm based on strategy optimization, is adopted, to minimize the overhead of the LSP. The response speed of the results is improved by narrowing the search scope of the points of interest (POIs) and speeding up the prune of the non-nearest neighbors. The security analysis and simulation results demonstrated that our proposed scheme could protect the users’ location and trajectory privacy, and the response speed and communication overhead of the service, were superior to other peer algorithms, both in the snapshot and continuous queries.

APA, Harvard, Vancouver, ISO, and other styles

38

Zheng, Wei, Hui Fang, Hong Cheng, and Xuanhui Wang. "Diversifying Search Results through Pattern-Based Subtopic Modeling." International Journal on Semantic Web and Information Systems 8, no. 4 (October 2012): 37–56. http://dx.doi.org/10.4018/jswis.2012100103.

Full text

Abstract:

Traditional information retrieval models do not necessarily provide users with optimal search experience because the top ranked documents may contain excessively redundant information. Therefore, satisfying search results should be not only relevant to the query but also diversified to cover different subtopics of the query. In this paper, the authors propose a novel pattern-based framework to diversify search results, where each pattern is a set of semantically related terms covering the same subtopic. They first apply a maximal frequent pattern mining algorithm to extract the patterns from retrieval results of the query. The authors then propose to model a subtopic with either a single pattern or a group of similar patterns. A profile-based clustering method is adapted to group similar patterns based on their context information. The search results are then diversified using the extracted subtopics. Experimental results show that the proposed pattern-based methods are effective to diversify the search results.

APA, Harvard, Vancouver, ISO, and other styles

39

Dong, Zheng, Xin Huang, Guorui Yuan, Hengshu Zhu, and Hui Xiong. "Butterfly-core community search over labeled graphs." Proceedings of the VLDB Endowment 14, no. 11 (July 2021): 2006–18. http://dx.doi.org/10.14778/3476249.3476258.

Full text

Abstract:

Community search aims at finding densely connected subgraphs for query vertices in a graph. While this task has been studied widely in the literature, most of the existing works only focus on finding homogeneous communities rather than heterogeneous communities with different labels. In this paper, we motivate a new problem of cross-group community search, namely Butterfly-Core Community (BCC), over a labeled graph, where each vertex has a label indicating its properties and an edge between two vertices indicates their cross relationship. Specifically, for two query vertices with different labels, we aim to find a densely connected cross community that contains two query vertices and consists of butterfly networks, where each wing of the butterflies is induced by a k-core search based on one query vertex and two wings are connected by these butterflies. We first develop a heuristic algorithm achieving 2-approximation to the optimal solution. Furthermore, we design fast techniques of query distance computations, leader pair identifications, and index-based BCC local explorations. Extensive experiments on seven real datasets and four useful case studies validate the effectiveness and efficiency of our BCC and its multi-labeled extension models.

APA, Harvard, Vancouver, ISO, and other styles

40

ZHU, QIANG, and P. Å. LARSON. "CLASSIFYING LOCAL QUERIES FOR GLOBAL QUERY OPTIMIZATION IN MULTIDATABASE SYSTEMS." International Journal of Cooperative Information Systems 09, no. 03 (September 2000): 315–55. http://dx.doi.org/10.1142/s0218843000000156.

Full text

Abstract:

A multidatabase system (MDBS) integrates information from multiple pre-existing local databases. A major challenge for global query optimization in an MDBS is that some required local information about local database systems such as local cost models may not be available at the global level due to local autonomy. A feasible method to tackle this challenge is to group local queries on a local database system into classes and then use the costs of sample queries from each query class to derive a cost formula for the class via regression analysis. This paper discusses the issues on how to classify local queries so that a good cost formula can be derived for each query class. Two classification approaches, i.e. bottom-up and top-down, are suggested. The relationship between these two approaches is discussed. Classification rules that can be used in the approaches are identified. Problems regarding composition and redundancy of classification rules are studied. Classification algorithms are given. To test the membership of a query in a class, an efficient algorithm based on ranks is introduced. In addition, a hybrid classification approach that combines the bottom-up and top-down ones is also suggested. Experimental results demonstrate that the suggested query classification techniques can be used to derive good local cost formulas for global query optimization in an MDBS.

APA, Harvard, Vancouver, ISO, and other styles

41

Ullah, Mohib, Rafi Ullah Khan, Irfan Ullah Khan, Nida Aslam, Sumayh S. Aljameel, Muhammad Inam Ul Haq, and Muhammad Arshad Islam. "Profile Aware ObScure Logging (PaOSLo): A Web Search Privacy-Preserving Protocol to Mitigate Digital Traces." Security and Communication Networks 2022 (February 3, 2022): 1–13. http://dx.doi.org/10.1155/2022/2109024.

Full text

Abstract:

Web search querying is an inevitable activity of any Internet user. The web search engine (WSE) is the easiest way to search and retrieve data from the Internet. The WSE stores the user’s search queries to retrieve the personalized search result in a form of query log. A user often leaves digital traces and sensitive information in the query log. WSE is known to sell the query log to a third party to generate revenue. However, the release of the query log can compromise the security and privacy of a user. In this work, we propose a Profile Aware ObScure Logging (PaOSLo) Web search privacy-preserving protocol that mitigates the digital traces a user leaves in Web searching. PaOSLo systematically groups users based on profile similarity. The primary objective of this work is to evaluate the impact of the systematic group compared to random grouping. We first computed the similarity between the users’ profiles and then clustered them using the K-mean algorithm to group the users systematically. Unlikability and indistinguishability are the two dimensions in which we have measured the privacy of a user. To compute the impact of systematic grouping on a user’s privacy, we have experimented with and compared the performance of PaOSLo with modern distributed protocols like OSLo and UUP(e). Results show that, at the top degree of the ODP hierarchy, PaOSLo preserved 10% and 3% better profile privacy than the modern distributed protocols mentioned above. In addition, the PaOSLo has less profile exposure for any group size and at each degree of the ODP hierarchy.

APA, Harvard, Vancouver, ISO, and other styles

42

Nayak, Ashwin. "Deterministic algorithms for the hidden subgroup problem." Quantum Information and Computation 22, no. 9&10 (July 2022): 755–69. http://dx.doi.org/10.26421/qic22.9-10-3.

Full text

Abstract:

We present deterministic algorithms for the Hidden Subgroup Problem. The first algorithm, for abelian groups, achieves the same asymptotic worst-case query complexity as the optimal randomized algorithm, namely~$ \Order(\sqrt{ n}\, )$, where~$n$ is the order of the group. The analogous algorithm for non-abelian groups comes within a~$\sqrt{ \log n}$ factor of the optimal randomized query complexity. The best known randomized algorithm for the Hidden Subgroup Problem has \emph{expected\/} query complexity that is sensitive to the input, namely~$ \Order(\sqrt{ n/m}\, )$, where~$m$ is the order of the hidden subgroup. In the first version of this article~\cite[Sec.~5]{Nayak21-hsp-classical}, we asked if there is a deterministic algorithm whose query complexity has a similar dependence on the order of the hidden subgroup. Prompted by this question, Ye and Li~\cite{YL21-hsp-classical} present deterministic algorithms for \emph{abelian\/} groups which solve the problem with~$ \Order(\sqrt{ n/m }\, )$ queries, and find the hidden subgroup with~$ \Order( \sqrt{ n (\log m) / m} + \log m ) $ queries. Moreover, they exhibit instances which show that in general, the deterministic query complexity of the problem may be~$\order(\sqrt{ n/m } \,)$, and that of \emph{finding\/} the entire subgroup may also be~$\order(\sqrt{ n/m } \,)$ or even~$\upomega(\sqrt{ n/m } \,) $.}We present a different deterministic algorithm for the Hidden Subgroup Problem that also has query complexity~$ \Order(\sqrt{ n/m }\, )$ for abelian groups. The algorithm is arguably simpler. Moreover, it works for non-abelian groups, and has query complexity~$ \Order(\sqrt{ (n/m) \log (n/m) }\,) $ for a large class of instances, such as those over supersolvable groups. We build on this to design deterministic algorithms to find the hidden subgroup for all abelian and some non-abelian instances, at the cost of a~$\log m$ multiplicative factor increase in the query complexity.

APA, Harvard, Vancouver, ISO, and other styles

43

Mawhirter, Daniel, Sam Reinehr, Connor Holmes, Tongping Liu, and Bo Wu. "GraphZero." ACM SIGOPS Operating Systems Review 55, no. 1 (June 2, 2021): 21–37. http://dx.doi.org/10.1145/3469379.3469383.

Full text

Abstract:

Subgraph matching is a fundamental task in many applications which identifies all the embeddings of a query pattern in an input graph. Compilation-based subgraph matching systems generate specialized implementations for the provided patterns and often substantially outperform other systems. However, the generated code causes significant computation redundancy and the compilation process incurs too much overhead to be used online, both due to the inherent symmetry in the structure of the query pattern. In this paper, we propose an optimizing query compiler, named GraphZero, to completely address these limitations through symmetry breaking based on group theory. GraphZero implements three novel techniques. First, its schedule explorer efficiently prunes the schedule space without missing any high-performance schedule. Second, it automatically generates and enforces a set of restrictions to eliminate computation redundancy. Third, it generalizes orientation, a surprisingly effective optimization that was only used for clique patterns, to apply to arbitrary patterns. Evaluation on multiple query patterns shows that GraphZero outperforms two state-of-the-art compilation and non-compilation based systems by up to 40X and 2654X, respectively.

APA, Harvard, Vancouver, ISO, and other styles

44

Wang, Haitao. "Aggregate-MAX Top-k Nearest Neighbor Searching in the L1 Plane." International Journal of Computational Geometry & Applications 25, no. 01 (March 2015): 57–76. http://dx.doi.org/10.1142/s0218195915500053.

Full text

Abstract:

We study the aggregate/group top-k nearest neighbor searching for the Max operator in the plane, where the distances are measured by the L1 metric. Let P be a set of n points in the plane. Given a query set Q of m points, for each point p ∈ P, the aggregate-max distance from p to Q is defined to be the maximum distance from p to all points in Q. Given Q and an integer k with 1 ≤ k ≤ n, the query asks for the k points of P that have the smallest aggregate-max distances to Q. We build a data structure of O(n) size in O(n log n) time, such that each query can be answered in O(m+k log n) time and the k points are reported in sorted order by their aggregate-max distances to Q. Alternatively, we build a data structure of O(n log n) size in O(n log2 n) time that can answer each query in O(m + k + log3 n) time.

APA, Harvard, Vancouver, ISO, and other styles

45

Raju, Y., Dr D. Suresh Babu, and Dr K. Anuradha. "A Web Search Personalization Based on Probability of Semantic Similarity between User Log and Query with Web Page." International Journal of Engineering & Technology 7, no. 4.24 (November 27, 2018): 59. http://dx.doi.org/10.14419/ijet.v7i4.24.21856.

Full text

Abstract:

Web search personalization is recognized as a competent solution to address the problem of query-relevant search as per the user interest, while it able to present dissimilar search results based upon the preferences and information requirements of users. The popular search engines provide their search results interpreting the user query only, which mostly have unrelated results due to the keywords ambiguity problem. In order to have satisfied and user interesting result, it is important to personalize the results according to their relevancies. In this paper, we propose a Web search Personalization based on a Probability of Semantic Similarity (WP-PSS) between user log and query with search result webpage. It performs a probability of semantic similarities computation between the user query and search result webpage snippet, and compute the frequency of link associated with the log data. Based on these two computed factors a probability of similarities association is computed to group and re-rank the search results for the personalization. Experiment evaluation over a set of multi-domain web searched data collection shows an accuracy improvisation.

APA, Harvard, Vancouver, ISO, and other styles

46

Jia, Lianyin, Junzhuo Tang, Mengjuan Li, Runxin Li, Jiaman Ding, and Yinong Chen. "A Trie Based Set Similarity Query Algorithm." Mathematics 11, no. 1 (January 2, 2023): 229. http://dx.doi.org/10.3390/math11010229.

Full text

Abstract:

Set similarity query is a primitive for many applications, such as data integration, data cleaning, and gene sequence alignment. Most of the existing algorithms are inverted index based, they usually filter unqualified sets one by one and do not have sufficient support for duplicated sets, thus leading to low efficiency. To solve this problem, this paper designs T-starTrie, an efficient trie based index for set similarity query, which can naturally group sets with the same prefix into one node, and can filter all sets corresponding to the node at a time, thereby significantly improving the candidates generation efficiency. In this paper, we find that the set similarity query problem can be transformed into matching nodes of the first-layer (FMNodes) detecting problem on T-starTrie. Therefore, an efficient FLMNode detection algorithm is designed. Based on this, an efficient set similarity query algorithm, TT-SSQ, is implemented by developing a variety of filtering techniques. Experimental results show that TT-SSQ can be up to 3.10x faster than existing algorithms.

APA, Harvard, Vancouver, ISO, and other styles

47

Tao, Yuchao, Amir Gilad, Ashwin Machanavajjhala, and Sudeepa Roy. "DPXPlain." Proceedings of the VLDB Endowment 16, no. 1 (September 2022): 113–26. http://dx.doi.org/10.14778/3561261.3561271.

Full text

Abstract:

Differential privacy (DP) is the state-of-the-art and rigorous notion of privacy for answering aggregate database queries while preserving the privacy of sensitive information in the data. In today's era of data analysis, however, it poses new challenges for users to understand the trends and anomalies observed in the query results: Is the unexpected answer due to the data itself, or is it due to the extra noise that must be added to preserve DP? In the second case, even the observation made by the users on query results may be wrong. In the first case, can we still mine interesting explanations from the sensitive data while protecting its privacy? To address these challenges, we present a three-phase framework DPXPlain, which is the first system to the best of our knowledge for explaining group-by aggregate query answers with DP. In its three phases, DPXPlain (a) answers a group-by aggregate query with DP, (b) allows users to compare aggregate values of two groups and with high probability assesses whether this comparison holds or is flipped by the DP noise, and (c) eventually provides an explanation table containing the approximately 'top-k' explanation predicates along with their relative influences and ranks in the form of confidence intervals, while guaranteeing DP in all steps. We perform an extensive experimental analysis of DPXPlain with multiple use-cases on real and synthetic data showing that DPXPlain efficiently provides insightful explanations with good accuracy and utility.

APA, Harvard, Vancouver, ISO, and other styles

48

Ismail, Anis, and Aziz Barbar. "A Simulation Framework for P2P Queries Routing for E-Business." International Journal of E-Entrepreneurship and Innovation 3, no. 2 (April 2012): 29–50. http://dx.doi.org/10.4018/jeei.2012040103.

Full text

Abstract:

On-line business transaction processing systems have so far been based on centralized or client-server architectures. The growing interest in Peer-to-Peer centralized or decentralized systems has inspired numerous research activities, though in a schema-based Peer-to-Peer (P2P) system, locating Peers (services) relevant to a given query is a basic problem for which different routing strategies of queries have been proposed. In this paper, the architecture, based on (Super-) Peers, is proposed, with a special focus on query routing. For an efficient query routing, (Super-) Peers having similar interests are grouped together and called Super-Super-Peers (SSP). Super-Peers submit queries that are often processed by members of this group. A SSP is a specific Super-Peer that contains knowledge about 1) its Super-Peers, and 2) the other SSP. Using data mining techniques knowledge is extracted by processing queries of Peers that transit on the network. The advantage of this distributed knowledge is that it avoids making semantic mapping between heterogeneous data sources owned by (Super-) Peers each time the system decides to route query to other (Super-) Peers.

APA, Harvard, Vancouver, ISO, and other styles

49

Liu, Yongshan, Xiang Gong, Dehan Kong, Tianbao Hao, and Xiaoqi Yan. "A Voronoi-Based Group Reverse k Farthest Neighbor Query Method in the Obstacle Space." IEEE Access 8 (2020): 50659–73. http://dx.doi.org/10.1109/access.2020.2979739.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

Lee, Sang-Hyeok, Sangjin Ahn, and Mi-hyun Kim. "Comparing a Query Compound with Drug Target Classes Using 3D-Chemical Similarity." International Journal of Molecular Sciences 21, no. 12 (June 12, 2020): 4208. http://dx.doi.org/10.3390/ijms21124208.

Full text

Abstract:

3D similarity is useful in predicting the profiles of unprecedented molecular frameworks that are 2D dissimilar to known compounds. When comparing pairs of compounds, 3D similarity of the pairs depends on conformational sampling, the alignment method, the chosen descriptors, and the similarity coefficients. In addition to these four factors, 3D chemocentric target prediction of an unknown compound requires compound–target associations, which replace compound-to-compound comparisons with compound-to-target comparisons. In this study, quantitative comparison of query compounds to target classes (one-to-group) was achieved via two types of 3D similarity distributions for the respective target class with parameter optimization for the fitting models: (1) maximum likelihood (ML) estimation of queries, and (2) the Gaussian mixture model (GMM) of target classes. While Jaccard–Tanimoto similarity of query-to-ligand pairs with 3D structures (sampled multi-conformers) can be transformed into query distribution using ML estimation, the ligand pair similarity within each target class can be transformed into a representative distribution of a target class through GMM, which is hyperparameterized via the expectation–maximization (EM) algorithm. To quantify the discriminativeness of a query ligand against target classes, the Kullback–Leibler (K–L) divergence of each query was calculated and compared between targets. 3D similarity-based K–L divergence together with the probability and the feasibility index, (Fm), showed discriminative power with regard to some query–class associations. The K–L divergence of 3D similarity distributions can be an additional method for (1) the rank of the 3D similarity score or (2) the p-value of one 3D similarity distribution to predict the target of unprecedented drug scaffolds.

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'Group-query'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles