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K-Join: Knowledge-Aware Similarity Join

Zeyuan Shang, Yaxiao Liu, Guoliang Li, Jianhua Feng
2016 IEEE Transactions on Knowledge and Data Engineering  
To the best of our knowledge, this is the first study on knowledge-aware similarity join. There are two main challenges. The first is how to quantify the knowledge-aware similarity.  ...  To address this problem, we study knowledge-aware similarity join, which, given a knowledge hierarchy and two collections of objects (e.g., documents), finds all knowledge-aware similar object pairs.  ...  K-Join + took a little more time than K-Join as it found more results. CONCLUSION We study a new problem, knowledge-aware similarity join.  ... 
doi:10.1109/tkde.2016.2601325 fatcat:jlpw37qbafhzleowq5xdurmkdu

K-Join: Knowledge-Aware Similarity Join

Zeyuan Shang, Yaxiao Liu, Guoliang Li, Jianhua Feng
2017 2017 IEEE 33rd International Conference on Data Engineering (ICDE)  
To the best of our knowledge, this is the first study on knowledge-aware similarity join. There are two main challenges. The first is how to quantify the knowledge-aware similarity.  ...  To address this problem, we study knowledge-aware similarity join, which, given a knowledge hierarchy and two collections of objects (e.g., documents), finds all knowledge-aware similar object pairs.  ...  K-Join + took a little more time than K-Join as it found more results. CONCLUSION We study a new problem, knowledge-aware similarity join.  ... 
doi:10.1109/icde.2017.18 dblp:conf/icde/ShangLLF17 fatcat:46d26u52ffcplouks4mpwkpf44

Supporting top-k join queries in relational databases

IhabF. Ilyas, WalidG. Aref, AhmedK. Elmagarmid
2004 The VLDB journal  
Typically, these queries involve joins, where users are usually interested only in the top-k join results.  ...  We also propose an efficient heuristic designed to optimize a top-k join query by choosing the best join order.  ...  We would like to thank Ronald Fagin for helping us with the instance optimality analysis of the rank-join algorithm.  ... 
doi:10.1007/s00778-004-0128-2 fatcat:4x3zmmcarvbtlb7gaoferyfrku

Supporting Top-k Join Queries in Relational Databases [chapter]

Ihab F. Ilyas, Walid G. Aref, Ahmed K. Elmagarmid
2003 Proceedings 2003 VLDB Conference  
Typically, these queries involve joins, where users are usually interested only in the top-k join results.  ...  We also propose an efficient heuristic designed to optimize a top-k join query by choosing the best join order.  ...  We would like to thank Ronald Fagin for helping us with the instance optimality analysis of the rank-join algorithm.  ... 
doi:10.1016/b978-012722442-8/50072-0 dblp:conf/vldb/IlyasAE03 fatcat:fly7wfewrveg5lom2arzorx4py

Using semantic links to support top-K join queries in peer-to-peer networks

Jie Liu, Liang Feng, Hai Zhuge
2007 Concurrency and Computation  
Secondly, we plan to apply the proposed approach to answering top-K join queries in XML. Finally, we plan to look for a good method of answering top-K join queries in structured P2P networks.  ...  First, we plan to incorporate query optimization techniques, such as bloom filters and ripple join algorithms, with the proposed top-K join approach to reduce the transmission cost, the response time,  ...  Figure 1 is an example of a top-K join query, where data from the ISI Web of Knowledge (ISI) and the Journal Citation Reports (JCR) are located at different peers.  ... 
doi:10.1002/cpe.1145 fatcat:c2vnwnrjlban7fq3vfi6uhgcz4

MashRank: Towards uncertainty-aware and rank-aware mashups

Mohamed A. Soliman, Mina Saleeb, Ihab F. Ilyas
2010 2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)  
To the best of our knowledge, no current tools allow for similar functionalities.  ...  The knowledge of k is only available to the root of query plan, which controls the plan execution. Similar techniques are used in [4] .  ...  Uncertain Rank Join We define the set of top-k join results J k as the set of join results (i.e., the results of a mashup) that are dominated by less than k join results.  ... 
doi:10.1109/icde.2010.5447757 dblp:conf/icde/SolimanSI10 fatcat:tfmjeviuhbgp5dulwwhvsc5ib4

Adaptive rank-aware query optimization in relational databases

Ihab F. Ilyas, Walid G. Aref, Ahmed K. Elmagarmid, Hicham G. Elmongui, Rahul Shah, Jeffrey Scott Vitter
2006 ACM Transactions on Database Systems  
In this paper, we introduce a rank-aware query optimization framework that fully integrates rank-join operators into relational query engines.  ...  To our knowledge, this is the first effort in estimating the needed input size for optimal rank aggregation algorithms.  ...  Example 1 illustrates a key-equality top-k join scenario, while Example 2 gives a general top-k join scenario.  ... 
doi:10.1145/1189769.1189772 fatcat:e5qgnwnifndmvekhwvury7p7ha

Rank-aware query optimization

Ihab F. Ilyas, Rahul Shah, Walid G. Aref, Jeffrey Scott Vitter, Ahmed K. Elmagarmid
2004 Proceedings of the 2004 ACM SIGMOD international conference on Management of data - SIGMOD '04  
We introduce a rank-aware query optimization framework that fully integrates rank-join operators into relational query engines.  ...  To our knowledge, this paper is the first effort in estimating the needed input size for optimal rank aggregation algorithms.  ...  The goal is to produce the top-k join results. We refer to this problem as top-k join.  ... 
doi:10.1145/1007568.1007593 dblp:conf/sigmod/IlyasSAVE04 fatcat:tf3ss3wfv5cetia5gwdjqvfoty

Research on optimizing top-K join queries for RDF datasets based on spark

Jinguang Gu, Hao Dong, Zhao Liu, Fangfang Xu
2016 Services Proceedings of the 2016 S2   unpublished
On this basis of the STA query algorithm, the STA algorithm and a new top-k query algorithm SSJA (Spark Simple Join Algorithm) are improved to reduce the sorting related operations for the intermediate  ...  Optimization of top-k join algorithm is another key technology.  ...  In recent years, research of the query optimization on SPARQL top-k join is on the rise.  ... 
doi:10.29268/iciot.2016.0018 fatcat:f7j2cryqtbcvrab7ttoocgf4yy

Processing of Rank Joins in Highly Distributed Systems

Christos Doulkeridis, Akrivi Vlachou, Kjetil Nørvåg, Yannis Kotidis, Neoklis Polyzotis
2012 2012 IEEE 28th International Conference on Data Engineering  
We propose a novel distributed rank-join framework that determines the subset of each relational fragment that needs to be fetched to generate the top-k join results.  ...  In addition, we demonstrate how our algorithms can utilize distributed statistics to process top-k join queries without any modifications.  ...  The algorithm performs bound estimation, fetches tuples from the servers and executes rank join (lines 6-12), similar to Algorithm 1.  ... 
doi:10.1109/icde.2012.108 dblp:conf/icde/DoulkeridisVNKP12 fatcat:mx43wfpctjdjliqdx6tgimqsbm

Optimization of decentralized multi-way join queries over pipelined filtering services

Efthymia Tsamoura, Anastasios Gounaris, Yannis Manolopoulos
2012 Computing  
To the best of our knowledge, there is no known algorithm for this problem and the evaluation results show that the proposed algorithms can yield significant performance improvements compared to naive  ...  It is assumed that W j does not contain S k join , however, the following analysis is similar when W j = W k .  ...  Also assume that S k join ∈ V j , unless it is stated otherwise (as in Lemma 4) . It is also assumed that W j does not contain S k join . The proofs are similar when W j = W k .  ... 
doi:10.1007/s00607-012-0209-9 fatcat:calnkkrp7bcynkfkznzlnlx5su

k-Anonymity in the Presence of External Databases

Dimitris Sacharidis, Kyriakos Mouratidis, Dimitris Papadias
2010 IEEE Transactions on Knowledge and Data Engineering  
Specifically, existing generalization algorithms create anonymous tables using only the microdata table (M T ) to be published, independently of the external knowledge available.  ...  k-JOIN-ANONYMITY Section 3.1 formally introduces k-join-anonymity (KJA) and presents the underlying assumptions.  ...  Section 3 introduces k-join-anonymity. Section 4 describes the methodologies for adapting k-anonymity generalization to KJA.  ... 
doi:10.1109/tkde.2009.120 fatcat:cyh4k7e6k5edpcktb5d7nn7m6u

Balance-aware distributed string similarity-based query processing system

Ji Sun, Zeyuan Shang, Guoliang Li, Dong Deng, Zhifeng Bao
2019 Proceedings of the VLDB Endowment  
Dima supports four core similarity operations, i.e., similarity selection, similarity join, top-k selection and top-k join.  ...  To the best of our knowledge, this is the first full-fledged distributed in-memory system that can support complex similarity-based query processing on largescale datasets.  ...  In particular, Dima focuses on supporting four core similarity-based operations, i.e., similarity selection, similarity join, top-k selection and top-k join.  ... 
doi:10.14778/3329772.3329774 fatcat:sorbhypaijg6rjoevbvdhxyjbm

Supporting top-K keyword search in XML databases

Liang Jeff Chen, Yannis Papakonstantinou
2010 2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)  
The algorithms essentially reduce the keyword query evaluation to relational joins, and incorporate the idea of the top-K join from relational databases.  ...  In this paper, we propose a series of join-based algorithms that combine the semantic pruning and the top-K processing to support top-K keyword search in XML databases.  ...  The selection of the join algorithms should be context-aware.  ... 
doi:10.1109/icde.2010.5447818 dblp:conf/icde/ChenP10 fatcat:k47sgudn45allpbz7lgvnpwqga

Building ranked mashups of unstructured sources with uncertain information

Mohamed A. Soliman, Ihab F. Ilyas, Mina Saleeb
2010 Proceedings of the VLDB Endowment  
Mashups are situational applications that join multiple sources to better meet the information needs of Web users.  ...  To the best of our knowledge, both the technical problems and target applications of MashRank have not been addressed before.  ...  Join-aware Sampling. Join induces correlations among join results.  ... 
doi:10.14778/1920841.1920947 fatcat:3n2fnluwfjbsxeru2rog2am7dy
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