J
Jiaheng Lu
Researcher at University of Helsinki
Publications - 135
Citations - 3419
Jiaheng Lu is an academic researcher from University of Helsinki. The author has contributed to research in topics: XML database & XML. The author has an hindex of 27, co-authored 124 publications receiving 3067 citations. Previous affiliations of Jiaheng Lu include University of California, Irvine & National University of Singapore.
Papers
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Proceedings Article
From region encoding to extended dewey: on efficient processing of XML twig pattern matching
TL;DR: This paper designs a novel holistic twig join algorithm, called TJFast, which to answer a twig query only needs to access the labels of the leaf query nodes, and reports experimental results to show that these algorithms are superior to previous approaches in terms of the number of elements scanned, the size of intermediate results and query performance.
Proceedings ArticleDOI
Efficient Merging and Filtering Algorithms for Approximate String Searches
Chen Li,Jiaheng Lu,Yiming Lu +2 more
TL;DR: This paper develops several algorithms that can greatly improve the performance of existing algorithms and studies how to integrate existing filtering techniques with these algorithms, and shows that they should be used together judiciously.
Journal ArticleDOI
Big data challenge: a data management perspective
TL;DR: This paper reviews big data challenges from a data management respective, and discusses big data diversity, big data reduction,big data integration and cleaning,Big data indexing and query, and finally big data analysis and mining.
Proceedings ArticleDOI
On boosting holism in XML twig pattern matching using structural indexing techniques
TL;DR: This paper develops a method to perform holistic twig pattern matching on XML documents partitioned using various streaming schemes and can process a large class of twig patterns consisting of both ancestor-descendant and parent-child relationships and avoid generating redundant intermediate results.
Proceedings ArticleDOI
Effective XML Keyword Search with Relevance Oriented Ranking
TL;DR: This paper designs novel formulae to identify the search for nodes and search via nodes of a query, and presents a novel XML TF*IDF ranking strategy to rank the individual matches of all possible search intentions.