Keyword proximity search in XML trees

Hristidis, Vagelis; Koudas, Nick; Papakonstantinou, Yannis; Srivastava, Divesh

doi:10.1109/tkde.2006.1599390

Cited by 120 publications

(161 citation statements)

References 13 publications

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“…Since two objects are connected via either a reference or containment connection, line 2-3 deal with the counterparts of o via reference connection by calling getConnectedList(); line 4-7 deal with containment connection. Then it recursively finds such counterparts connecting to src indirectly in a depth limited search(line [8][9][10]. getIROGroups() in Algorithm 3 works in a similar way, the detail isn't shown due to space limit.…”

Section: Algorithmsmentioning

confidence: 99%

“…Therefore, it is desired that the search engine is able to find and extract the data fragments corresponding to the real world objects. semantics, which solve the problem by examining the data set to find the smallest common ancestors [16,13,9,7,20]. This method, while pioneering, has the drawback that its result may not be meaningful in many cases.…”

Section: Introductionmentioning

confidence: 99%

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An Effective Object-Level XML Keyword Search

Bao

Ling

et al. 2010

Database Systems for Advanced Applications

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Abstract. Keyword search is widely recognized as a convenient way to retrieve information from XML data. In order to precisely meet users' search concerns, we study how to effectively return the targets that users intend to search for. We model XML document as a set of interconnected object-trees, where each object contains a subtree to represent a concept in the real world. Based on this model, we propose object-level matching semantics called Interested Single Object (ISO) and Interested Related Object (IRO) to capture single object and multiple objects as user's search targets respectively, and design a novel relevance oriented ranking framework for the matching results. We propose efficient algorithms to compute and rank the query results in one phase. Finally, comprehensive experiments show the efficiency and effectiveness of our approach, and an online demo of our system on DBLP data is available at http://xmldb.ddns.comp.nus.edu.sg.

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Section: Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Effective Object-Level XML Keyword Search

Bao

Ling

et al. 2010

Database Systems for Advanced Applications

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“…Although many research efforts have been conducted in XML keyword search [1], [2], [3], [4], [5], none of them has addressed and resolved the above three issues yet. For instance, one widely adopted approach so far is to find the smallest lowest common ancestor (SLCA) of all keywords [3].…”

Section: Introductionmentioning

confidence: 99%

“…Each SLCA result of a keyword query contains all query keywords but has no subtree which also contains all the keywords. Since [4], [5] etc. are variations of SLCA, we use SLCA as a typical existing approach in the rest discussion.…”

Section: Introductionmentioning

confidence: 99%

“…Subsequently, SLCA (smallest LCA [9], [3]) is proposed to find the smallest LCAs that do not contain other LCAs in their subtrees. GDMCT (minimum connecting trees) [5] excludes the subtrees rooted at the LCAs that do not contain query keywords. Sun et al [10] generalize SLCA to support keyword search involving combinations of AND and OR boolean operators.…”

Section: Introductionmentioning

confidence: 99%

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Effective XML Keyword Search with Relevance Oriented Ranking

Bao

Ling

Chen

et al. 2009

2009 IEEE 25th International Conference on Data Engineering

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In this paper, we propose an IR-style approach which basically utilizes the statistics of underlying XML data to address these challenges. We first propose specific guidelines that a search engine should meet in both search intention identification and relevance oriented ranking for search results. Then based on these guidelines, we design novel formulae to identify the search for nodes and search via nodes of a query, and present a novel XML TF*IDF ranking strategy to rank the individual matches of all possible search intentions. Lastly, the proposed techniques are implemented in an XML keyword search engine called XReal, and extensive experiments show the effectiveness of our approach.

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A tool for data cube construction from structurally heterogeneous XML documents

Näppilä

Järvelin

Niemi

2007

J. Am. Soc. Inf. Sci.

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In neonates and infants with critical aortic coarctation, balloon angioplasty is considered for rescue therapy of heart failure. The use of conventional stents is limited because of further vessel growth, the need of redilation, and later surgical removal. However, a novel bioabsorbable magnesium stent (AMS) might overcome such restrictions of vessel stenting in newborns. Presented is the first use of an AMS for acute treatment of a newborn with severely impaired heart function due to a long segment recoarctation after a complex surgical repair. We hypothesize that bioabsorbable stents will dramatically change the treatment of coarctation and recoarctation in newborns. © 2006 Wiley‐Liss, Inc.

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Keyword proximity search in XML trees

Cited by 120 publications

References 13 publications

An Effective Object-Level XML Keyword Search

An Effective Object-Level XML Keyword Search

Effective XML Keyword Search with Relevance Oriented Ranking

A tool for data cube construction from structurally heterogeneous XML documents

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