Tree Pattern Relaxation

Amer-Yahia, Sihem; Cho, SungRan; Srivastava, Divesh

doi:10.1007/3-540-45876-x_32

Cited by 132 publications

(155 citation statements)

References 12 publications

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“…In the tree relaxation approach [2] exact and relaxed weights are associated with query nodes and edges. The score of a match is computed as the sum of the corresponding weights, and the relaxed weight is function of the transformations applied to the tree.…”

Section: Related Workmentioning

confidence: 99%

“…The key idea in path scoring is to decompose the twig query into paths, independently compute the score of each path, and then combine these scores. [21] On content and tag Node insertion Structure dependent [2] On content and tag Delete node, relax edge, promote node Structure dependent approXQL On content and tag Node insertion, node deletion Structure dependent [3] On content and tag Edge generalization, leaf deletion, subtree promotion Structure dependent…”

Section: Related Workmentioning

confidence: 99%

“…For example, in [23] a dynamic programming algorithm for ranking query results according to a cost function is proposed. In [2] a data pruning algorithm is presented where intermediate query results are filtered dynamically during evaluation process. ATreeGrep [24], instead, uses as basis an exact matching algorithm, but allowing a fixed number of ''differences'' in the result.…”

Section: Related Workmentioning

confidence: 99%

“…Starting from the user query, the approaches [2][3][4][5], for structural and content scoring of XML documents, generates relaxations of the query structure that preserve the ancestor-descendant relationships existing among nodes in the query. These relaxations do not consider the effective presence of such a structure in the collection of documents.…”

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

Fragment-based approximate retrieval in highly heterogeneous XML collections

Sanz

Mesiti

Guerrini

et al. 2008

Data & Knowledge Engineering

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Due to the heterogeneous nature of XML data for internet applications exact matching of queries is often inadequate. The need arises to quickly identify subtrees of XML documents in a collection that are similar to a given pattern. Similarity involves both tags, that are not required to coincide, and structure, in which not all the relationships among nodes in the tree structure are strictly preserved.In this paper we present an efficient approach to the identification of similar subtrees, relying on ad-hoc indexing structures. The approach allows to quickly detect, in a heterogeneous document collection, the minimal portions that exhibit some similarity with the pattern. These candidate portions are then ranked according to their actual similarity. The approach supports different notions of similarity, thus it can be customized to different application domains. In the paper, three different similarity measures are proposed and compared. The approach is experimentally validated and the experimental results are extensively discussed.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Fragment-based approximate retrieval in highly heterogeneous XML collections

Sanz

Mesiti

Guerrini

et al. 2008

Data & Knowledge Engineering

View full text Add to dashboard Cite

show abstract

“…Clearly this is not efficient due to the large number of queries that need to be generated. Instead of reordering the initial query, relaxing techniques can be used to change its form and search for answers in local data sources [8,19]. For example, query /new/monitors/CRT/17 ′′ can be relaxed to /new/monitors//17 ′′ , where '//' denotes ancestor-descendand relationship.…”

mentioning

confidence: 99%

Semantic Integration of Tree-Structured Data Using Dimension Graphs

Dalamagas

Theodoratos

Koufopoulos

et al. 2005

Lecture Notes in Computer Science

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Abstract. Nowadays, huge volumes of Web data are organized or exported in tree-structured form. Popular examples of such structures are product catalogs of e-market stores, taxonomies of thematic categories, XML data encodings, etc. Even for a single knowledge domain, name mismatches, structural differences and structural inconsistencies raise difficulties when many data sources need to be integrated and queried in a uniform way. In this paper, we present a method for semantically integrating tree-structured data. We introduce dimensions which are sets of semantically related nodes in tree structures. Based on dimensions, we suggest dimension graphs. Dimension graphs can be automatically extracted from trees and abstract their structural information. They are semantically rich constructs that provide query guidance to pose queries, assist query evaluation and support integration of tree-structured data. We design a query language to query tree-structured data. The language allows full, partial or no specification of the structure of the underlying tree-structured data used to issue queries. Thus, queries in our language are not restricted by the structure of the trees. We provide necessary and sufficient conditions for checking query satisfiability and we present a technique for evaluating satisfiable queries. Finally, we conducted several experiments to compare our method for integrating tree-structured data with one that does not exploit dimension graphs. Our results demonstrate the superiority of our approach.

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CoXML: Cooperative XML Query Answering?

Chu

Liu

2007

Wiley Encyclopedia of Computer Science and Engineering

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The heterogeneity nature of XML data creates the need for approximate query answering. Approximate answers may be derived by relaxing query conditions to less restricted forms, i.e., query relaxation . In this article, we first present an approach to XML query relaxation based on schema conversion, which leverages on the value relaxation techniques in the relational model. This approach, however, does not support structure relaxation. Also, information may be lost during schema conversion. To remedy these shortcomings, we then present a cooperative XML (CoXML) system provides user‐specific approximate query answers directly in the XML model. The key features of the system include: a query language that allows users to specify approximate query conditions and relaxation control requirements; a relaxation index structure, XTAH, that enables the system to provide user‐desired relaxations as specified in the queries; and a ranking model that incorporates both content and structure similarities in evaluating the relevancy of approximate answers. We also present a scalable and extensible architecture for the CoXML system based on mediators. Finally, we evaluate the system using the INEX test collections. The evaluation results demonstrate the effectiveness of the system in providing user‐specific relaxation.

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Tree Pattern Relaxation

Cited by 132 publications

References 12 publications

Fragment-based approximate retrieval in highly heterogeneous XML collections

Fragment-based approximate retrieval in highly heterogeneous XML collections

Semantic Integration of Tree-Structured Data Using Dimension Graphs

CoXML: Cooperative XML Query Answering?

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