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Query relaxation using malleable schemas
- In Proc. ACM SIGMOD
, 2007
"... In contrast to classical databases and IR systems, real-world information systems have to deal increasingly with very vague and diverse structures for information management and storage that cannot be adequately handled yet. While current object-relational database systems require clear and unified ..."
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Cited by 14 (2 self)
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In contrast to classical databases and IR systems, real-world information systems have to deal increasingly with very vague and diverse structures for information management and storage that cannot be adequately handled yet. While current object-relational database systems require clear and unified data schemas, IR systems usually ignore the structured information completely. Malleable schemas, as recently introduced, provide a novel way to deal with vagueness, ambiguity and diversity by incorporating imprecise and overlapping definitions of data structures. In this paper, we propose a novel query relaxation scheme that enables users to find best matching information by exploiting malleable schemas to effectively query vaguely structured information. Our scheme utilizes duplicates in differently described data sets to discover the correlations within a malleable schema, and then uses these correlations to appropriately relax the users’ queries. In addition, it ranks results of the relaxed query according to their respective probability of satisfying the original query’s intent. We have implemented the scheme and conducted extensive experiments with real-world data to confirm its performance and practicality.
Query relaxation for entityrelationship search
- In ESWC
, 1997
"... Abstract. Entity-relationship-structured data is becoming more important on the Web. For example, large knowledge bases have been automatically constructed by information extraction from Wikipedia and other Web sources. Entities and relationships can be represented by subject-property-object triples ..."
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Cited by 12 (3 self)
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Abstract. Entity-relationship-structured data is becoming more important on the Web. For example, large knowledge bases have been automatically constructed by information extraction from Wikipedia and other Web sources. Entities and relationships can be represented by subject-property-object triples in the RDF model, and can then be precisely searched by structured query languages like SPARQL. Because of their Boolean-match semantics, such queries often return too few or even no results. To improve recall, it is thus desirable to support users by automatically relaxing or reformulating queries in such a way that the intention of the original user query is preserved while returning a sufficient number of ranked results. In this paper we describe comprehensive methods to relax SPARQL-like triplepattern queries in a fully automated manner. Our framework produces a set of relaxations by means of statistical language models for structured RDF data and queries. The query processing algorithms merge the results of different relaxations into a unified result list, with ranking based on any ranking function for structured queries over RDF-data. Our experimental evaluation, with two different datasets about movies and books, shows the effectiveness of the automatically generated relaxations and the improved quality of query results based on assessments collected on the Amazon Mechanical Turk platform.
Techniques for Fast Query Relaxation in Contentbased Recommender Systems
- Proceedings of Annual German Conference on AI 2006
, 2006
"... Abstract. ‘Query relaxation ’ is one of the basic approaches to deal with unfulfillable or conflicting customer requirements in content-based recommender systems: When no product in the catalog exactly matches the customer requirements, the idea is to retrieve those products that fulfill as many of ..."
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Cited by 5 (0 self)
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Abstract. ‘Query relaxation ’ is one of the basic approaches to deal with unfulfillable or conflicting customer requirements in content-based recommender systems: When no product in the catalog exactly matches the customer requirements, the idea is to retrieve those products that fulfill as many of the requirements as possible by removing (relaxing) parts of the original query to the catalog. In general, searching for such an ‘maximum succeeding subquery ’ is a non-trivial task because a) the theoretical search space exponentially grows with the number of the subqueries and b) the allowed response times are strictly limited in interactive recommender applications. In this paper, we describe new techniques for the fast computation of ‘user-optimal ’ query relaxations: First, we show how the number of required database queries for determining an optimal relaxation can be limited to the number of given subqueries by evaluating the subqueries individually. Next, it is described how the problem of finding relaxations returning ‘at-least-n ’ products can be efficiently solved by analyzing these partial query results in memory. Finally, we show how a general-purpose conflict detection algorithm can be applied for determining ‘preferred’ conflicts in interactive relaxation scenarios. The described algorithms have been implemented and evaluated in a knowledge-based recommender framework; the paper comprises a discussion of implementation details, experiences, and experimental results. 1
XML Algebras for Data Mining
- IN THE PROCEEDINGS OF DATA MINING AND KNOWLEDGE DISCOVERY: THEORY, TOOLS, AND TECHNOLOGY
, 2004
"... The XML is a new standard for data representation and exchange on the Internet. There are studies on XML query languages as well as XML algebras in literature. However, attention has not been paid to research on XML algebras for data mining due to partially the fact that there is no widely accepted ..."
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Cited by 3 (0 self)
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The XML is a new standard for data representation and exchange on the Internet. There are studies on XML query languages as well as XML algebras in literature. However, attention has not been paid to research on XML algebras for data mining due to partially the fact that there is no widely accepted definition of XML mining tasks. This paper tries to examine the XML mining tasks and provide guidelines to design XML algebras for data mining. Some summarization and comparison have been done to existing XML algebras. We argue that by adding additional operators for mining tasks, XML algebras may work well for data mining with XML documents.
The Relaxation Manager for XML Query Relaxation
"... 2 Table of Contents Abstract............................................................................................................................... 3 1 Introduction................................................................................................................. 3 ..."
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Cited by 1 (0 self)
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2 Table of Contents Abstract............................................................................................................................... 3 1 Introduction................................................................................................................. 3
Approximate Retrieval of XML Data with ApproXPath
"... Several XML query languages have been proposed that use XPath expressions to locate data. But XPath expressions might miss some data because of irregularities in the data and schema of an XML data collection. In this paper we propose ApproXPath, which supports approximate path expressions. Approxima ..."
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Several XML query languages have been proposed that use XPath expressions to locate data. But XPath expressions might miss some data because of irregularities in the data and schema of an XML data collection. In this paper we propose ApproXPath, which supports approximate path expressions. Approximate path expressions have the same syntax as XPath expressions, but allow content and structural errors. An error is a string or tree edit operation that creates a (virtual) data collection in which the data can be located. ApproXPath extends XPath’s axes, node tests and predicates to utilize the string/tree edit distance. We show that the complexity of ApproXPath is reasonable. For many queries, the inexact matching (with no errors) is as fast as exact matching, and the cost increases linearly with the number of errors allowed. 1
Query Relaxation for Entity-Relationship Search Shady Elbassuoni Maya Ramanath
, 2010
"... Entity-relationship-structured data is becoming more important on the Web. For example, large knowledge bases have been automatically constructed by information extraction from Wikipedia and other Web sources. Entities and relationships can be represented by subject-property-object triples in the RD ..."
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Entity-relationship-structured data is becoming more important on the Web. For example, large knowledge bases have been automatically constructed by information extraction from Wikipedia and other Web sources. Entities and relationships can be represented by subject-property-object triples in the RDF model, and can then be precisely searched by structured query languages like SPARQL. Because of their Boolean-match semantics, such queries often return too few or even no results. To improve recall, it is thus desirable to support users by automatically relaxing or reformulating queries in such a way that the intention of the original user query is preserved while returning a sufficient number of ranked results. In this paper we describe comprehensive methods to relax SPARQL-like triple-pattern queries, possibly augmented with keywords, in a fully automated manner. Our framework produces a set of relaxations by means of statistical language models for structured RDF data and queries. The query
