• Journal of KIISE:Databases
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• v.33 no.4
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• pp.423-436
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• 2006

In recent years, publish-subscribe (pub-sub) systems based on XML document filtering have received much attention. In a typical pub-sub system, subscribing users specify their interest in profiles expressed in the XPath language, and each new content is matched against the user profiles so that the content is delivered only to the interested subscribers. As the number of subscribed users and their profiles can grow very large, the scalability of the system is critical to the success of pub-sub services. In this paper, we propose a novel scalable filtering system called FiST(Filtering by Sequencing Twigs) that transforms twig patterns expressed in XPath and XML documents into sequences using Prufer's method. As a consequence, instead of matching linear paths of twig patterns individually and merging the matches during post-processing, FiST performs holistic matching of twig patterns with incoming documents. FiST organizes the sequences into a dynamic hash based index for efficient filtering. We demonstrate that our holistic matching approach yields lower filtering cost and good scalability under various situations.

• Journal of KIISE:Databases
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• v.33 no.5
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• pp.538-550
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• 2006

XML Keyword search enables us to get information easily without knowledge of structure of documents and returns specific and useful partial document results instead of whole documents. Element level query processing makes it possible, but computational complexity, as the number of documents grows, increases significantly overhead costs. In this paper, we present document-level ranking scheme over XML documents which predicts results of element-level processing to reduce processing cost. To do this, we propose the notion of 'keyword proximity' - the correlation of keywords in a document that affects the results of element-level query processing using path information of occurrence nodes and their resemblances - for document ranking process. In benefit of document-centric view, it is possible to reduce processing time using ranked document list or filtering of low scored documents. Our experimental evaluation shows that document-level processing technique using ranked document list is effective and improves performance by the early termination for top-k query.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.1
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• pp.1-11
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• 2005

The paper proposes a preprocessing method for efficient processing of XML queries in information retrieval with a large amount of XML documents. The conventional preprocessing methods filter out XML documents by parsing XML document for keyword of query or by comparing query signatures with signatures of XML document to be generated. But these methods are dependent on a query and are very in efficient for a large amount of XML documents. For this, we generate a universal DTD based on ontology of a domain. The universal DTD is applicable to the XML documents when they contain information of a same domain even when they have different structures and attributes. Then, using the universal DTD, we filter out the XML documents that are not bounded in the domain. We evaluate the performance of this method through experiments.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.5
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• pp.487-497
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• 2003

There have been many filtering systems covering mail or news. Documents filtered by them consist of general text or HTML. XML is emerging as a new standard for information exchange. So, filtering systems need new approaches in dealing with XML documents. Our system suggests a method to describe user profiles with XML's ability to represent schema and structure. An user profile is made from DTD information and it is supposed to point the specific part of a document conforming to the DTD. More, it is different from the existing systems in extracting part of a document. An user profile is reflected in XML query to get part of an XML document.

• Journal of KIISE:Databases
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• v.35 no.4
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• pp.368-378
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• 2008

In recent years, publish-subscribe (pub-sub) systems based on XML document filtering have received much attention. In a typical pub-sub system, subscribed users specify their interest in profiles expressed in the XPath language, and each new content is matched against the user profiles so that the content is delivered to only the interested subscribers. As the number of subscribed users and their profiles can grow very large, the scalability of the system is critical to the success of pub-sub services. In this paper, we propose a fast and scalable XML filtering system called SFiST which is an extension of the FiST system. Sharable segments are extracted from twig patterns and stored into the hash-based Segment Table in SFiST system. Segments are used to represent user profiles as Terse Sequences and stored in the Compact Segment Index during filtering. Our experimental study shows that SFiST system has better performance than FiST system in terms of filtering time and memory usage.

• Journal of KIISE:Databases
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• v.33 no.5
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• pp.437-452
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• 2006

In this paper, we propose an extended XPath specification which includes a special matching character '%' used in the LIKE operation of SQL in order to solve the difficulty of writing some queries to filter element contents well, using the previous XPath specification. We also present a novel technique for filtering a collection of document-centric XMLs, called Pfilter, which is able to exploit the extended XPath specification. Owing to sharing the common prefix characters of the operands in value-based predicates, the Pfilter improves the performance in processing those. We show several performance studies, comparing Pfilter with Yfilter in respect to efficiency and scalability as using multi-query processing time (MQPT), and reporting the results with respect to inserting, deleting, and processing of value-based predicates. In conclusion, our approach provides a core algorithm for evaluating the contains() function of XPath queries in previous XML filtering researches, and a foundation for building XML-based distributed information systems.

• Journal of Korea Multimedia Society
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• v.8 no.5
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• pp.596-605
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• 2005

Conventional XML query methods such as simple keyword match or structural query expansion are not sufficient to catch the underlying information in the documents. Moreover, these methods inefficiently try to query all the documents. This paper proposes document tittering and query expansion methods that are based on ontology. Using ontology, we construct a universal DTD that can filter off unnecessary documents. Then, query expansion method is developed through the analysis of concept hierarchy and association among concepts. The proposed methods are applied on variety of sample XML documents to test the effectiveness.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06a
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• pp.13-14
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• 2007

• Proceedings of the Korean Information Science Society Conference
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• 2006.06c
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• pp.25-27
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• 2006

XPath 명세는 XML 원소 내용을 필터링하기 위한 질의어 작성이 어렵다. 본 논문은 이러한 문제점을 해결하기 위해 SQL의 LIKE 연산자에서 사용되던 특별한 매칭 문자 '%' 를 허용한 확장된 XPath 명세와 그것을 표준 질의어로 사용하는 문서-중심적 XML 필터링 기법인 Pfilter를 제안한다. Pfilter는 값-기반 술어(value-based predicate)에서 피연산자의 공통 앞부분 문자를 공유하여 값-기반 술어의 처리 성능을 향상시킨다. 또한 본 논문은 Pfilter와 대표적인 데이터-중심적 XML 필터링 기법인 Yfilter를 값-기반 술어 처리의 확장성과 효율성에 대해 비교하고 Pfilter의 값-기반 술어 삽입, 삭제, 처리 결과를 제공한다.

• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.661-670
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• 2006

With the development of e-Commerce and the proliferation of easily accessible information, information filtering systems such as recommender and SDI systems have become popular to prune large information spaces so that users are directed toward those items that best meet their needs and preferences. Until now, many information filtering methods have been proposed to support filtering systems. XML is emerging as a new standard for information. Recently, filtering systems need new approaches in dealing with XML documents. So, in this paper our system suggests a method to create multiform user profiles with XML's ability to represent structure. This system consists of two parts; one is an administrator profile definition part that an administrator defines to analyze users purchase pattern before a transaction such as purchase happens directly. an other is a user profile creation part module which is applied by the defined profile. Administrator profiles are made from DTD information and it is supposed to point the specific part of a document conforming to the DTD. Proposed system builds user's profile more accurately to get adaptability for user's behavior of buying and provide useful product information without inefficient searching based on such user's profile.