• Journal of KIISE:Databases
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• v.33 no.5
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• pp.513-525
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• 2006

Search results of XML keyword search are defined generally as the most specific elements containing all query keywords in the literature. The labels of XML elements and semantic information such as ontology, conceptual model, thesaurus, and so on, are used to improve the preciseness of the search results. This paper presents a hierarchical index for an efficient XML keyword query processing on the condition that returnable search concepts are defined and users' query concepts can be interpreted with the help of the semantic information. The hierarchical index separately stores the XML elements containing a keyword on the basis of the hierarchical relations of the concepts that the XML elements belong to, and makes it possible to obtain least common ancestors, which are candidates for the search results, with selectively reading the elements belonging to the concepts relevant to query concepts and without considering all the combinations of the elements having been read. This paper deals with how to organize the hierarchical index and how to process XML keyword queries with the index. In our experiment with the DBLP XML document and the XML documents in the INEX2003 test set, the hierarchical index worked well.

• Journal of KIISE
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• v.41 no.9
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• pp.699-706
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• 2014

As XML documents are getting bigger and more complex, a keyword-based search method that does not require structural information is needed to search these large XML documents. In order to use this method, not only all keywords expressed as nodes in the XML document must be labeled for indexing but also structural information should be well represented. However, the existing labeling methods either have very simple information of XML documents for index or represent the structural information which is difficult to deal with the increase of XML documents' size. As the size of XML documents is getting larger, it causes either the poor performance of keyword search or the exponential increase of space usage. In this paper, we present the Repetitive Prime Labeling Scheme (RPLS) in order to improve the problem of the existing labeling methods for keyword-based search of large XML documents. This method is based on the existing prime number labeling method and allows a parent's prime number to be used at a lower level repeatedly so that the number of prime numbers being generated can be reduced. Then, we show an experimental result of the comparison between our methods and the existing methods.

• Journal of KIISE:Databases
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• v.33 no.7
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• pp.754-765
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• 2006

In XML keyword search, a search result is defined as a set of the smallest elements (i.e., least common ancestors) containing all query keywords and a granularity of indexing is an XML element instead of a document. Under the conventional index structure, all least common ancestors produced by the combination of the elements, each of which contains a query keyword, are considered as a search result. In this paper, to avoid unnecessary operations of producing the least common ancestors and reduce query process time, we describe a way to construct a partitioned index composed of several partitions and produce a search result by merging those partitions if necessary. When a search result is restricted to be composed of the least common ancestors whose depths are higher than a given minimum depth, under the proposed partitioned index structure, search systems can reduce the query process time by considering only combinations of the elements belonging to the same partition. Even though the minimum depth is not given or unknown, search systems can obtain a search result with the partitioned index, which requires the same query process time to obtain the search result with non-partitioned index. Our experiment was conducted with the XML documents provided by the DBLP site and INEX2003, and the partitioned index could reduce a substantial amount of query processing time when the minimum depth is given.

• 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 KIISE:Databases
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• v.35 no.6
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• pp.495-504
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• 2008

Recently, there has been much work on supporting keyword search not only for text documents, but a]so for structured data such as relational data, XML data, and RDF data. In this paper, we propose an efficient keyword search method for RDF data. The proposed method first groups related nodes and edges in RDF data graphs to reduce data sizes for efficient keyword search and to allow relevant information to be returned together in the query answers. The proposed method also utilizes the semantics in RDF data to measure the relevancy of nodes and edges with respect to keywords for search result ranking. The experimental results based on real RDF data show that the proposed method reduces RDF data about in half and is at most 5 times faster than the previous methods.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.710-720
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• 2004

As XML documents have much richer information than plain texts, we can perform very elaborated, fine-grained search which was difficult in past years. However, as the cost of finer grained element level search is very high, the processing overhead has become a new challenge. We propose an inverted index structure called PIX, which reduces the number of elements processed by partitioning elements according to their match potentiality. We choose a base level and partition elements according to whether they have possibility of having a common ancestor higher than the level. We also propose partition merging technique by which we can get same results as unpartitioned case. Our experimental results show that the index partitioning strategy can reduce processing time considerably.

• Journal of Computing Science and Engineering
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• v.6 no.2
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• pp.127-140
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• 2012

In this paper, we focus on efficient construction of tightest matched subtree (TMSubtree) results, for keyword queries on extensible markup language (XML) data, based on smallest lowest common ancestor (SLCA) semantics. Here, "matched" means that all nodes in a returned subtree satisfy the constraint that the set of distinct keywords of the subtree rooted at each node is not subsumed by that of any of its sibling nodes, while "tightest" means that no two subtrees rooted at two sibling nodes can contain the same set of keywords. Assume that d is the depth of a given TMSubtree, m is the number of keywords of a given query Q. We proved that if d ${\leq}$ m, a matched subtree result has at most 2m! nodes; otherwise, the size of a matched subtree result is bounded by (d - m + 2)m!. Based on this theoretical result, we propose a pipelined algorithm to construct TMSubtree results without rescanning all node labels. Experiments verify the benefits of our algorithm in aiding keyword search over XML data.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.121-140
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• 2006

UDDI (Universal Discovery Description and Integration) Registry is used for Web Services registration and search. UDDI offers the search result to the keyword-based query. UDDI supports WSDL registration but it does not supports WSDL search. So it is required that contents based search and ranking using name and description in UDDI registration information and WSDL. This paper proposes a retrieval engine considering contents of services registered in the UDDI and WSDL. It uses Vector Space Model for similarity comparison between contents of those. UDDI registry information hierarchy and WSDL hierarchy are considered during searching process. This engine suppports two discovery methods. One is Keyword-based search and the other is template-based search supporting ranking for user's query. Template-based search offers how service interfaces correspond to the query for WSDL documents. Proposed retrieval engine can offer search result more accurately than one which UDDI offers and it can retrieve WSDL which is registered in UDDI in detail.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1287-1290
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• 2011

Because of the rapid development of internet, there are more and more documents stored by the XML-based format. When there is a great deal of XML documents, how to get the valuable Information is an important subject. This paper proposes an effective XML document search method to search text contents and structures of XML documents. We build the keyword matrix of text contexts and structure matrixes of structures in XML documents to improve the efficiency of query time. When there is a great deal of XML documents, the search method we propose can improve much efficiency of query time.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.48-51
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• 2018

The traditional documents analysis was centered on words based system was implemented using a morpheme analyzer. These traditional systems can classify used words in the document but, cannot help to user's document understanding or analysis. In this problem solved, System needs extract for most valuable paragraphs what can help to user understanding documents. In this paper, we propose system extracts paragraphs of normalized XML document. User insert to system what filename when wants for analyze XML document. Then, system is search for keyword of the document. And system shows results searched keyword. When user choice and inserts keyword for user wants then, extracting for paragraph including keyword. After extracting paragraph, system operating maintenance paragraph sequence and check duplication. If exist duplication then, system deletes paragraph of duplication. And system informs result to user what counting each keyword frequency and weight to user, sorted paragraphs.