• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.17-24
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• 2018

One of the major issues in big data processing is extracting keywords from internet and using them to process the necessary information. Most of the proposed keyword extraction algorithms extract keywords using search function of a large portal site. In addition, these methods extract keywords based on already posted or created documents or fixed contents. In this paper, we propose a KAES(Keyword Advertisement Extraction System) system that helps the potential shopping keyword marketing to extract issue keywords and related keywords based on dynamic instant messages such as various issues, interests, comments posted on SNS. The KAES system makes a list of specific accounts to extract keywords and related keywords that have most frequency in the SNS.

• 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 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3937-3954
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• 2014

With the increasing electricity consumption and the wide application of renewable energy sources, energy auction attracts a lot of attention due to its economic benefits. Many schemes have been proposed to support energy auction in smart grid. However, few of them can achieve range query, ranked search and personalized search. In this paper, we propose an efficient multi-keyword range query (EMRQ) scheme, which can support range query, ranked search and personalized search simultaneously. Based on the homomorphic Paillier cryptosystem, we use two super-increasing sequences to aggregate multidimensional keywords. The first one is used to aggregate one buyer's or seller's multidimensional keywords to an aggregated number. The second one is used to create a summary number by aggregating the aggregated numbers of all sellers. As a result, the comparison between the keywords of all sellers and those of one buyer can be achieved with only one calculation. Security analysis demonstrates that EMRQ can achieve confidentiality of keywords, authentication, data integrity and query privacy. Extensive experiments show that EMRQ is more efficient compared with the scheme in [3] in terms of computation and communication overhead.

• IE interfaces
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• v.19 no.3
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• pp.225-235
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• 2006

In this paper, we propose an intelligent e-commerce meta-search engine which integrates distributed e-commerce sites and provides a unified search to the sites. The meta-search engine performs the following functions: (1) the user is able to create a category-based user query, (2) by using the WordNet, the query is semantically refined for increasing search accuracy, and (3) the meta-search engine recommends an e-commerce site which has the closest product information to the user’s search intention by matching the user query with the product catalogs in the e-commerce sites linked to the meta-search engine. An experiment shows that the performance of our model is better than that of general keyword-based search.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1489-1515
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• 2022

The number of interconnected real-world devices such as sensors, actuators, and physical devices has increased with the advancement of technology. Due to this advancement, users face difficulties searching for the location of these devices, and the central issue is the findability of Things. In the WoT environment, keyword-based and geospatial searching approaches are used to locate these devices anywhere and on the web interface. A few static methods of indexing and ranking are discussed in the literature, but they are not suitable for finding devices dynamically. The authors have proposed a mechanism for dynamic and efficient searching of the devices in this paper. Indexing and ranking approaches can improve dynamic searching in different ways. The present paper has focused on indexing for improving dynamic searching and has indexed the Things Description in Solr. This paper presents the Things Description according to the model of W3C JSON-LD along with the open-access APIs. Search efficiency can be analyzed with query response timings, and the accuracy of response timings is critical for search results. Therefore, in this paper, the authors have evaluated their approach by analyzing the search query response timings and the accuracy of their search results. This study utilized different indexing approaches such as key-words-based, spatial, and hybrid. Results indicate that response time and accuracy are better with the hybrid approach than with keyword-based and spatial indexing approaches.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.346-355
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• 2005

In this paper, we propose a meta-search engine which provides distributed product information through a unified access to multiple e-commerce. The meta-search engine proposed in this paper performs the following functions: (I) The user is able to create a category-based user query, (2) by using the WordNet, the query is semantical refined fined for increasing search accuracy, and (3) the meta-search engine recommends an e-commerce site which has the closest product information to the user's search intention, by matching the user query with the product catalogs in the e-commerce sites linked to the meta-search engine. An experiment shows that the performance of our model is better than that of general keyword-based search.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.10
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• pp.429-436
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• 2017

There is a growing tendency to outsource sensitive or important data in cloud computing recently. However, it is very important to protect the privacy of outsourced data. So far, a variety of secure and efficient multi-keyword search schemes have been proposed in cloud computing environment composed of a single data owner and multiple data users. Zhang et. al recently proposed a search protocol based on multi-keyword in cloud computing composed of multiple data owners and data users but their protocol has two problems. One is that the cloud server can illegally infer the relevance between data files by going through the keyword index and user's trapdoor, and the other is that the response for the user's request is delayed because the cloud server has to execute complicated operations as many times as the size of the keyword index. In this paper, we propose an improved multi-keyword based search protocol which protects the privacy of outsourced data under the assumption that the cloud server is completely unreliable. And our experiments show that the proposed protocol is more secure in terms of relevance inference between the data files and has higher efficiency in terms of processing time than Zhang's one.

• Knowledge Management Research
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• v.19 no.3
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• pp.47-61
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• 2018

A knowledge map, a taxonomy of knowledge repositories, must have capabilities supporting and enhancing knowledge user's activity to search and select proper knowledge for problem-solving. Conventional knowledge maps, however, have been hierarchically categorized, and could not support such activity that must coincide with the user's cognitive process for knowledge utilization. This paper, therefore, aims to verify and develop a methodology to build a networked knowledge map that can support user's activity to search and retrieve proper knowledge based on the referential navigation between content-relevant knowledge. This paper deploys keywords as the semantic information between knowledge, because they can represent the overall contents of a given document, and because they can play the role of semantic information on the link between related documents. By aggregating links between documents, a document network can be formulated: a keyword-based networked knowledge map can be finally built. Domain expert-based validation test was also conducted on a networked knowledge map of 50 research papers, which confirmed the performance of the proposed methodology to be outstanding with respect to the precision and recall.

• Journal of Internet Computing and Services
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• v.4 no.3
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• pp.15-22
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• 2003

Many information storage systems, such as database system, were needed to integrate much informations into one system and to provide mare voluminous lump of informations. But as the size of information system becomes larger, the responded result size of existing keyword based searching system might be too large and couldn't do the exact search which the user intends to. In this study, we proposed a paper searching method which uses RDF semantic. For this, we analyzed the structural forms of the tit1e of research papers and reconstructed them into RDF/XML. When we use these RDF descriptions of the titles to search papers, we could get more precise and accurate results than keyword based searching method.