• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.91-100
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• 2005

It has been proposed diverse methods to use web information efficiently as the size of information is increasing. Most of search systems use a keyword-based method that mostly relies on syntactic information. They cannot utilize semantic information of documents and thus they could generate to users. To solve shortcoming in searching documents, a technique using the Semantic Web is suggested. A semantic web can find relevant information to users by employing metadata which are represented using standard ontologies. Each document is annotated with a metadata which can be reasoned by agents. In this paper, we propose a search system using semantic web technologies. Our semantic search system analyzes semantically questions that user input, and get resolution information that user want. To improve efficiency and accuracy of semantic search systems, this paper proposes DQL(DAML Query Language) engine that employs inference engine to execute reasoning and DQL converter that changes keyword form question of the user to DQL.

• Journal of Digital Contents Society
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• v.11 no.1
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• pp.105-115
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• 2010

Search engines provide web documents that are related to user's query. However, using only the query terms that user provided, it is hard for search engines to know user's exact intention and provide the very matching web documents. To remedy this problem, search systems are needed to exploit personalized search technologies. In this paper, we propose not only a novel personalized query recommendation scheme based on folksonomy but also a new personalized search service architecture which reduces the risk of privacy violation while enabling search service providers to provide other various personalized services such as personalized advertisement.

• Journal of the Korean Society for information Management
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• v.27 no.2
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• pp.37-60
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• 2010

The purpose of this study is to investigate image search query reformulation patterns in relation to image attribute categories. A total of 592 sessions and 2,445 queries from the Excite Web search engine log data were analyzed by utilizing Batley's visual information types and two facets and seven sub-facets of query reformulation patterns. The results of this study are organized with two folds: query reformulation and categorical transition. As the most dominant categories of queries are specific and general/nameable, this tendency stays over various search stages. From the perspective of reformulation patterns, while the Parallel movement is the most dominant, there are slight differences depending on initial or preceding query categories. In examining categorical transitions, it was found that 60-80% of search queries were reformulated within the same categories of image attributes. These findings may be applied to practice and implementation of image retrieval systems in terms of assisting users' query term selection and effective thesauri development.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.587-594
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• 2019

This paper proposes a personalized web search technique that produces ranked results reflecting user's query intents and individual interests. The performance of personalized search relies on an effective users' profiling strategy to accurately capture their interests and preferences. User profile is a data set of words and customized weights based on recent user queries and the topic words of web documents from their click history. Personal profile is used to expand a user query to the personalized query before the web search. To determine the exact meaning of ambiguous queries and topic words, this strategy uses WordNet to calculate semantic similarities to words in the user personal profile. Experimental results with query expansion and re-ranking modules installed on general search systems shows enhanced performance with this personalized search technique in terms of precision and recall.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.669-679
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• 2008

With the increasing demands of information sharing and searches via the web, the web search engine has drawn much attention. Although many researches have been done to solve technical challenges to build the web search engine, the issue regarding its query processing system is rarely dealt with. Since the software architecture and operational schemes of the query processing system are hard to elaborate, we here present related techniques implemented on a commercial system. The implemented system is a very large-scale system that can process 5-million user queries per day by using index files built on about 65-million web pages. We implement a multi-level cache scheme to save already returned query results for performance considerations, and the multi-level cache is managed in 4-level cache storage areas. Using the multi-level cache, we can improve the system throughput by a factor of 4, thereby reducing around 70% of the server cost.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.271-281
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• 2006

Due to the development of Internet, number of online documents and the amount of web services are increasing dramatically. However, there are several procedures required, before you actually find what you were looking for. These procedures are necessary to Internet users, but it takes time to search. As a method to systematize and simplify this repetitive job, this paper suggests a DotQuery based interactive search agent. This agent enables a user to search, from his computer, a plenty of information through the DotQuery service. which includes natural languages. and it executes several procedures required instead. This agent also functions as a plug-in service within general web browsers such as Internet Explorer and decodes the DotQuery service. Then it analyzes the DotQuery from a user through its own program and acquires service results through multiple browsers of its own.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.285-292
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• 2013

The method of recent information retrieval passes into an semantic search to provide more accurate results than keyword-based search. But in common user case, they are still accustomed to using existing keyword-based search. Hence they are hard to create a typed structured query language. In this paper, we propose to ontology knowledge-base scheme for query interpretation of these user. The proposed scheme was designed based on the OWL-DL for description logic reasoning, it can provide a richer representation of the relationship between the object by using SWRL(Semantic Web Rule Language). Finally, we are describe the experimental results of the similarity measurement for verification of a user query semantic interpretation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2468-2487
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• 2015

In web searching, trustable and precise results are greatly affected by the inherent uncertainty in the input queries. Queries submitted to search engines are by nature ambiguous and constitute a significant proportion of the instances given to web search engines. Ambiguous queries pose real challenges for the web search engines due to versatility of information. Temporal based approaches whereas somehow reduce the uncertainty in queries but still lack to provide results according to users aspirations. Web search science has created an interest for the researchers to incorporate contextual information for resolving the uncertainty in search results. In this paper, we propose an Adaptive Disambiguation Approach (ADA) of hybrid nature that makes use of both the temporal and contextual information to improve user experience. The proposed hybrid approach presents the search results to the users based on their location and temporal information. A Java based prototype of the systems is developed and evaluated using standard dataset to determine its efficacy in terms of precision, accuracy, recall, and F1-measure. Supported by experimental results, ADA demonstrates better results along all the axes as compared to temporal based approaches.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.169-179
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• 2018

Recently, web search query information has been applied in advanced predictive model research. Google dominates the global web search market in the Korean market; however, Naver possesses a dominant market share. Based on this characteristic, this study intends to compare the utility of the Korean web search query information of Google and Naver using predictive models. Therefore, this study develops three time-series predictive models to estimate the youth unemployment rate in Korea using the ARIMA model. Model 1 only used the youth unemployment rate in Korea, whereas Models 2 and 3 added the Korean web search query information of Naver and Google, respectively, to Model 1. Compared to the predictability of the models during the training period, Models 2 and 3 showed better fit compared with Model 1. Models 2 and 3 correlated different query information. During predictive periods 1 (continuous with the training period) and 2 (discontinuous with the training period), Model 3 showed the best performance. During predictive period 2, only Model 3 exhibited a significant prediction result. This comparative study contributes to a general understanding of the usefulness of Korean web query information using the Naver and Google search engines.

• The Journal of Society for e-Business Studies
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• v.13 no.3
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• pp.85-101
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• 2008

The semantic web is taken as next generation standards of information exchange on the internet to overcome the limitations of the current web. To utilize the information on the semantic web, tools are required the functionality of query search and reasoning for the ontology. However, most of semantic web management tools cannot efficiently support the search for the complex query because they apply Triple-based storage structure about RDF metadata. We design the storage structure of the ontology in corresponding with the structure of ontology data and develop the search system(SMART-DLTriple) to support complex query search efficiently in this research. The performance of the system using new storage structure is evaluated to compare with the popular semantic web management systems. The proposed method and system make a contribution to enhancement of a practical ontology reasoning systems due to improved performance of the ontology search.