• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2840-2861
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• 2020

The purpose of this survey-based study is to make an analysis of search engine users' behaviors on the Search Engine Results Pages (SERPs) based on the three demographic characteristics gender, age, and program studying. In this study, a questionnaire was designed with 12 closed-ended questions. Remaining questions other than the demographic characteristic related ones were about "tab", "advertisement", "spelling suggestion", "related query suggestion", "instant search suggestion", "video result", "image result", "pagination" and the amount of clicking results. The questionnaire was used and the data collected were analyzed with the descriptive statistics as well as the inferential statistics. 84.2% of the study population was reached. Some of the major results are as follows: Most of each demographic characteristic category (i.e. female, male, under-20, 20-24, above-24, English computer engineering, Turkish computer engineering, software engineering) have rarely or more click for tab, spelling suggestion, related query suggestion, instant search suggestion, video result, image result, and pagination. More than 50.0% of female category click advertisement rarely; however, for the others, 50.0% or more never click advertisement. For every demographic characteristic category, between 78.0% and 85.4% click 10 or fewer results. This study would be the first attempt with its complete content and design. Search engine providers and researchers would gain knowledge to user behaviors about the usage of the SERPs based on the demographic characteristics.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.724-729
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• 2011

Information retrieval is a method to search the needed data by users. Generally, when a user searches some data in the large scale data set like the internet, ranking-based search is widely used because it is not easy to find the exactly needed data at once. In this paper, we propose a novel ranking-based search method based on sequence and adjacency relationship of user query by the help of TF-IDF and n-gram. As a result, it was possible to find the needed data more accurately with 73% accuracy in more than 19,000 data set.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.97-104
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• 2010

In this paper, mesh network structure is applied to solve the load balancing problems in the Grid database. Data of the Grid database is replicated to several node for enhanced performance. Therefore, load balancing for user's query is selected node that evaluated workload in it. Existing researches are using passive load balancing method that selected another node after then node overflowed workload. It is inefficient to be applied to Gird database that has a number of node and user's queries almost changes dynamically. The proposed method connected each node which includes the same data through mesh network structure. When user's query occurs, it select node that has the lowest workload. The performance evaluation shows that proposed method performs better than the existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.424-431
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• 2012

In information retrieval, search engine provide the rank of web page and the summary of the web page information to user. Snippet is a summaries information of representing web pages. Visiting the web page by the user is affected by the snippet. User sometime visits the wrong page with respect to user intention when uses snippet. The snippet extraction method is difficult to accurate comprehending user intention. In order to solve above problem, this paper proposes a new snippet extraction method using fuzzy implication operator and relevance feedback. The proposed method uses relevance feedback to expand the use's query. The method uses the fuzzy implication operator between the expanded query and the web pages to extract snippet to be well reflected semantic user's intention. The experimental results demonstrate that the proposed method can achieve better snippet extraction performance than the other methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.137-142
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• 2012

Snippet is a summaries information of representing web pages which search engine provides user. Snippet and page rank in search engine abundantly influence user for visiting web pages. User sometime visits the wrong page with respect to user intention when uses snippet. The snippet extraction method is difficult to accurate comprehending user intention. In order to solve above problem, this paper proposes a new snippet extraction method using fuzzy association and pseudo relevance feedback. The proposed method uses pseudo relevance feedback to expand the use's query. It uses the fuzzy association between the expanded query and the web pages to extract snippet to be well reflected semantic user's intention. The experimental results demonstrate that the proposed method can achieve better snippet extraction performance than the other methods.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.31-36
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• 2019

A chatbot is an important area of mobile service, which understands informal data of a user as a conversational form and provides a customized service information for user. However, there is still a lack of a service way to fully understand the user's natural language typed query dialogue. Therefore, in this paper, we extract meaningful words, such a region, a food category, and a restaurant name from user's dialogue sentences for recommending a restaurant. and by comparing the extracted words against the contents of the knowledge database that is built from the hashtag for recommending a restaurant in SNS, and provides user target information having statistically much the word-similarity. In order to evaluate the performance of the restaurant recommendation chatbot system implemented in this paper, we measured the accessibility of various user query information by constructing a web-based mobile environment. As a results by comparing a previous similar system, our chabot is reduced by 37.2% and 73.3% with respect to the touch-count and the cutaway-count respectively.

• Journal of KIISE:Databases
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• v.33 no.7
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• pp.668-681
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• 2006

Due to its diverse advantages, XML has secured its position as a standard for data representation and exchange in the Internet. As a consequence, there has been much research on efficient storing and query processing of in data. Storing XML data in a relational database system warrants much benefit in data management and query processing; the system provides a strong query processing and data management function and can be applicable to XML data, its function being extended. In this paper, we design and implement a query translator that translates XQuery, a representative XML query language, into SQL:2003 query. SQL:2003, the latest SQL standard used as a substitute for SQL:1999, defines SQL/XML that supports XML. The main contribution of this paper is as follows: First, we look into the supporting features of XML, defined in the SQL:2003 standard, and propose a user-defined function for shortcoming sections. Second, we propose a way to translate XQuery into SQL that observes the latest SQL standard. Third, we describe in detail the design and the implementation of the translator to show its feasibility as a translator.

• Journal of the Korean Society for information Management
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• v.23 no.2
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• pp.61-79
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• 2006

To come up with the recommendations to improve the patent & trademark retrieval efficiency, 100,016 patent & trademark search requests by 17,559 unique users over a period of 193 days were analyzed. By analyzing 2,202 multi-query sessions, where one user issuing two or more queries consecutively, we discovered a number of retrieval efficiency improvements clues. The session analysis result also led to suggestions for new system features to help users reformulating queries. The patent & trademark retrieval users were found to be similar to the typical web users in certain aspects especially in issuing short queries. However, we also found that the patent & trademark retrieval users used Boolean operators more than the typical web search users. By analyzing the multi-query sessions, we found that the users had five intentions in reformulating queries such as paraphrasing, specialization, generalization, alternation, and interruption, which were also used by the web search engine users.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.384-396
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• 2003

Hybrid query processing method is used for preventing server overload that is created by heavy user connection in Web GIS. In Hybrid query processing method, both server and client participate in spatial query processing. But, Hybrid query processing method is restricted in scalability of server and it can't be fundamentally solution for server overload. So, it is necessary for Web GIS to be brought in web clustering technique. In this thesis, we propose load-balancing method that uses proximity of query region. In this paper, we create tile groups that have relation each tile in same group is very close, and forward client request to the server that can have maximum rate of buffer reuse with considering characteristic of spatial query. With out load balancing method, buffet in server is optimized for exploring spatial index tree and increase rate of buffer reuse, so it can be reduced amount of disk access and increase system performance.

• Korean Journal of Cognitive Science
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• v.14 no.1
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• pp.29-40
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• 2003

Cross-Language Information Retrieval (CLIR) deals with the documents in various languages by one language query. A user who uses one language can retrieve the documents in another language through CLIR system. In CLIR, query translation method is known to be more efficient. For the better performance of query translation, we need more resources like dictionary, ontology, and parallel/comparable corpus but usually not available. This paper proposes a new concept called the Common Base Axis which is adapted to Korean-English Query translation ann a new weighting method in dictionary based query translation. The essential idea is that we can express Korean and English word in one vector space by Common Base Axis and use it in calculating sense distance for query weighting. The experiments show that Common Base Axis gives us good performance without ontology and is especially good for one word query translation.