• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.79-88
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• 2015

The web search engines are exposed to the issue of uncertainty because of ambiguous queries, being input for retrieving the accurate results. Ambiguous queries constitute a significant fraction of such instances and pose real challenges to web search engines. Moreover, web search has created an interest for the researchers to deal with search by considering context in terms of location perspective. Our proposed disambiguation approach is designed to improve user experience by using context in terms of location relevance with the document relevance. The aim is that providing the user a comprehensive location perspective of a topic is informative than retrieving a result that only contains temporal or context information. The capacity to use this information in a location manner can be, from a user perspective, potentially useful for several tasks, including user query understanding or clustering based on location. In order to carry out the approach, we developed a Java based prototype to derive the contextual information from the web results based on the queries from the well-known datasets. Among those results, queries are further classified in order to perform search in a broad way. After the result provision to users and the selection made by them, feedback is recorded implicitly to improve the web search based on contextual information. The experiment results demonstrate the outstanding performance of our approach in terms of precision 75%, accuracy 73%; recall 81% and f-measure 78% when compared with generic temporal evaluation approach and furthermore achieved precision 86%, accuracy 71%; recall 67% and f-measure 75% when compared with web document clustering approach.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.1
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• pp.71-99
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• 2016

This study investigated users' information seeking behaviors associated with their perceptions of uncertainty. For this study, the data was collected from an user group, who conducted information searches in the field of history, using the KERIS Edunet system and it was analyzed through the comparative analysis of the grounded theory. The results presented users' uncertainty in the following stages: the identification of information needs, the selection of an information system, the selection of search terms, the actual use of the system, and the evaluation of search results. Major implications pertain to the enhancement of the Edunet system and related services. The former includes the improvement of the retrieval mechanisms related to the search and display interfaces. The latter emphasizes the consideration of the origin of uncertainty in the process of the services. In other words, the study suggested to consider the inadequacy of the system functions, the insufficiency of search experiences and the lack of such abilities of particular users.

• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.111-129
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• 2009

This study examined the usability of text-based search and visual search of a large multidisciplinary library database to provide an empirical analysis of the acceptability of visual systems in the information retrieval environment. It also examined if there are differences in the usability assessment based on experimental order. The results indicated that the text-based search supported users' search behaviors more efficiently than the visual search. Also the text-based search was rated higher than the visual search in terms of user perceptions of four usability factors.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.230-237
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• 2022

The Community Social Service Investment project started as a state subsidy project in 2007 and has grown very rapidly in quantitative terms in a short period of time. It is a bottom-up project that discovers the welfare needs of people and plans and provides services suitable for them. The purpose of this study is to analyze using big data to determine the social response to local community service investment projects. For this, data was collected and analyzed by crawling with a specific keyword of community service investment project on Google and Naver sites. As for the analysis contents, monthly search volume, related keywords, monthly search volume, search rate by age, and gender search rate were conducted. As a result, 10 items were found as related keywords in Google, and 3 items were found in Naver. The overall results of Google and Naver sites were slightly different, but they increased and decreased at almost the same time. Therefore, it can be seen that the community service investment project continues to attract users' interest.

• 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.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.93-98
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• 2023

Instagram is one of the fastest-growing online photo social web services where users share their life images and videos with other users. Image tagging is an essential step for developing Automatic Image Annotation (AIA) methods that are based on the learning by example paradigm. Hashtags can be used on just about any social media platform, but they're most popular on Twitter and Instagram. Using hashtags is essentially a way to group together conversations or content around a certain topic, making it easy for people to find content that interests them. Practically on average, 20% of the Instagram hashtags are related to the actual visual content of the image they accompany, i.e., they are descriptive hashtags, while there are many irrelevant hashtags, i.e., stophashtags, that are used across totally different images just for gathering clicks and for search ability enhancement. Hence in this work, Sorting instagram hashtags all the way through mass tagging using HITS (Hyperlink-Induced Topic Search) algorithm is presented. The hashtags can sorted to several groups according to Jensen-Shannon divergence between any two hashtags. This approach provides an effective and consistent way for finding pairs of Instagram images and hashtags, which lead to representative and noise-free training sets for content-based image retrieval. The HITS algorithm is first used to rank the annotators in terms of their effectiveness in the crowd tagging task and then to identify the right hashtags per image.

• Journal of KIISE:Software and Applications
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• v.37 no.10
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• pp.745-750
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• 2010

To effectively retrieve mathematical documents including various equations, mathaware search engines are needed. In this paper, we propose a equation retrieval system which helps users effectively search structurally similar equations. The proposed system disassembles MathML equations into three types of heterogeneous indexing terms; operators, variables, and partial structures of equations. Then, it independently indexes the disassembled terms. When a user inputs a MathML equation, the proposed system searches and ranks equations using weighted sums of three language models for the heterogeneous indexing terms. In the experiments with 244,744 MathML equations, three proposed system showed reliable performances (a P@1 of 53% in the closed test and a P@1 of 63% in the open test).

• International Journal of Knowledge Content Development & Technology
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• v.1 no.1
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• pp.7-24
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• 2011

This study aims to measure the impact of these two variables on consumers' 'click-through' rates (the number of users that click on the ad compared to the number of times the ad is delivered). The result is as follows. First, search ads play a critical role in drawing consumers to advertisers' websites. Once search ads are placed, the number of visitors increased tenfold. Secondly, when search ads are keyed to highly-involved words such as 'IDC', 'hosting' and 'co-location', click-through rates significantly fluctuate according to the type of advertising message. In this case, consumers respond much more positively to ads highlighting credibility and product quality than to ads with emphasis on sales and events. Thirdly, the placement of search ads also matters. The ad placed first in the search list overpowers ads in the third or fifth place in terms of click-through rates. However, there was no significant difference of click-through rates between ads in the third place and ads in fifth. Lastly, when estimating which variable plays the bigger role in bringing traffic to advertisers' websites, consumers are more receptive to the substance of the advertising message than to its placement, under the circumstances of high involvement.

• Journal of Korean Library and Information Science Society
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• v.47 no.2
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• pp.259-286
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• 2016

The purposes of this research is designing an FRBR-based information search services based on users' needs and behaviors. Regarding this matter, this study first extensively analysed literature related to the FRBR Model. On that basis, this study categorized foreign cases by application methods of FRBR Model, and identified their characteristics. Also this study analysed how Korean users evaluated the FRBR-based information search services. Afterwards, this study discussed the overall development direction before we develop the FRBR search service in earnest. In those terms, this study selected four types of FRBR-based search services(FictionFinder, AustLit, Perseus Digital Library, Virtua) and analysed each Model's application method. Finally, this study analysed user preference of the categorization using four undergraduate and four postgraduate students of the Department of Library and Information Science.

• Journal of Korean Society of Archives and Records Management
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• v.13 no.2
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• pp.201-225
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• 2013

This study aims to investigate services of presidential archives in Korea for users who utilize holdings of the archives for scholarly purposes, as well as to examine users' perception of the services. For these purposes, the study analyzed the content of 13 U.S. presidential libraries' Web sites in terms of their research services. In addition, it examined the content of a Korean presidential archives' Web site regarding its research services. Telephone interviews of three staff members of the presidential archives were conducted to better understand the services. With this, three users who have written research papers by using presidential records were interviewed by telephone. It was found that federated search services, access by subjects, and related records of search results were considered necessary by users. A variety of digitized records should be provided online and the services needed should be changed from mere processing of FOIA requests to archival reference services to meet users' needs. Congruently, the presidential archives should provide specialized services to offer records relevant to users' research interests and to provide the compilation of selected records crucial for research.