• 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 KIISE:Software and Applications
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• v.31 no.8
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• pp.1101-1112
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• 2004

In this paper, we propose a Web page weighting scheme using the user preference in each sense of query word to improve the performance of Web search. Generally search engines assign weights to a web page by using relevancy only, which is obtained by comparing the query word and the words in a web page. In the information retrieval from huge data such as the Web, simple word comparison cannot distinguish important documents because there exist too many documents with similar relevancy In this paper we implement a WordNet-based user interface that helps to distinguish different senses of query word, and constructed a search engine in which the implicit evaluations by multiple users are reflected in ranking by accumulating the number of clicks. In accumulating click counts, they are stored separately according to senses, so that more accurate search is possible. The experimental results with several keywords show that the precision of proposed system is improved compared to conventional search engines.

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.147-152
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• 2010

The Internet has become a major channel of business marketing and sales, and there is a core competitive object between websites for a high position ranking in search engine results. There are various ways to maintain the high position ranking of website involving the development of componental coding or the expensive investment for the search engine optimization. The purpose of this paper is proposed to identify and rank the negative elements of website visibility to get rid of those elements when website designer designs the webpage. Website can be removed from indices of search engines when they are not satisfied for search engine optimization. The proposed experiments that are identified and ranked the negative elements of website visibility in this paper are based on the theories and experiments of existing website visibility models. The experimental analyses in this paper are scored and normalized based on methodologies of those models and 10 highest negative elements are ranked through the analyses. Therefore when website is designed, these highest negative elements should be avoided so website can not be removed in the indices of search engines.

• Journal of KIISE:Software and Applications
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• v.33 no.7
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• pp.646-654
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• 2006

Directory searching and index searching methods are two main methods in web search engines. Both of the methods are applied to most of the well-known Internet search engines, which enable users to choose the other method if they are not satisfied with results shown by one method. That is, Index searching tends to come up with too many search results, while directory searching has a difficulty in selecting proper categories, frequently mislead to false ones. In this paper, we propose a novel method in which a category hierarchy is dynamically constructed. To do this, a category is regarded as a fuzzy set which includes keywords. Similarly extensible subcategories of a category can be found using fuzzy relational products. The merit of this method is to enhance the recall rate of directory search by expanding subcategories on the basis of similarity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.75-77
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• 2021

A variety of search engines are currently in use. The search engine supports the retrieval of data required by users through three stages: crawling, index generation, and output of search results based on meta-tag information. However, a large number of documents obtained by searching for keywords are often unrelated or scarce. Because of these problems, it takes time and effort to grasp the content from the search results and classify the accuracy. The index of search engines is updated periodically, but the criteria for weighted values and update periods are different from one search engine to another. Therefore, this paper uses the LSTM model, which extracts the relationship between keywords entered by the user and documents instead of the existing search engine, and improves the relationship between keywords and documents by entering keywords that the user wants to find.

• Journal of Korean Library and Information Science Society
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• v.31 no.4
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• pp.191-212
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• 2000

This study is intlded to ampre the effectiveness of the Northemlight and Google, which are based on Datamining kdmique with a Metacrawler, one of metasearch engines. As a result, searches responding to queries in the Northemlight and Google produced a higher precision and recall as comparrd with searches nspcdhg to queries in the metacrawler. The results show that the Datamining techniques can help improve information retrieval effectinveness.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.13 no.1
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• pp.43-57
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• 2002

Modern society is called as an intelligence society that many companies need information and intelligence as factors for good production. So many knowledge workers want to seek information by himself easily and effectively. As a result of this study, the using search engines in internet is not effective for the competitive intelligence. This thesis suggests some methods for effective searching methods for competitive intelligence. The first method is intensive searching for special site and the second is customized information service and the last is using of the limited function in search engines.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.216-221
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• 2005

The rapid growth and spread of the World Wide Web has made it possible to easily access a variety of useful information. It is, however, very difficult to retrieve, manage, and use the desired information in web. Various kinds of systems such as Search engines, MetaSearch engines, Spiders, Softbots, Intelligent Agents or Web Agents have been developed by a large number of researchers and companies. Those systems as intelligent agent are employed to avoid the overload of information. To efficiently improve the Software Agents, it is necessary to represent and classify the retrieved data. And to improve performance of the Intelligent Agents to create the classification, it is offered how to evaluate the propriety with other information retrieved from the Web and to recommend to the user the most suitable information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.445-447
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• 2016

SQLite, Realm, etc. are database engines which are suitable for small devices that have large resource restriction and are used a lot in mobile devices based on Linux. These engines are open source programs and have advantages which are lighter weight and faster speed than general purpose databases. This paper implements performance test program and performs performance experiment of SQLite database to test search efficiency in Linux environments. The experiment is processed by comparison with the results of a Oracle database working out at the same environment.

• Culinary science and hospitality research
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• v.9 no.3
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• pp.155-168
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• 2003

As people's interest about food service rises, curiosity about correct foodservice company's information is rising on own inclination and necessity than usual foodservice company. Full text search site that do to foodservice company hereupon is operated, it is becoming menu that do not fall in name of ' Eumsikjeomchatgi ' in a representative search site such as Yahoo, Empas, Hanmir and so on. But, is not beam margin battle array that these search engines find data that they want being applied perfectly in site FACE that is use up to now. Also, is looked that there is problem about practical use service and search. Because search effect of site by that investigate consumers' awareness and practical use turkey for foodservice company search site and diagnose present level, it is thing to grope improvement. This research may supply one suggestion point establishing by more effective marketing communication strategy through internet hereafter.