• Journal of the Korean Society for information Management
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• v.30 no.2
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• pp.297-315
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• 2013

This study aims to analyze and evaluate term suggestion services of major search portals, Naver and Google Korea. In particular, this study evaluated relevance and currency of related search terms provided, and analyzed characteristics such as number and distribution of terms, and queries that did not produce terms. This study also analyzed types of terms in terms of the relationship between queries and terms, and investigated types and characteristics of harmful terms and terms with grammatical errors. Finally, Korean queries and English queries, and popular queries and academic queries were compared in terms of the amount and relevance of search terms provided. The results of this study show that the relevance and currency of Naver's related search terms are somewhat higher than those of Google. Both Naver and Google tend to add terms to or delete terms from original queries, and provide identical search terms or synonym terms rather than providing entirely new search terms. The results of this study can be implemented to the portal's effective development of term suggestion services.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.335-342
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• 2018

The search service, which is a core service of the portal site, presents search queries that are rapidly increasing among the inputted search queries based on the highest instantaneous search frequency, so it is difficult to immediately notify a search query having a high degree of interest for a certain period. Therefore, it is necessary to overcome the above problems and to provide more intelligent information retrieval service by bringing improved analysis results on the change of the search queries. In this paper, we present the criteria for measuring the interest, continuity, and attention of real-time search queries. In addition, according to the criteria, we measure and summarize changes in real-time search queries in hours, days, weeks, and months over a period of time to assess the issues that are of high interest, long-lasting issues of interest, and issues that need attention in the future.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2173-2184
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• 1997

Among spatial queries handled in spatial database systems, nearest neighbor queries to find the nearest spatial object from the given locaion occur frequently. The number of searched nodes in an index must be minimized in order to increase the performance of nearest neighbor queries. An Existing approach considered only the processing of an nearest neighbor query in a two-dimensional search space and could not optimize the number of searched nodes accurately. In this paper, we propose the optimal search distance and prove its properties. The proposed optimal search distance is the measurement of a new search distance for accurately selecting the nodes which will be searched in processing nearest neighbor queries. We present an algorithm for processing the nearest neighbor query by applying the optimal search distance to R-trees and prove that the result of query processing is correcter than the existing approach.

• Convergence Security Journal
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• v.17 no.2
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• pp.81-88
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• 2017

It is occurred frequently the reverse nearest neighbor queries to find objects where a query point can be the nearest neighbor object in recently applications like the encrypted spatial database. In a search space of the real world, however, there are many physical obstacles(e.g., rivers, lakes, highways, etc.). It is necessary the accurate measurement of distances considered the obstacles to increase the retrieval performance such as this circumstance. In this study, we present the algorithm and the measurement of distance to optimize the processing performance of reverse nearest neighbor queries in a search space with the presence of obstacles.

• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.133-138
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• 2012

Queries entered in a search box are the results of users' activities to actively seek information. Therefore, search logs are important data which represent users' information needs. The purpose of this study is to examine if there is a relationship between the results of queries automatically classified and the categories of documents accessed. Search sessions were identified in 2009 NDSL(National Discovery for Science Leaders) log dataset of KISTI (Korea Institute of Science and Technology Information). Queries and items used were extracted by session. The queries were processed using an automatic classifier. The identified queries were then compared with the subject categories of items used. As a result, it was found that the average similarity was 58.8% for the automatic classification of the top 100 queries. Interestingly, this result is a numerical value lower than 76.8%, the result of search evaluated by experts. The reason for this difference explains that the terms used as queries are newly emerging as those of concern in other fields of research.

• 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 the Korean Society for information Management
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• v.24 no.4
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• pp.255-265
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• 2007

In this paper we analyzed regularity of daily patterns of distribution of Queries coming from internet search engine. And then, we proposed a Pareto distribution and Zipf law for identifying the query distribution and applied them to daily queries on the search engine during 2 week. We found that there is some evidence that Pareto and Zipf laws can be applied to evaluate the regularity of daily patterns of distribution of queries in search engine. Those results can be used to provide a better understanding of the social interests and trends using the query distribution patterns.

• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.215-222
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• 2005

In this paper, a MetaSearch algorithm for navigational queries is presented. Previous MetaSearch algorithms focused on informational queries. They Eave a high score to an overlapped document. However, the overemphasis of overlapped documents may degrade the performance of a MetaSearch algerian for a navigational query. However, if a lot of result documents are from a certain domain or a directory, then we can assume the importance of the domain or directory. Various experiments are conducted to show the effectiveness of overlap of a domain and directory names. System results from TREC and commercial search engines are used for experiments. From the results of experiments, the overlap of documents showed the better performance for informational queries. However, the overlap of domain names and directory names showed the $10\%$ higher performance for navigational queries.

• Journal of Dental Anesthesia and Pain Medicine
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• v.21 no.2
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• pp.113-118
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• 2021

Background: Consumers and patients in the last two decades have increasingly turned to various internet search engines including Google for information. Google Trends records searches done using the Google search engine. Google Trends is free and provides data on search terms and related queries. One recent study found a large public interest in "dental anesthesia". In this paper, we further explore this interest in "dental anesthesia" and assess if any patterns emerge. Methods: In this study, Google Trends and the search term "dental pain" was used to record the consumer's interest over a five-year period. Additionally, using the search term "Dental anesthesia," a top ten related query list was generated. Queries are grouped into two sections, a "top" category and a "rising" category. We then added additional search term such as: wisdom tooth anesthesia, wisdom tooth general anesthesia, dental anesthetics, local anesthetic, dental numbing, anesthesia dentist, and dental pain. From the related queries generated from each search term, repeated themes were grouped together and ranked according to the total sum of their relative search frequency (RSF) values. Results: Over the five-year time period, Google Trends data show that there was a 1.5% increase in the search term "dental pain". Results of the related queries for dental anesthesia show that there seems to be a large public interest in how long local anesthetics last (Total RSF = 231) - even more so than potential side effects or toxicities (Total RSF = 83). Conclusion: Based on these results it is recommended that clinicians clearly advice their patients on how long local anesthetics last to better manage patient expectations.

• Journal of the Korean Society for Library and Information Science
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• v.26
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• pp.213-233
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• 1994

This study measured whether subject descriptor searching and citation searching retrieve different documents for conceptual queries and methodological queries in natural science, engineering and social science. The retrieval effectiveness of two search methods was measured using as criteria, total number of documents retrieved, total number of relevant documents, overlapping and unique documents and precision ratio. The search subject was water resources and the databases used were Selected Water Resources Abstracts (SWRA) and SCISEARCH. Data were collected for 21 doctoral students working on their dissertations in the three fields of water resources. Principal findings included: 1) subject searching and citation searching each retrieved substantially equal number of documents; 2) total number of relevant documents for conceptual queries was larger than that for methodological queries, while there was a large variation among the three fields; 3) the average overlap was quite small, while citation searching yielded more unique documents than subject searching; 4) for conceptual queries, citation searching yielded a higher precision ratio than subject searching, while subject searching obtained a slightly higher precision ratio than citation searching for methodological queries ; and 5) citation searching was effective for both specific queries and broad queries if seed articles are well chosen, while subject searching only worked well for broad queries. It was further found that: 1) citation searching is not a subsidiary but a substantial retrieval method in water resources; 2) SWRA is effective for queries for engineering and SCISEARCH is appropriate for queries for natural science, while neither SWRA nor SCISEARCH work well for queries for social science; and 3) characteristics of queries affect retrieval results more than the characteristics of documents or the coverage of databases.