• Annual Conference on Human and Language Technology
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• 2010.10a
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• pp.15-21
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• 2010

본 논문은 검색 서비스 기능 중에 빼놓을 수 없는 기능인 한글 검색 질의어(query) 교정 시스템을 '야후!'에서 구축하며 분석한 한글 오타 패턴 그리고 사용자 로그를 기반으로 설계한 질의어 교정 서비스에 대한 설명을 하고 있다. 이 교정 서비스는 현재 '야후! 코리아'에 적용되어 있으며, 한글을 고려한 키스트 로크를 기반으로 한 설계 방식 그리고 동적으로 에러모델을 구축하는 방법을 소개하고 있으며 또한 구축된 모델의 성능을 다른 검색 서비스와 비교한 결과를 소개한다.

• Journal of Information Management
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• v.42 no.3
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• pp.71-94
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• 2011

Query by visual example is the principal query paradigm for expressing queries in a content-based image retrieval environment. Query by image and query by sketch have long been purported as being viable methods of query formulation yet there is little empirical evidence to support their efficacy in facilitating query formulation. The ability of the searcher to express their information problem to an information retrieval system is fundamental to the retrieval process. The aim of this research was to investigate the query by image and query by sketch methods in supporting a range of information problems through a usability experiment in order to contribute to the gap in knowledge regarding the relationship between searchers' information problems and the query methods required to support efficient and effective visual query formulation. The results of the experiment suggest that query by image is a viable approach to visual query formulation. In contrast, the results strongly suggest that there is a significant mismatch between the searchers information problems and the expressive power of the query by sketch paradigm in supporting visual query formulation. The results of a usability experiment focusing on efficiency (time), effectiveness (errors) and user satisfaction show that there was a significant difference, p<0.001, between the two query methods on all three measures: time (Z=-3.597, p<0.001), errors (Z=-3.317, p<0.001), and satisfaction (Z=-10.223, p<0.001). The results also show that there was a significant difference in participants perceived usefulness of the query tools Z=-4.672, p<0.001.

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.169-189
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• 2005

In order to derive a better classifier with a limited number of training examples, active teaming alternately repeats the querying stage fur category labeling and the subsequent learning stage fur rebuilding the calssifier with the newly expanded training set. To relieve the user from the burden of labeling, especially in an on-line environment, it is important to minimize the number of querying steps as well as the total number of query examples. We can derive a good classifier in a small number of querying steps by using only a small number of examples if we can select multiple of diverse, representative, and ambiguous examples to present to the user at each querying step. In this paper, we propose a cluster-based batch query selection method which can select diverse, representative, and highly ambiguous examples for efficient active learning. Experiments with various text data sets have shown that our method can derive a better classifier than other methods which only take into account the ambiguity as the criterion to select multiple query examples.

• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.619-630
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• 2017

With the growing popularity of smart devices, various location based services have been providing to users. Recently, some location based social applications that combine social services and location based services have been emerged. The demands of a k-nearest neighbors(k-NN) query which finds k closest locations from a user location are increased in the location based social network services. In this paper, we propose an approximate k-NN query processing method for fast response time in a large number of users environments. The proposed method performs efficient stream processing using big data distributed processing technologies. In this paper, we also propose a modified grid index method for indexing a large amount of location data. The proposed query processing method first retrieves the related cells by considering a user movement. By doing so, it can make an approximate k results set. In order to show the superiority of the proposed method, we conduct various performance evaluations with the existing method.

• Journal of the Korean Society for information Management
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• v.36 no.4
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• pp.183-205
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• 2019

Among the various methods for identifying users's information needs, Log analysis methods can realistically reflect the users' actual search behavior and analyze the overall usage of most users. Based on the large quantity of query log big data obtained through the portal service of the National Archives of Korea, this study conducted an analysis by the information type and search result type in order to identify the users' information needs. The Query log used in analysis were based on 1,571,547 query data collected over a total of 141 months from 2007 to December 2018, when the National Archives of Korea provided search services via the web. Furthermore, based on the analysis results, improvement methods were proposed to improve user search satisfaction. The results of this study could actually be used to improve and upgrade the National Archives of Korea search service.

• 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 KIISE:Software and Applications
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• v.27 no.5
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• pp.551-562
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• 2000

Content-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. GContent-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. Generally, the query image produced by a user is different from the intended target image. To overcome this problem, many image retrieval systems use the spatial relationships of the objects, instead of pixel coordinates of the objects. In this paper, a query-converting algorithm for an image retrieval system, which uses the spatial relationship of every two objects as an image feature, is proposed. The proposed algorithm converts the query image into a graph that has the minimum number of edges, by eliminating every transitive edge. Since each edge in the graph represents the spatial relationship of two objects, the elimination of unnecessary edges makes the retrieval process more efficient. Experimental results show that the proposed algorithm leads the smaller number of comparison in searching process as compared with other algorithms that do not guarantee the minimum number of edges.

• Journal of Korea Spatial Information System Society
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• v.10 no.1
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• pp.15-28
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• 2008

In ubiquitous sensor networks(USN) environment, it is essential to process region query for user-demand services. Using R-tree is a preferred technique to process region query for in-network query environment. In USN environment, USN middleware must select sensors that transfers region query with accuracy because the lifetime of sensors is that of whole sensor networks. When R-tree is used, however, it blindly passes the region query including non-existent sensors where MBR(Minimum Boundary Rectangle) of R-tree is Intersected by region of query. To solve in this problem, we propose a reconstruction of region query method which is a trie-structured Quad tree in the base station that includes sensors in region of query select with accuracy. We observed that the proposed method delays response time than R-tree, but is useful for reducing communication cost and energy consumption.

• 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 information Management
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• v.23 no.2
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• pp.5-19
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• 2006

The purpose of this study is to observe and analyze information searching behaviors of various user groups in different access modes for designing user-centered query interface of content-based Music Information Retrieval System(MIRS). Two expert groups and two non-expert groups were recruited for this research. The data gathering techniques employed in this study were in-depth interviewing, participant observation, searching task experiments, think-aloud protocols, and post-search surveys. Expert users, especially majoring in music theory, preferred to input exact notes one by one using the devices such as keyboard and musical score. On the other hand, non-expert users preferred to input melodic contours by humming.