• Journal of the Korea Society of Computer and Information
• /
• v.22 no.2
• /
• pp.97-104
• /
• 2017

In semantic information retrieval, we first need to build domain ontology and second, we need to convert the users' search keywords into a standard query such as SPARQL. In this paper, we propose a method that can automatically convert the users' search keywords into the SPARQL queries. Furthermore, our method can ensure effective performance in a specific domain such as law. Our method constructs the keyword history ontology by associating each keyword with a series of information when there are multiple keywords. The constructed ontology will convert keyword history ontology into SPARQL query. The automatic transformation method of SPARQL query proposed in the paper is converted into the query statement that is deemed the most appropriate by the user's intended keywords. Our study is based on the existing legal ontology constructions that supplement and reconstruct schema and use it as experiment. In addition, design and implementation of a semantic search tool based on legal domain and conduct experiments. Based on the method proposed in this paper, the semantic information retrieval based on the keyword is made possible in a legal domain. And, such a method can be applied to the other domains.

• Journal of Digital Convergence
• /
• v.11 no.7
• /
• pp.193-199
• /
• 2013

In this paper, a user search history based potential query recommendation system is proposed to enable the user of information search system to represent one's potential desire for information in terms of query and to facilitate the desired information to be searched. The proposed system has analyzed the association with the existing users's search histories based on the users' search query, and it has extracted the users's potential desire for information. The extracted potential desire for information is represented in terms of recommended query and thereby made recommendations to users. In order to analyze the effectiveness of the system proposed in this paper, we conducted behavioral experiments by using search histories of 27656. As a result of behavioral experiments, the experiment subjects were found to show a statistically significant higher level of satisfaction when using the proposed system as compared to using general search engines.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.12
• /
• pp.117-123
• /
• 2017

The personalized search algorithm is a search system that analyzes the user's IP, cookies, log data, and search history to recommend the desired information. As a result, users are isolated in the information frame recommended by the algorithm. This is called 'Filter bubble' phenomenon. Most of the personalized data can be deleted or changed by the user, but data stored in the service provider's server is difficult to access. This study suggests a way to neutralize personalization by keeping on sending random query words. This is to confuse the data accumulated in the server while performing search activities with words that are not related to the user. We have analyzed the rank change of the URL while conducting the search activity with 500 random query words once using the personalized account as the experimental group. To prove the effect, we set up a new account and set it as a control. We then searched the same set of queries with these two accounts, stored the URL data, and scored the rank variation. The URLs ranked on the upper page are weighted more than the lower-ranked URLs. At the beginning of the experiment, the difference between the scores of the two accounts was insignificant. As experiments continue, the number of random query words accumulated in the server increases and results show meaningful difference.

• Journal of Multimedia Information System
• /
• v.4 no.3
• /
• pp.99-106
• /
• 2017

This study does a qualitative and quantitative analysis of how music by humming is being used by music educators in the classroom. Music by humming is part division of music information retrieval. In order to define what a music information retrieval system is first I need to define what it is. Berger and Lafferty (1999) define information retrieval as "someone doing a query to a retrieval system, a user begins with an information need. This need is an ideal document- perfect fit for the user, but almost certainly not present in the retrieval system's collection of documents. From this ideal document, the user selects a group of identifying terms. In the context of traditional IR, one could view this group of terms as akin to expanded query." Music Information Retrieval has its background in information systems, data mining, intelligent systems, library science, music history and music theory. Three rounds of surveys using question pro where completed. The study found that there were variances in knowledge, training and level of awareness of query by humming, music information retrieval systems. Those variance relationships where based on music specialty, level that they teach, and age of the respondents.

• Herbal Formula Science
• /
• v.25 no.1
• /
• pp.39-49
• /
• 2017

Objectives : The contents of the literature associated with the medical records were entered into the database. We want to find the structure and search methods for efficient utilization of the database. Methods : The contents were entered into the database using the 'Access 2014 of the MS'. The Query Sentences were created and utilized for a search. Results : We could find information about the prescriptions, medical records and patients by the herbs and symptom combinations using the single table named 'Integrated Knowledge' and queries. Integrated Knowledge is a table that gathered patient information, prescription information and symptom information together. Conclusions : If you store patient, prescription and symptom information on a single table, you could search and use the results by various combinations of the various elements included in the table. These results could help curing patients on the basis of evidence-based treatment at the clinics.

• ETRI Journal
• /
• v.11 no.2
• /
• pp.120-136
• /
• 1989

최근의 데이터 베이스 응용분야에 있어서 시간에 따른 정보의 변화를 유지관리할 필요성이 대두되고 대용량의 기억장치 가격의 급속한 감소와 함께 이의 이용 기술이 향상되면서 시간주기에 따라 실세계의 상태에 대한 변경과정을 표현하는 시간 즉, 데이터의 변경이력을 지원하는 데이터베이스(Terporal Database)에 관심이 집중되고 있으며, 이러한 요구를 만족시키기 위한 여러 방법들이 연구되고 있다. 일반적으로 시간 지원 데이터베이스 모델은 지원되는 시간의 형태에 따라 Static, Static Rollback, Historical, Temporal, Revision 데이터베이스 모델로 나뉘어진다. 본 논문에서는 시간 및 변경이력을 지원하기 위한 데이터베이스 모델과 이를 위한 데이터베이스 시스템의 주요 설계 Issue들에 관하여 조사분석한 다음, Static Rollback 데이터베이스 모델을 기본으로 하는 "$SR^2DBS$: 시간 지원 데이터베이스 시스팀"의 설계 및 구현에 관하여 기술하였다. $SR^2DBS$은 기존의 관계형 데이터 베이스 시스팀"의 모델을 시간 애트리뷰트를 추가시킴으로서 데이터 베이스의 변경이력관리를 가능케 한 Direct Manipulation Database Processing System으로 데이터베이스의 현상태 뿐만 아니라 시간에 따른 변경이력에 대해서 Screenoriented Relation Browsing & Editing 기능을 제공하며, 다음과 같은 특징을 갖는다. - Screen oriented Processing - Directi-Manipulation of Objects - Object & Revision History of Interest Visibility - Rapid Reversible Actions - Transaction Time & Revision Number Supporting - Roll-back Query Supporting - Han-gul Data Supporting - Two level Storage Structure(Current Version & History Versions)

• The KIPS Transactions:PartB
• /
• v.18B no.4
• /
• pp.231-240
• /
• 2011

Many search algorithms have been implemented by many researchers on the world wide web. One of the best algorithms is Google using PageRank technology. PageRank approach computes the number of inlink of each documents then ranks documents in the order of inlink members. But it is difficult to find the results that user needs, because this method find documents not valueable for a person but valueable for the public. To solve this problem, We use the WordNet for analysis of the user's query history. This paper proposes a personalized search engine using the user's query history and PageRank Check. We compared the performance of the proposed approaches with google search results in the top 30. As a result, the average of the r-precision for the proposed approaches is about 60% and it is better as about 14%.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.2
• /
• pp.690-696
• /
• 2016

Search engines that rely on morphological matching of user query and web document content do not support individual interests. This research proposes a personalized web search scheme that returns the results that reflect the users' query intent and personal preferences. The performance of the personalized search depends on using an effective user profiling strategy to accurately capture the users' personal interests. In this study, the user profiles are the databases of topic words and customized weights based on the recent user queries and the frequency of topic words in click history. To determine the precise meaning of ambiguous queries and topic words, this strategy uses WordNet to calculate the semantic relatedness to words in the user profile. The experiments were conducted by installing a query expansion and re-ranking modules on the general web search systems. The results showed that this method has 92% precision and 82% recall in the top 10 search results, proving the enhanced performance.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.3
• /
• pp.587-594
• /
• 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.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.6 no.4
• /
• pp.37-50
• /
• 2003

In the paper, we describe the query extension techniques for spatiotemporal query functionalities on object-relational DBMS. The spatial objects in real world change the shapes over time. Spatiotemporal databases support to manage a temporal dimension as well as a spatial dimension for history of the objects. The proposed techniques can make conventional object-relational databases to support spatiotemporal databases system by the implementation and inheritance of abstract data types. We define and implement spatial and temporal classes as superclass. And, spatiotemporal classes inherits and extends the classes. The proposed extensions make it easy that conventional database systems not only are transformed into the spatiotemporal database systems, but also do not need to be changed to support spatiotemporal applications.